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Sample records for modeling blast-related brain

  1. The nature of white matter abnormalities in blast-related mild traumatic brain injury

    Directory of Open Access Journals (Sweden)

    Jasmeet P. Hayes

    2015-01-01

    Full Text Available Blast-related traumatic brain injury (TBI has been a common injury among returning troops due to the widespread use of improvised explosive devices in the Iraq and Afghanistan Wars. As most of the TBIs sustained are in the mild range, brain changes may not be detected by standard clinical imaging techniques such as CT. Furthermore, the functional significance of these types of injuries is currently being debated. However, accumulating evidence suggests that diffusion tensor imaging (DTI is sensitive to subtle white matter abnormalities and may be especially useful in detecting mild TBI (mTBI. The primary aim of this study was to use DTI to characterize the nature of white matter abnormalities following blast-related mTBI, and in particular, examine the extent to which mTBI-related white matter abnormalities are region-specific or spatially heterogeneous. In addition, we examined whether mTBI with loss of consciousness (LOC was associated with more extensive white matter abnormality than mTBI without LOC, as well as the potential moderating effect of number of blast exposures. A second aim was to examine the relationship between white matter integrity and neurocognitive function. Finally, a third aim was to examine the contribution of PTSD symptom severity to observed white matter alterations. One hundred fourteen OEF/OIF veterans underwent DTI and neuropsychological examination and were divided into three groups including a control group, blast-related mTBI without LOC (mTBI - LOC group, and blast-related mTBI with LOC (mTBI + LOC group. Hierarchical regression models were used to examine the extent to which mTBI and PTSD predicted white matter abnormalities using two approaches: 1 a region-specific analysis and 2 a measure of spatial heterogeneity. Neurocognitive composite scores were calculated for executive functions, attention, memory, and psychomotor speed. Results showed that blast-related mTBI + LOC was associated with greater odds of

  2. Neural and Behavioral Sequelae of Blast-Related Traumatic Brain Injury

    Science.gov (United States)

    2012-11-01

    cerebral dysfunction and/or cognitive deficit (e.g., cerebral palsy , mental retardation, epilepsy), history of severe psychiatric disorder (e.g...data analysis. 15. SUBJECT TERMS Blast-related traumatic brain injury (TBI), fMRI, DTI, cognition 16. SECURITY CLASSIFICATION OF: 17. LIMITATION...neuropsychologic test for learning and other cerebral disorders. Journal of Learning Disorders 3, 83-91. 36. (1944). Army Individual Test of General

  3. Evidence of central and peripheral vestibular pathology in blast-related traumatic brain injury.

    Science.gov (United States)

    Scherer, Matthew R; Burrows, Holly; Pinto, Robin; Littlefield, Philip; French, Louis M; Tarbett, Aaron K; Schubert, Michael C

    2011-06-01

    To prospectively assay the vestibular and oculomotor systems of blast-exposed service members with traumatic brain injury (TBI). Prospective, nonblinded, nonrandomized descriptive study. Tertiary care facility (Department of Defense Medical Center). Twenty-four service members recovering from blast-related TBI sustained in Iraq or Afghanistan. Focused history and physical, videonystagmography (VNG), rotational chair, cervical vestibular-evoked myogenic potentials, computerized dynamic posturography, and self-report measures. Vestibular testing confirms a greater incidence of vestibular and oculomotor dysfunction in symptomatic (vestibular-like dizziness) personnel with blast-related TBI relative to asymptomatic group members. VNG in the symptomatic group revealed abnormal nystagmus or oculomotor findings in 6 of 12 subjects tested. Similarly, rotational chair testing in this group revealed evidence of both peripheral (4/12) and central (2/12) vestibular pathology. By contrast, the asymptomatic group revealed less vestibular impairment with 1 of 10 rotational chair abnormalities. The asymptomatic group was further characterized by fewer aberrant nystagmus findings (4/12 abnormal VNGs). Computerized dynamic posturography testing revealed no significant differences between groups. Self-report measures demonstrated differences between groups. Vestibular function testing confirms a greater incidence of peripheral vestibular hypofunction in dizzy service members with blast-related TBI relative to those who are asymptomatic. Additionally, oculomotor abnormalities and/or nystagmus consistent with central involvement were present in 10 of the 24 study participants tested. The precise cause of these findings remains unknown.

  4. Viscoelastic Materials Study for the Mitigation of Blast-Related Brain Injury

    Science.gov (United States)

    Bartyczak, Susan; Mock, Willis, Jr.

    2011-06-01

    Recent preliminary research into the causes of blast-related brain injury indicates that exposure to blast pressures, such as from IED detonation or multiple firings of a weapon, causes damage to brain tissue resulting in Traumatic Brain Injury (TBI) and Post Traumatic Stress Disorder (PTSD). Current combat helmets are not sufficient to protect the warfighter from this danger and the effects are debilitating, costly, and long-lasting. Commercially available viscoelastic materials, designed to dampen vibration caused by shock waves, might be useful as helmet liners to dampen blast waves. The objective of this research is to develop an experimental technique to test these commercially available materials when subject to blast waves and evaluate their blast mitigating behavior. A 40-mm-bore gas gun is being used as a shock tube to generate blast waves (ranging from 1 to 500 psi) in a test fixture at the gun muzzle. A fast opening valve is used to release nitrogen gas from the breech to impact instrumented targets. The targets consist of aluminum/ viscoelastic polymer/ aluminum materials. Blast attenuation is determined through the measurement of pressure and accelerometer data in front of and behind the target. The experimental technique, calibration and checkout procedures, and results will be presented.

  5. High prevalence of chronic pituitary and target-organ hormone abnormalities after blast-related mild traumatic brain injury

    Directory of Open Access Journals (Sweden)

    Charles W. Wilkinson

    2012-02-01

    Full Text Available Studies of traumatic brain injury from all causes have found evidence of chronic hypopituitarism, defined by deficient production of one or more pituitary hormones at least one year after injury, in 25-50% of cases. Most studies found the occurrence of posttraumatic hypopituitarism (PTHP to be unrelated to injury severity. Growth hormone deficiency (GHD and hypogonadism were reported most frequently. Hypopituitarism, and in particular adult GHD, is associated with symptoms that resemble those of PTSD, including fatigue, anxiety, depression, irritability, insomnia, sexual dysfunction, cognitive deficiencies, and decreased quality of life. However, the prevalence of PTHP after blast-related mild TBI (mTBI, an extremely common injury in modern military operations, has not been characterized. We measured concentrations of 12 pituitary and target-organ hormones in two groups of male US Veterans of combat in Iraq or Afghanistan. One group consisted of participants with blast-related mTBI whose last blast exposure was at least one year prior to the study. The other consisted of Veterans with similar military deployment histories but without blast exposure. Eleven of 26, or 42% of participants with blast concussions were found to have abnormal hormone levels in one or more pituitary axes, a prevalence similar to that found in other forms of TBI. Five members of the mTBI group were found with markedly low age-adjusted insulin-like growth factor-I (IGF-I levels indicative of probable GHD, and three had testosterone and gonadotropin concentrations consistent with hypogonadism. If symptoms characteristic of both PTHP and PTSD can be linked to pituitary dysfunction, they may be amenable to treatment with hormone replacement. Routine screening for chronic hypopituitarism after blast concussion shows promise for appropriately directing diagnostic and therapeutic decisions that otherwise may remain unconsidered and for markedly facilitating recovery and

  6. Assessing Neuro-Systemic & Behavioral Components in the Pathophysiology of Blast-Related Brain Injury

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    Firas H Kobeissy

    2013-11-01

    Full Text Available Among the U.S. military personnel, blast injury is among the leading causes of brain injury. During the past decade, it has become apparent that even blast injury as a form of mild traumatic brain injury (mTBI may lead to multiple different adverse outcomes, such as neuropsychiatric symptoms and long-term cognitive disability. Blast injury is characterized by blast overpressure (BOP, blast duration, and blast impulse. While the blast injuries of a victim close to the explosion will be severe, majority of victims are usually at a distance leading to milder form described as mild blast TBI (mbTBI. A major feature of mbTBI is its complex manifestation occurring in concert at different organ levels involving systemic, cerebral, neuronal and neuropsychiatric responses; some of which are shared with other forms of brain trauma such as acute brain injury and other neuropsychiatric disorders such as PTSD. The pathophysiology of blast injury exposure involves complex cascades of chronic psychological stress, autonomic dysfunction and neuro/systemic inflammation. These factors render blast injury as an arduous challenge in terms of diagnosis and treatment as well as identification of sensitive and specific biomarkers distinguishing mTBI from other non-TBI pathologies and from neuropsychiatric disorders with similar symptoms. This is due to the distinct but shared and partially identified biochemical pathways and neuro-histopathological changes that might be linked to behavioral deficits observed. Taken together, this article aims to provide an overview of the current status of the cellular and pathological mechanisms involved in blast overpressure injury and argues for the urgent need to identify potential biomarkers that can hint at the different mechanisms involved.

  7. Disruption of caudate working memory activation in chronic blast-related traumatic brain injury

    Directory of Open Access Journals (Sweden)

    Mary R. Newsome

    2015-01-01

    Full Text Available Mild to moderate traumatic brain injury (TBI due to blast exposure is frequently diagnosed in veterans returning from the wars in Iraq and Afghanistan. However, it is unclear whether neural damage resulting from blast TBI differs from that found in TBI due to blunt-force trauma (e.g., falls and motor vehicle crashes. Little is also known about the effects of blast TBI on neural networks, particularly over the long term. Because impairment in working memory has been linked to blunt-force TBI, the present functional magnetic resonance imaging (fMRI study sought to investigate whether brain activation in response to a working memory task would discriminate blunt-force from blast TBI. Twenty-five veterans (mean age = 29.8 years, standard deviation = 6.01 years, 1 female who incurred TBI due to blast an average of 4.2 years prior to enrollment and 25 civilians (mean age = 27.4 years, standard deviation = 6.68 years, 4 females with TBI due to blunt-force trauma performed the Sternberg Item Recognition Task while undergoing fMRI. The task involved encoding 1, 3, or 5 items in working memory. A group of 25 veterans (mean age = 29.9 years, standard deviation = 5.53 years, 0 females and a group of 25 civilians (mean age = 27.3 years, standard deviation = 5.81 years, 0 females without history of TBI underwent identical imaging procedures and served as controls. Results indicated that the civilian TBI group and both control groups demonstrated a monotonic relationship between working memory set size and activation in the right caudate during encoding, whereas the blast TBI group did not (p < 0.05, corrected for multiple comparisons using False Discovery Rate. Blast TBI was also associated with worse performance on the Sternberg Item Recognition Task relative to the other groups, although no other group differences were found on neuropsychological measures of episodic memory, inhibition, and general processing speed. These results

  8. Blast-related mild traumatic brain injury: a Bayesian random-effects meta-analysis on the cognitive outcomes of concussion among military personnel.

    Science.gov (United States)

    Karr, Justin E; Areshenkoff, Corson N; Duggan, Emily C; Garcia-Barrera, Mauricio A

    2014-12-01

    Throughout their careers, many soldiers experience repeated blasts exposures from improvised explosive devices, which often involve head injury. Consequentially, blast-related mild Traumatic Brain Injury (mTBI) has become prevalent in modern conflicts, often occuring co-morbidly with psychiatric illness (e.g., post-traumatic stress disorder [PTSD]). In turn, a growing body of research has begun to explore the cognitive and psychiatric sequelae of blast-related mTBI. The current meta-analysis aimed to evaluate the chronic effects of blast-related mTBI on cognitive performance. A systematic review identified 9 studies reporting 12 samples meeting eligibility criteria. A Bayesian random-effects meta-analysis was conducted with cognitive construct and PTSD symptoms explored as moderators. The overall posterior mean effect size and Highest Density Interval (HDI) came to d = -0.12 [-0.21, -0.04], with executive function (-0.16 [-0.31, 0.00]), verbal delayed memory (-0.19 [-0.44, 0.06]) and processing speed (-0.11 [-0.26, 0.01]) presenting as the most sensitive cognitive domains to blast-related mTBI. When dividing executive function into diverse sub-constructs (i.e., working memory, inhibition, set-shifting), set-shifting presented the largest effect size (-0.33 [-0.55, -0.05]). PTSD symptoms did not predict cognitive effects sizes, β PTSD  = -0.02 [-0.23, 0.20]. The results indicate a subtle, but chronic cognitive impairment following mTBI, especially in set-shifting, a relevant aspect of executive attention. These findings are consistent with past meta-analyses on multiple mTBI and correspond with past neuroimaging research on the cognitive correlates of white matter damage common in mTBI. However, all studies had cross-sectional designs, which resulted in universally low quality ratings and limited the conclusions inferable from this meta-analysis.

  9. Development of an Anatomically Accurate Finite Element Human Ocular Globe Model for Blast-Related Fluid-Structure Interaction Studies

    Science.gov (United States)

    2017-02-01

    primary blast wave loading on the eye. Watson et al.16 evaluated primary blast wave insult through a combined experimental-computational approach...analysis model of orbital biomechanics. Vision Res. 2006;46(11):1724–1731. 16. Watson R, Gray W, Sponsel WE, Lund BJ, Glickman RD, Groth SL, Reilly MA...ISRN Ophthalmology; 2011. Article ID No.: 146813. doi:10.5402/2011/146813. 39. Roberts KF, Artes PH, OLeary N, Reis AS, Sharpe GP, Hutchison DM

  10. Prevention of Blast-Related Injuries

    Science.gov (United States)

    2017-09-01

    Award Number: W81XWH-12-2-0038 TITLE: Prevention of Blast-Related Injuries PRINCIPAL INVESTIGATOR: Albert I. King CONTRACTING ORGANIZATION...CONTRACT NUMBER Prevention of Blast-Related Injuries 5b. GRANT NUMBER W81XWH-12-2-0038 5c. PROGRAM ELEMENT NUMBER 6. AUTHOR(S) Albert King, John...TR-7340). Army research lab Aberdeen proving ground MD weapons and materials research directorate. (2015) 11. Reneer, D.V., Hisel, R.D., Hoffman

  11. Civilian blast-related burn injuries.

    Science.gov (United States)

    Patel, J N; Tan, A; Dziewulski, P

    2016-03-31

    There is limited English literature describing the experience of a civilian hospital managing blast-related burn injuries. As the largest regional burn unit, we reviewed our cases with the aim of identifying means to improve current management. A 6-year retrospective analysis of all patients coded as sustaining blast-related burns was conducted through the unit's burns database. Medical case notes were reviewed for information on burn demographics, management and outcomes. 42 patients were identified. Male to female ratio was 37:5. Age range was 12-84 years, (mean=33 years). Total body surface area (%TBSA) burn ranged from 0.25% to 60%, (median=1%). The most common burn injury was flame (31/42, 73.8%). Gas explosions were the most common mechanism of injury (19 cases; 45.2%). 7/42 cases (16.7%) had full ATLS management pre-transfer to the burns unit. The Injury Severity Score (ISS) ranged from 0-43 (median=2). 17/42 (40.4%) patients required admission. 37/36 (88.1%) patients were managed conservatively of which 1 patient later required surgery due to deeper burns. 5/42 (11.9%) patients required surgical management at presentation and these were noted to be burns with >15% TBSA requiring resuscitation. One case required emergency escharotomies and finger amputations. All patients survived their burn injuries. Blast-related burn injuries are generally uncommon in the civilian setting. Following proper assessment, most of these cases can be deemed as minor injuries and managed conservatively. Improvement in burns management education and training at local emergency departments would provide efficient patient care and avoid unnecessary referrals to a burns unit.

  12. Brain Network Modelling

    DEFF Research Database (Denmark)

    Andersen, Kasper Winther

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

  13. Modeling Structural Brain Connectivity

    DEFF Research Database (Denmark)

    Ambrosen, Karen Marie Sandø

    The human brain consists of a gigantic complex network of interconnected neurons. Together all these connections determine who we are, how we react and how we interpret the world. Knowledge about how the brain is connected can further our understanding of the brain’s structural organization, help...... improve diagnosis, and potentially allow better treatment of a wide range of neurological disorders. Tractography based on diffusion magnetic resonance imaging is a unique tool to estimate this “structural connectivity” of the brain non-invasively and in vivo. During the last decade, brain connectivity...... has increasingly been analyzed using graph theoretic measures adopted from network science and this characterization of the brain’s structural connectivity has been shown to be useful for the classification of populations, such as healthy and diseased subjects. The structural connectivity of the brain...

  14. Retrospective and Prospective Memory Among OEF/OIF/OND Veterans With a Self-Reported History of Blast-Related mTBI.

    Science.gov (United States)

    Pagulayan, Kathleen F; Rau, Holly; Madathil, Renee; Werhane, Madeleine; Millard, Steven P; Petrie, Eric C; Parmenter, Brett; Peterson, Sarah; Sorg, Scott; Hendrickson, Rebecca; Mayer, Cindy; Meabon, James S; Huber, Bertrand R; Raskind, Murray; Cook, David G; Peskind, Elaine R

    2018-04-01

    To evaluate prospective and retrospective memory abilities in Operation Enduring Freedom (OEF), Operation Iraqi Freedom (OIF), and Operation New Dawn (OND) Veterans with and without a self-reported history of blast-related mild traumatic brain injury (mTBI). Sixty-one OEF/OIF/OND Veterans, including Veterans with a self-reported history of blast-related mTBI (mTBI group; n=42) and Veterans without a self-reported history of TBI (control group; n=19) completed the Memory for Intentions Test, a measure of prospective memory (PM), and two measures of retrospective memory (RM), the California Verbal Learning Test-II and the Brief Visuospatial Memory Test-Revised. Veterans in the mTBI group exhibited significantly lower PM performance than the control group, but the groups did not differ in their performance on RM measures. Further analysis revealed that Veterans in the mTBI group with current PTSD (mTBI/PTSD+) demonstrated significantly lower performance on the PM measure than Veterans in the control group. PM performance by Veterans in the mTBI group without current PTSD (mTBI/PTSD-) was intermediate between the mTBI/PTSD+ and control groups, and results for the mTBI/PTSD- group were not significantly different from either of the other two groups. Results suggest that PM performance may be a sensitive marker of cognitive dysfunction among OEF/OIF/OND Veterans with a history of self-reported blast-related mTBI and comorbid PTSD. Reduced PM may account, in part, for complaints of cognitive difficulties in this Veteran cohort, even years post-injury. (JINS, 2018, 24, 324-334).

  15. Exposure to a predator scent induces chronic behavioral changes in rats previously exposed to low-level blast: Implications for the relationship of blast-related TBI to PTSD

    Directory of Open Access Journals (Sweden)

    Georgina Perez-Garcia

    2016-10-01

    Full Text Available Blast-related mild traumatic brain injury (mTBI has been unfortunately common in veterans who served in the recent conflicts in Iraq and Afghanistan. The postconcussion syndrome associated with these mTBIs has frequently appeared in combination with post-traumatic stress disorder (PTSD. The presence of PTSD has complicated diagnosis since clinically PTSD and the postconcussion syndrome of mTBI have many overlapping symptoms. In particular establishing how much of the symptom complex can be attributed to the psychological trauma associated with PTSD in contrast to the physical injury of TBI has proven difficult. Indeed some have suggested that much of what is now being called blast-related postconcussion syndrome is better explained by PTSD. The relationship between the postconcussion syndrome of mTBI and PTSD is complex. Association of the two disorders might be viewed as additive effects of independent psychological and physical traumas suffered in a war zone. However we previously found that rats exposed to repetitive low-level blast exposure in the absence of a psychological stressor developed a variety of anxiety and PTSD-related behavioral traits that were present months following the last blast exposure. Here we show that a single predator scent challenge delivered 8 months after the last blast exposure induces chronic anxiety related changes in blast-exposed rats that are still present 45 days later. These observations suggest that in addition to independently inducing PTSD-related traits, blast exposure sensitizes the brain to react abnormally to a subsequent psychological stressor. These studies have implications for conceptualizing the relationship between blast-related mTBI and PTSD and suggest that blast-related mTBI in humans may predispose to the later development of PTSD in reaction to subsequent psychological stressors.

  16. Modeling Pediatric Brain Trauma: Piglet Model of Controlled Cortical Impact.

    Science.gov (United States)

    Pareja, Jennifer C Munoz; Keeley, Kristen; Duhaime, Ann-Christine; Dodge, Carter P

    2016-01-01

    The brain has different responses to traumatic injury as a function of its developmental stage. As a model of injury to the immature brain, the piglet shares numerous similarities in regards to morphology and neurodevelopmental sequence compared to humans. This chapter describes a piglet scaled focal contusion model of traumatic brain injury that accounts for the changes in mass and morphology of the brain as it matures, facilitating the study of age-dependent differences in response to a comparable mechanical trauma.

  17. Computational Intelligence in a Human Brain Model

    Directory of Open Access Journals (Sweden)

    Viorel Gaftea

    2016-06-01

    Full Text Available This paper focuses on the current trends in brain research domain and the current stage of development of research for software and hardware solutions, communication capabilities between: human beings and machines, new technologies, nano-science and Internet of Things (IoT devices. The proposed model for Human Brain assumes main similitude between human intelligence and the chess game thinking process. Tactical & strategic reasoning and the need to follow the rules of the chess game, all are very similar with the activities of the human brain. The main objective for a living being and the chess game player are the same: securing a position, surviving and eliminating the adversaries. The brain resolves these goals, and more, the being movement, actions and speech are sustained by the vital five senses and equilibrium. The chess game strategy helps us understand the human brain better and easier replicate in the proposed ‘Software and Hardware’ SAH Model.

  18. Bayesian Modelling of Functional Whole Brain Connectivity

    DEFF Research Database (Denmark)

    Røge, Rasmus

    This thesis deals with parcellation of whole-brain functional magnetic resonance imaging (fMRI) using Bayesian inference with mixture models tailored to the fMRI data. In the three included papers and manuscripts, we analyze two different approaches to modeling fMRI signal; either we accept...... the prevalent strategy of standardizing of fMRI time series and model data using directional statistics or we model the variability in the signal across the brain and across multiple subjects. In either case, we use Bayesian nonparametric modeling to automatically learn from the fMRI data the number...... of funcional units, i.e. parcels. We benchmark the proposed mixture models against state of the art methods of brain parcellation, both probabilistic and non-probabilistic. The time series of each voxel are most often standardized using z-scoring which projects the time series data onto a hypersphere...

  19. Melanoma Brain Metastasis: Mechanisms, Models, and Medicine

    Science.gov (United States)

    Kircher, David A.; Silvis, Mark R.; Cho, Joseph H.; Holmen, Sheri L.

    2016-01-01

    The development of brain metastases in patients with advanced stage melanoma is common, but the molecular mechanisms responsible for their development are poorly understood. Melanoma brain metastases cause significant morbidity and mortality and confer a poor prognosis; traditional therapies including whole brain radiation, stereotactic radiotherapy, or chemotherapy yield only modest increases in overall survival (OS) for these patients. While recently approved therapies have significantly improved OS in melanoma patients, only a small number of studies have investigated their efficacy in patients with brain metastases. Preliminary data suggest that some responses have been observed in intracranial lesions, which has sparked new clinical trials designed to evaluate the efficacy in melanoma patients with brain metastases. Simultaneously, recent advances in our understanding of the mechanisms of melanoma cell dissemination to the brain have revealed novel and potentially therapeutic targets. In this review, we provide an overview of newly discovered mechanisms of melanoma spread to the brain, discuss preclinical models that are being used to further our understanding of this deadly disease and provide an update of the current clinical trials for melanoma patients with brain metastases. PMID:27598148

  20. D-galactose-induced brain ageing model

    DEFF Research Database (Denmark)

    Sadigh-Eteghad, Saeed; Majdi, Alireza; McCann, Sarah K.

    2017-01-01

    Animal models are commonly used in brain ageing research. Amongst these, models where rodents are exposed to d-galactose are held to recapitulate a number of features of ageing including neurobehavioral and neurochemical changes. However, results from animal studies are often inconsistent...

  1. Multivariate Heteroscedasticity Models for Functional Brain Connectivity

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    Christof Seiler

    2017-12-01

    Full Text Available Functional brain connectivity is the co-occurrence of brain activity in different areas during resting and while doing tasks. The data of interest are multivariate timeseries measured simultaneously across brain parcels using resting-state fMRI (rfMRI. We analyze functional connectivity using two heteroscedasticity models. Our first model is low-dimensional and scales linearly in the number of brain parcels. Our second model scales quadratically. We apply both models to data from the Human Connectome Project (HCP comparing connectivity between short and conventional sleepers. We find stronger functional connectivity in short than conventional sleepers in brain areas consistent with previous findings. This might be due to subjects falling asleep in the scanner. Consequently, we recommend the inclusion of average sleep duration as a covariate to remove unwanted variation in rfMRI studies. A power analysis using the HCP data shows that a sample size of 40 detects 50% of the connectivity at a false discovery rate of 20%. We provide implementations using R and the probabilistic programming language Stan.

  2. Modeling high dimensional multichannel brain signals

    KAUST Repository

    Hu, Lechuan

    2017-03-27

    In this paper, our goal is to model functional and effective (directional) connectivity in network of multichannel brain physiological signals (e.g., electroencephalograms, local field potentials). The primary challenges here are twofold: first, there are major statistical and computational difficulties for modeling and analyzing high dimensional multichannel brain signals; second, there is no set of universally-agreed measures for characterizing connectivity. To model multichannel brain signals, our approach is to fit a vector autoregressive (VAR) model with sufficiently high order so that complex lead-lag temporal dynamics between the channels can be accurately characterized. However, such a model contains a large number of parameters. Thus, we will estimate the high dimensional VAR parameter space by our proposed hybrid LASSLE method (LASSO+LSE) which is imposes regularization on the first step (to control for sparsity) and constrained least squares estimation on the second step (to improve bias and mean-squared error of the estimator). Then to characterize connectivity between channels in a brain network, we will use various measures but put an emphasis on partial directed coherence (PDC) in order to capture directional connectivity between channels. PDC is a directed frequency-specific measure that explains the extent to which the present oscillatory activity in a sender channel influences the future oscillatory activity in a specific receiver channel relative all possible receivers in the network. Using the proposed modeling approach, we have achieved some insights on learning in a rat engaged in a non-spatial memory task.

  3. Mathematical Model of Evolution of Brain Parcellation.

    Science.gov (United States)

    Ferrante, Daniel D; Wei, Yi; Koulakov, Alexei A

    2016-01-01

    We study the distribution of brain and cortical area sizes [parcellation units (PUs)] obtained for three species: mouse, macaque, and human. We find that the distribution of PU sizes is close to lognormal. We propose the mathematical model of evolution of brain parcellation based on iterative fragmentation and specialization. In this model, each existing PU has a probability to be split that depends on PU size only. This model suggests that the same evolutionary process may have led to brain parcellation in these three species. Within our model, region-to-region (macro) connectivity is given by the outer product form. We show that most experimental data on non-zero macaque cortex macroscopic-level connections can be explained by the outer product power-law form suggested by our model (62% for area V1). We propose a multiplicative Hebbian learning rule for the macroconnectome that could yield the correct scaling of connection strengths between areas. We thus propose an evolutionary model that may have contributed to both brain parcellation and mesoscopic level connectivity in mammals.

  4. Modeling High-Dimensional Multichannel Brain Signals

    KAUST Repository

    Hu, Lechuan

    2017-12-12

    Our goal is to model and measure functional and effective (directional) connectivity in multichannel brain physiological signals (e.g., electroencephalograms, local field potentials). The difficulties from analyzing these data mainly come from two aspects: first, there are major statistical and computational challenges for modeling and analyzing high-dimensional multichannel brain signals; second, there is no set of universally agreed measures for characterizing connectivity. To model multichannel brain signals, our approach is to fit a vector autoregressive (VAR) model with potentially high lag order so that complex lead-lag temporal dynamics between the channels can be captured. Estimates of the VAR model will be obtained by our proposed hybrid LASSLE (LASSO + LSE) method which combines regularization (to control for sparsity) and least squares estimation (to improve bias and mean-squared error). Then we employ some measures of connectivity but put an emphasis on partial directed coherence (PDC) which can capture the directional connectivity between channels. PDC is a frequency-specific measure that explains the extent to which the present oscillatory activity in a sender channel influences the future oscillatory activity in a specific receiver channel relative to all possible receivers in the network. The proposed modeling approach provided key insights into potential functional relationships among simultaneously recorded sites during performance of a complex memory task. Specifically, this novel method was successful in quantifying patterns of effective connectivity across electrode locations, and in capturing how these patterns varied across trial epochs and trial types.

  5. Brain-inspired Stochastic Models and Implementations

    KAUST Repository

    Al-Shedivat, Maruan

    2015-05-12

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

  6. Modelling Brain Tissue using Magnetic Resonance Imaging

    DEFF Research Database (Denmark)

    Dyrby, Tim Bjørn

    2008-01-01

    Diffusion MRI, or diffusion weighted imaging (DWI), is a technique that measures the restricted diffusion of water molecules within brain tissue. Different reconstruction methods quantify water-diffusion anisotropy in the intra- and extra-cellular spaces of the neural environment. Fibre tracking...... in the first time period of the scanning session. Probabilistic tractography was validated against two invasive in vivo neuronal tracers that were used to derive a gold standard. A high spatial agreement between tractography and the gold standard was found, and some of the widely known limitations...... experiment. This includes the selection of independent anatomical data to be used to derive a gold standard, the selection of a gyrated animal model in place of the human brain, objective selection of the seed region to initiate, and a waypoint region to constrain the tractography results....

  7. On a Quantum Model of Brain Activities

    Science.gov (United States)

    Fichtner, K.-H.; Fichtner, L.; Freudenberg, W.; Ohya, M.

    2010-01-01

    One of the main activities of the brain is the recognition of signals. A first attempt to explain the process of recognition in terms of quantum statistics was given in [6]. Subsequently, details of the mathematical model were presented in a (still incomplete) series of papers (cf. [7, 2, 5, 10]). In the present note we want to give a general view of the principal ideas of this approach. We will introduce the basic spaces and justify the choice of spaces and operations. Further, we bring the model face to face with basic postulates any statistical model of the recognition process should fulfill. These postulates are in accordance with the opinion widely accepted in psychology and neurology.

  8. A Culture-Behavior-Brain Loop Model of Human Development.

    Science.gov (United States)

    Han, Shihui; Ma, Yina

    2015-11-01

    Increasing evidence suggests that cultural influences on brain activity are associated with multiple cognitive and affective processes. These findings prompt an integrative framework to account for dynamic interactions between culture, behavior, and the brain. We put forward a culture-behavior-brain (CBB) loop model of human development that proposes that culture shapes the brain by contextualizing behavior, and the brain fits and modifies culture via behavioral influences. Genes provide a fundamental basis for, and interact with, the CBB loop at both individual and population levels. The CBB loop model advances our understanding of the dynamic relationships between culture, behavior, and the brain, which are crucial for human phylogeny and ontogeny. Future brain changes due to cultural influences are discussed based on the CBB loop model. Copyright © 2015 Elsevier Ltd. All rights reserved.

  9. Modeling brain resonance phenomena using a neural mass model.

    Directory of Open Access Journals (Sweden)

    Andreas Spiegler

    2011-12-01

    Full Text Available Stimulation with rhythmic light flicker (photic driving plays an important role in the diagnosis of schizophrenia, mood disorder, migraine, and epilepsy. In particular, the adjustment of spontaneous brain rhythms to the stimulus frequency (entrainment is used to assess the functional flexibility of the brain. We aim to gain deeper understanding of the mechanisms underlying this technique and to predict the effects of stimulus frequency and intensity. For this purpose, a modified Jansen and Rit neural mass model (NMM of a cortical circuit is used. This mean field model has been designed to strike a balance between mathematical simplicity and biological plausibility. We reproduced the entrainment phenomenon observed in EEG during a photic driving experiment. More generally, we demonstrate that such a single area model can already yield very complex dynamics, including chaos, for biologically plausible parameter ranges. We chart the entire parameter space by means of characteristic Lyapunov spectra and Kaplan-Yorke dimension as well as time series and power spectra. Rhythmic and chaotic brain states were found virtually next to each other, such that small parameter changes can give rise to switching from one to another. Strikingly, this characteristic pattern of unpredictability generated by the model was matched to the experimental data with reasonable accuracy. These findings confirm that the NMM is a useful model of brain dynamics during photic driving. In this context, it can be used to study the mechanisms of, for example, perception and epileptic seizure generation. In particular, it enabled us to make predictions regarding the stimulus amplitude in further experiments for improving the entrainment effect.

  10. Bayesian Joint Modeling of Multiple Brain Functional Networks

    OpenAIRE

    Lukemire, Joshua; Kundu, Suprateek; Pagnoni, Giuseppe; Guo, Ying

    2017-01-01

    Brain function is organized in coordinated modes of spatio-temporal activity (functional networks) exhibiting an intrinsic baseline structure with variations under different experimental conditions. Existing approaches for uncovering such network structures typically do not explicitly model shared and differential patterns across networks, thus potentially reducing the detection power. We develop an integrative modeling approach for jointly modeling multiple brain networks across experimental...

  11. Brain repair after stroke--a novel neurological model.

    Science.gov (United States)

    Small, Steven L; Buccino, Giovanni; Solodkin, Ana

    2013-12-01

    Following stroke, patients are commonly left with debilitating motor and speech impairments. This article reviews the state of the art in neurological repair for stroke and proposes a new model for the future. We suggest that stroke treatment--from the time of the ictus itself to living with the consequences--must be fundamentally neurological, from limiting the extent of injury at the outset, to repairing the consequent damage. Our model links brain and behaviour by targeting brain circuits, and we illustrate the model though action observation treatment, which aims to enhance brain network connectivity. The model is based on the assumptions that the mechanisms of neural repair inherently involve cellular and circuit plasticity, that brain plasticity is a synaptic phenomenon that is largely stimulus-dependent, and that brain repair required both physical and behavioural interventions that are tailored to reorganize specific brain circuits. We review current approaches to brain repair after stroke and present our new model, and discuss the biological foundations, rationales, and data to support our novel approach to upper-extremity and language rehabilitation. We believe that by enhancing plasticity at the level of brain network interactions, this neurological model for brain repair could ultimately lead to a cure for stroke.

  12. Brain repair after stroke—a novel neurological model

    Science.gov (United States)

    Small, Steven L.; Buccino, Giovanni; Solodkin, Ana

    2017-01-01

    Following stroke, patients are commonly left with debilitating motor and speech impairments. This article reviews the state of the art in neurological repair for stroke and proposes a new model for the future. We suggest that stroke treatment—from the time of the ictus itself to living with the consequences—must be fundamentally neurological, from limiting the extent of injury at the outset, to repairing the consequent damage. Our model links brain and behaviour by targeting brain circuits, and we illustrate the model though action observation treatment, which aims to enhance brain network connectivity. The model is based on the assumptions that the mechanisms of neural repair inherently involve cellular and circuit plasticity, that brain plasticity is a synaptic phenomenon that is largely stimulus-dependent, and that brain repair required both physical and behavioural interventions that are tailored to reorganize specific brain circuits. We review current approaches to brain repair after stroke and present our new model, and discuss the biological foundations, rationales, and data to support our novel approach to upper-extremity and language rehabilitation. We believe that by enhancing plasticity at the level of brain network interactions, this neurological model for brain repair could ultimately lead to a cure for stroke. PMID:24217509

  13. On a Mathematical Model of Brain Activities

    International Nuclear Information System (INIS)

    Fichtner, K.-H.; Fichtner, L.; Freudenberg, W.; Ohya, M.

    2007-01-01

    The procedure of recognition can be described as follows: There is a set of complex signals stored in the memory. Choosing one of these signals may be interpreted as generating a hypothesis concerning an 'expexted view of the world'. Then the brain compares a signal arising from our senses with the signal chosen from the memory leading to a change of the state of both signals. Furthermore, measurements of that procedure like EEG or MEG are based on the fact that recognition of signals causes a certain loss of excited neurons, i.e. the neurons change their state from 'excited' to 'nonexcited'. For that reason a statistical model of the recognition process should reflect both--the change of the signals and the loss of excited neurons. A first attempt to explain the process of recognition in terms of quantum statistics was given. In the present note it is not possible to present this approach in detail. In lieu we will sketch roughly a few of the basic ideas and structures of the proposed model of the recognition process (Section). Further, we introduce the basic spaces and justify the choice of spaces used in this approach. A more elaborate presentation including all proofs will be given in a series of some forthcoming papers. In this series also the procedures of creation of signals from the memory, amplification, accumulation and transformation of input signals, and measurements like EEG and MEG will be treated in detail

  14. Individual brain structure and modelling predict seizure propagation.

    Science.gov (United States)

    Proix, Timothée; Bartolomei, Fabrice; Guye, Maxime; Jirsa, Viktor K

    2017-03-01

    See Lytton (doi:10.1093/awx018) for a scientific commentary on this article.Neural network oscillations are a fundamental mechanism for cognition, perception and consciousness. Consequently, perturbations of network activity play an important role in the pathophysiology of brain disorders. When structural information from non-invasive brain imaging is merged with mathematical modelling, then generative brain network models constitute personalized in silico platforms for the exploration of causal mechanisms of brain function and clinical hypothesis testing. We here demonstrate with the example of drug-resistant epilepsy that patient-specific virtual brain models derived from diffusion magnetic resonance imaging have sufficient predictive power to improve diagnosis and surgery outcome. In partial epilepsy, seizures originate in a local network, the so-called epileptogenic zone, before recruiting other close or distant brain regions. We create personalized large-scale brain networks for 15 patients and simulate the individual seizure propagation patterns. Model validation is performed against the presurgical stereotactic electroencephalography data and the standard-of-care clinical evaluation. We demonstrate that the individual brain models account for the patient seizure propagation patterns, explain the variability in postsurgical success, but do not reliably augment with the use of patient-specific connectivity. Our results show that connectome-based brain network models have the capacity to explain changes in the organization of brain activity as observed in some brain disorders, thus opening up avenues towards discovery of novel clinical interventions. © The Author (2017). Published by Oxford University Press on behalf of the Guarantors of Brain.

  15. Animal models of brain dysfunction in phenylketonuria

    NARCIS (Netherlands)

    Martynyuk, A. E.; van Spronsen, F. J.; Van der Zee, E. A.

    2010-01-01

    Phenylketonuria (PKU) is a metabolic disorder that results in significant brain dysfunction if untreated. Although phenylalanine restricted diets instituted at birth have clearly improved PKU outcomes, neuropsychological deficits and neurological changes still represent substantial problems. The

  16. Statistical Challenges in Modeling Big Brain Signals

    KAUST Repository

    Yu, Zhaoxia

    2017-11-01

    Brain signal data are inherently big: massive in amount, complex in structure, and high in dimensions. These characteristics impose great challenges for statistical inference and learning. Here we review several key challenges, discuss possible solutions, and highlight future research directions.

  17. CSF transthyretin neuroprotection in a mouse model of brain ischemia

    DEFF Research Database (Denmark)

    Santos, Sofia Duque; Lambertsen, Kate Lykke; Clausen, Bettina Hjelm

    2010-01-01

    Brain injury caused by ischemia is a major cause of human mortality and physical/cognitive disability worldwide. Experimentally, brain ischemia can be induced surgically by permanent middle cerebral artery occlusion. Using this model, we studied the influence of transthyretin in ischemic stroke. ...

  18. Reptiles: a new model for brain evo-devo research.

    Science.gov (United States)

    Nomura, Tadashi; Kawaguchi, Masahumi; Ono, Katsuhiko; Murakami, Yasunori

    2013-03-01

    Vertebrate brains exhibit vast amounts of anatomical diversity. In particular, the elaborate and complex nervous system of amniotes is correlated with the size of their behavioral repertoire. However, the evolutionary mechanisms underlying species-specific brain morphogenesis remain elusive. In this review we introduce reptiles as a new model organism for understanding brain evolution. These animal groups inherited ancestral traits of brain architectures. We will describe several unique aspects of the reptilian nervous system with a special focus on the telencephalon, and discuss the genetic mechanisms underlying reptile-specific brain morphology. The establishment of experimental evo-devo approaches to studying reptiles will help to shed light on the origin of the amniote brains. Copyright © 2013 Wiley Periodicals, Inc.

  19. Modeling the brain morphology distribution in the general aging population

    Science.gov (United States)

    Huizinga, W.; Poot, D. H. J.; Roshchupkin, G.; Bron, E. E.; Ikram, M. A.; Vernooij, M. W.; Rueckert, D.; Niessen, W. J.; Klein, S.

    2016-03-01

    Both normal aging and neurodegenerative diseases such as Alzheimer's disease cause morphological changes of the brain. To better distinguish between normal and abnormal cases, it is necessary to model changes in brain morphology owing to normal aging. To this end, we developed a method for analyzing and visualizing these changes for the entire brain morphology distribution in the general aging population. The method is applied to 1000 subjects from a large population imaging study in the elderly, from which 900 were used to train the model and 100 were used for testing. The results of the 100 test subjects show that the model generalizes to subjects outside the model population. Smooth percentile curves showing the brain morphology changes as a function of age and spatiotemporal atlases derived from the model population are publicly available via an interactive web application at agingbrain.bigr.nl.

  20. Fresh Frozen Plasma Modulates Brain Gene Expression in a Swine Model of Traumatic Brain Injury and Shock

    DEFF Research Database (Denmark)

    Sillesen, Martin; Bambakidis, Ted; Dekker, Simone E

    2017-01-01

    BACKGROUND: Resuscitation with fresh frozen plasma (FFP) decreases brain lesion size and swelling in a swine model of traumatic brain injury and hemorrhagic shock. We hypothesized that brain gene expression profiles after traumatic brain injury and hemorrhagic shock would be modulated by FFP resu...

  1. Controlling ferrofluid permeability across the blood-brain barrier model

    Science.gov (United States)

    Shi, Di; Sun, Linlin; Mi, Gujie; Sheikh, Lubna; Bhattacharya, Soumya; Nayar, Suprabha; Webster, Thomas J.

    2014-02-01

    In the present study, an in vitro blood-brain barrier model was developed using murine brain endothelioma cells (b.End3 cells). Confirmation of the blood-brain barrier model was completed by examining the permeability of FITC-Dextran at increasing exposure times up to 96 h in serum-free medium and comparing such values with values from the literature. After such confirmation, the permeability of five novel ferrofluid (FF) nanoparticle samples, GGB (ferrofluids synthesized using glycine, glutamic acid and BSA), GGC (glycine, glutamic acid and collagen), GGP (glycine, glutamic acid and PVA), BPC (BSA, PEG and collagen) and CPB (collagen, PVA and BSA), was determined using this blood-brain barrier model. All of the five FF samples were characterized by zeta potential to determine their charge as well as TEM and dynamic light scattering for determining their hydrodynamic diameter. Results showed that FF coated with collagen passed more easily through the blood-brain barrier than FF coated with glycine and glutamic acid based on an increase of 4.5% in permeability. Through such experiments, diverse magnetic nanomaterials (such as FF) were identified for: (1) MRI use since they were less permeable to penetrate the blood-brain barrier to avoid neural tissue toxicity (e.g. GGB) or (2) brain drug delivery since they were more permeable to the blood-brain barrier (e.g. CPB).

  2. Modeling of Brain Shift Phenomenon for Different Craniotomies and Solid Models

    Directory of Open Access Journals (Sweden)

    Alvaro Valencia

    2012-01-01

    Full Text Available This study investigates the effects of different solid models on predictions of brain shift for three craniotomies. We created a generic 3D brain model based on healthy human brain and modeled the brain parenchyma as single continuum and constrained by a practically rigid skull. We have used elastic model, hyperelastic 1st, 2nd, and 3rd Ogden models, and hyperelastic Mooney-Rivlin with 2- and 5-parameter models. A pressure on the brain surface at craniotomy region was applied to load the model. The models were solved with the finite elements package ANSYS. The predictions on stress and displacements were compared for three different craniotomies. The difference between the predictions of elastic solid model and a hyperelastic Ogden solid model of maximum brain displacement and maximum effective stress is relevant.

  3. New neurons for injured brains? The emergence of new genetic model organisms to study brain regeneration.

    Science.gov (United States)

    Fernández-Hernández, Ismael; Rhiner, Christa

    2015-09-01

    Neuronal circuits in the adult brain have long been viewed as static and stable. However, research in the past 20 years has shown that specialized regions of the adult brain, which harbor adult neural stem cells, continue to produce new neurons in a wide range of species. Brain plasticity is also observed after injury. Depending on the extent and permissive environment of neurogenic regions, different organisms show great variability in their capacity to replace lost neurons by endogenous neurogenesis. In Zebrafish and Drosophila, the formation of new neurons from progenitor cells in the adult brain was only discovered recently. Here, we compare properties of adult neural stem cells, their niches and regenerative responses from mammals to flies. Current models of brain injury have revealed that specific injury-induced genetic programs and comparison of neuronal fitness are implicated in brain repair. We highlight the potential of these recently implemented models of brain regeneration to identify novel regulators of stem cell activation and regenerative neurogenesis. Copyright © 2015 Elsevier Ltd. All rights reserved.

  4. Brain repair after stroke—a novel neurological model

    OpenAIRE

    Small, Steven L.; Buccino, Giovanni; Solodkin, Ana

    2013-01-01

    Following stroke, patients are commonly left with debilitating motor and speech impairments. This article reviews the state of the art in neurological repair for stroke and proposes a new model for the future. We suggest that stroke treatment—from the time of the ictus itself to living with the consequences—must be fundamentally neurological, from limiting the extent of injury at the outset, to repairing the consequent damage. Our model links brain and behaviour by targeting brain circuits, a...

  5. Monte Carlo and phantom study in the brain edema models

    Directory of Open Access Journals (Sweden)

    Yubing Liu

    2017-05-01

    Full Text Available Because the brain edema has a crucial impact on morbidity and mortality, it is important to develop a noninvasive method to monitor the process of the brain edema effectively. When the brain edema occurs, the optical properties of the brain will change. The goal of this study is to access the feasibility and reliability of using noninvasive near-infrared spectroscopy (NIRS monitoring method to measure the brain edema. Specifically, three models, including the water content changes in the cerebrospinal fluid (CSF, gray matter and white matter, were explored. Moreover, these models were numerically simulated by the Monte Carlo studies. Then, the phantom experiments were performed to investigate the light intensity which was measured at different detecting radius on the tissue surface. The results indicated that the light intensity correlated well with the conditions of the brain edema and the detecting radius. Briefly, at the detecting radius of 3.0cm and 4.0cm, the light intensity has a high response to the change of tissue parameters and optical properties. Thus, it is possible to monitor the brain edema noninvasively by NIRS method and the light intensity is a reliable and simple parameter to assess the brain edema.

  6. A Dirichlet process mixture model for brain MRI tissue classification.

    Science.gov (United States)

    Ferreira da Silva, Adelino R

    2007-04-01

    Accurate classification of magnetic resonance images according to tissue type or region of interest has become a critical requirement in diagnosis, treatment planning, and cognitive neuroscience. Several authors have shown that finite mixture models give excellent results in the automated segmentation of MR images of the human normal brain. However, performance and robustness of finite mixture models deteriorate when the models have to deal with a variety of anatomical structures. In this paper, we propose a nonparametric Bayesian model for tissue classification of MR images of the brain. The model, known as Dirichlet process mixture model, uses Dirichlet process priors to overcome the limitations of current parametric finite mixture models. To validate the accuracy and robustness of our method we present the results of experiments carried out on simulated MR brain scans, as well as on real MR image data. The results are compared with similar results from other well-known MRI segmentation methods.

  7. A Bayesian Model of Category-Specific Emotional Brain Responses

    Science.gov (United States)

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

    2015-01-01

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

  8. Development of a Model for Whole Brain Learning of Physiology

    Science.gov (United States)

    Eagleton, Saramarie; Muller, Anton

    2011-01-01

    In this report, a model was developed for whole brain learning based on Curry's onion model. Curry described the effect of personality traits as the inner layer of learning, information-processing styles as the middle layer of learning, and environmental and instructional preferences as the outer layer of learning. The model that was developed…

  9. A hierarchical model of the evolution of human brain specializations

    Science.gov (United States)

    Barrett, H. Clark

    2012-01-01

    The study of information-processing adaptations in the brain is controversial, in part because of disputes about the form such adaptations might take. Many psychologists assume that adaptations come in two kinds, specialized and general-purpose. Specialized mechanisms are typically thought of as innate, domain-specific, and isolated from other brain systems, whereas generalized mechanisms are developmentally plastic, domain-general, and interactive. However, if brain mechanisms evolve through processes of descent with modification, they are likely to be heterogeneous, rather than coming in just two kinds. They are likely to be hierarchically organized, with some design features widely shared across brain systems and others specific to particular processes. Also, they are likely to be largely developmentally plastic and interactive with other brain systems, rather than canalized and isolated. This article presents a hierarchical model of brain specialization, reviewing evidence for the model from evolutionary developmental biology, genetics, brain mapping, and comparative studies. Implications for the search for uniquely human traits are discussed, along with ways in which conventional views of modularity in psychology may need to be revised. PMID:22723350

  10. Novel brain model for training of deep microvascular anastomosis.

    Science.gov (United States)

    Ishikawa, Tatsuya; Yasui, Nobuyuki; Ono, Hidenori

    2010-01-01

    Models of the brain and skull were developed using a selective laser sintering method for training in the procedures of deep microvascular anastomosis. Model A has an artificial skull with two craniotomies, providing fronto-temporal-subtemporal and suboccipital windows. The brain in Model A is soft and elastic, and consists of the brainstem and a hemispheric part with a detailed surface. Rehearsals or training for anastomosis to the insular part of the middle cerebral artery, superior cerebellar artery, posterior cerebral artery, and posterior inferior cerebellar artery can be performed through the craniotomies. Model B has an artificial skull with a bifrontal craniotomy and an artificial brain consisting of the bilateral frontal lobes with an interhemispheric fissure and corpus callosum. Rehearsals or training for anastomosis of the callosal segment of the anterior cerebral artery can be practiced through this craniotomy. These realistic models will help to develop skills for deep vascular anastomosis, which remains a challenging neurosurgical procedure, even for experienced neurosurgeons.

  11. Model brain based learning (BBL and whole brain teaching (WBT in learning

    Directory of Open Access Journals (Sweden)

    Baiq Sri Handayani

    2017-08-01

    Full Text Available The learning process is a process of change in behavior as a form of the result of learning. The learning model is a crucial component of the success of the learning process. The learning model is growing fastly, and each model has different characteristics. Teachers are required to be able to understand each model to teach the students optimally by matching the materials and the learning model. The best of the learning model is the model that based on the brain system in learning that are the model of Brain Based Learning (BBL and the model of Whole Brain Teaching (WBT. The purposes of this article are to obtain information related to (1 the brain’s natural learning system, (2 analyze the characteristics of the model BBL and WBT based on theory, brain sections that play a role associated with syntax, similarities, and differences, (3 explain the distinctive characteristics of both models in comparison to other models. The results of this study are: (1 the brain’s natural learning system are: (a the nerves in each hemisphere do not work independently, (b doing more activities can connect more brain nerves, (c the right hemisphere controls the left side motoric sensor of the body, and vice versa; (2 the characteristics of BBL and WBT are: (a BBL is based on the brain’s structure and function, while the model WBT is based on the instructional approach, neurolinguistic, and body language, (b the parts of the brain that work in BBL are: cerebellum, cerebral cortex, frontal lobe, limbic system, and prefrontal cortex; whereas the parts that work WBT are: prefrontal cortex, visual cortex, motor cortex, limbic system, and amygdala, (c the similarities between them are that they both rely on the brain’s system and they both promote gesture in learning, whereas the differences are on the view of the purposes of gestures and the learning theory that they rely on. BBL relies on cognitive theory while WBT relies on social theory; (3 the typical

  12. Computational modeling of brain tumors: discrete, continuum or hybrid?

    Science.gov (United States)

    Wang, Zhihui; Deisboeck, Thomas S.

    In spite of all efforts, patients diagnosed with highly malignant brain tumors (gliomas), continue to face a grim prognosis. Achieving significant therapeutic advances will also require a more detailed quantitative understanding of the dynamic interactions among tumor cells, and between these cells and their biological microenvironment. Data-driven computational brain tumor models have the potential to provide experimental tumor biologists with such quantitative and cost-efficient tools to generate and test hypotheses on tumor progression, and to infer fundamental operating principles governing bidirectional signal propagation in multicellular cancer systems. This review highlights the modeling objectives of and challenges with developing such in silico brain tumor models by outlining two distinct computational approaches: discrete and continuum, each with representative examples. Future directions of this integrative computational neuro-oncology field, such as hybrid multiscale multiresolution modeling are discussed.

  13. Dynamic causal modelling of brain-behaviour relationships.

    Science.gov (United States)

    Rigoux, L; Daunizeau, J

    2015-08-15

    In this work, we expose a mathematical treatment of brain-behaviour relationships, which we coin behavioural Dynamic Causal Modelling or bDCM. This approach aims at decomposing the brain's transformation of stimuli into behavioural outcomes, in terms of the relative contribution of brain regions and their connections. In brief, bDCM places the brain at the interplay between stimulus and behaviour: behavioural outcomes arise from coordinated activity in (hidden) neural networks, whose dynamics are driven by experimental inputs. Estimating neural parameters that control network connectivity and plasticity effectively performs a neurobiologically-constrained approximation to the brain's input-outcome transform. In other words, neuroimaging data essentially serves to enforce the realism of bDCM's decomposition of input-output relationships. In addition, post-hoc artificial lesions analyses allow us to predict induced behavioural deficits and quantify the importance of network features for funnelling input-output relationships. This is important, because this enables one to bridge the gap with neuropsychological studies of brain-damaged patients. We demonstrate the face validity of the approach using Monte-Carlo simulations, and its predictive validity using empirical fMRI/behavioural data from an inhibitory control task. Lastly, we discuss promising applications of this work, including the assessment of functional degeneracy (in the healthy brain) and the prediction of functional recovery after lesions (in neurological patients). Copyright © 2015 Elsevier Inc. All rights reserved.

  14. Cognitive Models as Bridge between Brain and Behavior.

    Science.gov (United States)

    Love, Bradley C

    2016-04-01

    How can disparate neural and behavioral measures be integrated? Turner and colleagues propose joint modeling as a solution. Joint modeling mutually constrains the interpretation of brain and behavioral measures by exploiting their covariation structure. Simultaneous estimation allows for more accurate prediction than would be possible by considering these measures in isolation. Copyright © 2016 The Authors. Published by Elsevier Ltd.. All rights reserved.

  15. Regional mechanical properties of human brain tissue for computational models of traumatic brain injury.

    Science.gov (United States)

    Finan, John D; Sundaresh, Sowmya N; Elkin, Benjamin S; McKhann, Guy M; Morrison, Barclay

    2017-06-01

    To determine viscoelastic shear moduli, stress relaxation indentation tests were performed on samples of human brain tissue resected in the course of epilepsy surgery. Through the use of a 500µm diameter indenter, regional mechanical properties were measured in cortical grey and white matter and subregions of the hippocampus. All regions were highly viscoelastic. Cortical grey matter was significantly more compliant than the white matter or hippocampus which were similar in modulus. Although shear modulus was not correlated with the age of the donor, cortex from male donors was significantly stiffer than from female donors. The presented material properties will help to populate finite element models of the brain as they become more anatomically detailed. We present the first mechanical characterization of fresh, post-operative human brain tissue using an indentation loading mode. Indentation generates highly localized data, allowing structure-specific mechanical properties to be determined from small tissue samples resected during surgery. It also avoids pitfalls of cadaveric tissue and allows data to be collected before degenerative processes alter mechanical properties. To correctly predict traumatic brain injury, finite element models must calculate intracranial deformation during head impact. The functional consequences of injury depend on the anatomical structures injured. Therefore, morbidity depends on the distribution of deformation across structures. Accurate prediction of structure-specific deformation requires structure-specific mechanical properties. This data will facilitate deeper understanding of the physical mechanisms that lead to traumatic brain injury. Copyright © 2017 Acta Materialia Inc. Published by Elsevier Ltd. All rights reserved.

  16. Evaluation of cat brain infarction model using microPET

    International Nuclear Information System (INIS)

    Lee, J. J.; Lee, D. S.; Kim, J. H.; Hwang, D. W.; Jung, J. G.; Lee, M. C; Lim, S. M

    2004-01-01

    PET has some disadvantage in the imaging of small animal due to poor resolution. With the advance of microPET scanner, it is possible to image small animals. However, the image quality was not so much satisfactory as human image. As cats have relatively large sized brain, cat brain imaging was superior to mice or rat. In this study, we established the cat brain infarction model and evaluate it and its temporal change using microPET scanner. Two adult male cats were used. Anesthesia was done with xylazine and ketamine HCl. A burr hole was made at 1cm right lateral to the bregma. Collagenase type IV 10 ul was injected using 30G needle for 5 minutes to establish the infarction model. F-18 FDG microPET (Concorde Microsystems Inc., Knoxville. TN) scans were performed 1. 11 and 32 days after the infarction. In addition. 18F-FDG PET scans were performed using Gemini PET scanner (Philips medical systems. CA, USA) 13 and 47 days after the infarction. Two cat brain infarction models were established. The glucose metabolism of an infraction lesion improved with time. An infarction lesion was also distinguishable in the Gemini PET scan. We successfully established the cat brain infarction model and evaluated the infarcted lesion and its temporal change using F-18 FDG microPET scanner

  17. Evaluation of cat brain infarction model using microPET

    Energy Technology Data Exchange (ETDEWEB)

    Lee, Jong Jin; Lee, Dong Soo; Kim, Yun Hui; Hwang, Do Won; Kim, Jin Su; Chung, June Key; Lee, Myung Chul [College of Medicine, Seoul National Univ., Seoul (Korea, Republic of); Lim, Sang Moo [Korea Institite of Radiological and Medical Sciences, Seoul (Korea, Republic of)

    2004-12-01

    PET has some disadvantage in the imaging of small animal due to poor resolution. With the advent of microPET scanner, it is possible to image small animals. However, the image quality was not good enough as human image. Due to larger brain, cat brain imaging was superior to mouse or rat. In this study, we established the cat brain infarction model and evaluate it and its temporal change using microPET scanner. Two adult male cats were used. Anesthesia was done with xylazine and ketamine HCI. A burr hole was made at 1 cm right lateral to the bregma. Collagenase type IV 10 {mu}l was injected using 30 G needle for 5 minutes to establish the infarction model. {sup 18}F-FDG microPET (Concorde Microsystems Inc., Knoxville, TN) scans were performed 1, 11 and 32 days after the infarction. In addition, {sup 18}F-FDG PET scans were performed using human PET scanner (Gemini, Philips medical systems, CA, USA) 13 and 47 days after the infarction. Two cat brain infarction models were established. The glucose metabolism of an infarction lesion improved with time. An infarction lesion was also distinguishable in the human PET scan. We successfully established the cat brain infarction model and evaluated the infarcted lesion and its temporal change using {sup 18}F-FDG microPET scanner.

  18. Evaluation of cat brain infarction model using microPET

    Energy Technology Data Exchange (ETDEWEB)

    Lee, J. J.; Lee, D. S.; Kim, J. H.; Hwang, D. W.; Jung, J. G.; Lee, M. C [College of Medicine, Seoul National University, Seoul (Korea, Republic of); Lim, S. M [Korea Institute of Radiological and Medical Sciences, Seoul (Korea, Republic of)

    2004-07-01

    PET has some disadvantage in the imaging of small animal due to poor resolution. With the advance of microPET scanner, it is possible to image small animals. However, the image quality was not so much satisfactory as human image. As cats have relatively large sized brain, cat brain imaging was superior to mice or rat. In this study, we established the cat brain infarction model and evaluate it and its temporal change using microPET scanner. Two adult male cats were used. Anesthesia was done with xylazine and ketamine HCl. A burr hole was made at 1cm right lateral to the bregma. Collagenase type IV 10 ul was injected using 30G needle for 5 minutes to establish the infarction model. F-18 FDG microPET (Concorde Microsystems Inc., Knoxville. TN) scans were performed 1. 11 and 32 days after the infarction. In addition. 18F-FDG PET scans were performed using Gemini PET scanner (Philips medical systems. CA, USA) 13 and 47 days after the infarction. Two cat brain infarction models were established. The glucose metabolism of an infraction lesion improved with time. An infarction lesion was also distinguishable in the Gemini PET scan. We successfully established the cat brain infarction model and evaluated the infarcted lesion and its temporal change using F-18 FDG microPET scanner.

  19. An adaptive complex network model for brain functional networks.

    Directory of Open Access Journals (Sweden)

    Ignacio J Gomez Portillo

    Full Text Available Brain functional networks are graph representations of activity in the brain, where the vertices represent anatomical regions and the edges their functional connectivity. These networks present a robust small world topological structure, characterized by highly integrated modules connected sparsely by long range links. Recent studies showed that other topological properties such as the degree distribution and the presence (or absence of a hierarchical structure are not robust, and show different intriguing behaviors. In order to understand the basic ingredients necessary for the emergence of these complex network structures we present an adaptive complex network model for human brain functional networks. The microscopic units of the model are dynamical nodes that represent active regions of the brain, whose interaction gives rise to complex network structures. The links between the nodes are chosen following an adaptive algorithm that establishes connections between dynamical elements with similar internal states. We show that the model is able to describe topological characteristics of human brain networks obtained from functional magnetic resonance imaging studies. In particular, when the dynamical rules of the model allow for integrated processing over the entire network scale-free non-hierarchical networks with well defined communities emerge. On the other hand, when the dynamical rules restrict the information to a local neighborhood, communities cluster together into larger ones, giving rise to a hierarchical structure, with a truncated power law degree distribution.

  20. Large Scale Computing for the Modelling of Whole Brain Connectivity

    DEFF Research Database (Denmark)

    Albers, Kristoffer Jon

    , which allows us to couple and explore different models and sampling procedures in runtime, still being applied to full-sized data. Using the implemented tools, we demonstrate that the models successfully can be applied for clustering whole-brain connectivity networks. Without being informed of spatial......The human brain constitutes an impressive network formed by the structural and functional connectivity patterns between billions of neurons. Modern functional and diffusion magnetic resonance imaging (fMRI and dMRI) provides unprecedented opportunities for exploring the functional and structural...... organization of the brain in continuously increasing resolution. From these images, networks of structural and functional connectivity can be constructed. Bayesian stochastic block modelling provides a prominent data-driven approach for uncovering the latent organization, by clustering the networks into groups...

  1. Resolving structural variability in network models and the brain.

    Directory of Open Access Journals (Sweden)

    Florian Klimm

    2014-03-01

    Full Text Available Large-scale white matter pathways crisscrossing the cortex create a complex pattern of connectivity that underlies human cognitive function. Generative mechanisms for this architecture have been difficult to identify in part because little is known in general about mechanistic drivers of structured networks. Here we contrast network properties derived from diffusion spectrum imaging data of the human brain with 13 synthetic network models chosen to probe the roles of physical network embedding and temporal network growth. We characterize both the empirical and synthetic networks using familiar graph metrics, but presented here in a more complete statistical form, as scatter plots and distributions, to reveal the full range of variability of each measure across scales in the network. We focus specifically on the degree distribution, degree assortativity, hierarchy, topological Rentian scaling, and topological fractal scaling--in addition to several summary statistics, including the mean clustering coefficient, the shortest path-length, and the network diameter. The models are investigated in a progressive, branching sequence, aimed at capturing different elements thought to be important in the brain, and range from simple random and regular networks, to models that incorporate specific growth rules and constraints. We find that synthetic models that constrain the network nodes to be physically embedded in anatomical brain regions tend to produce distributions that are most similar to the corresponding measurements for the brain. We also find that network models hardcoded to display one network property (e.g., assortativity do not in general simultaneously display a second (e.g., hierarchy. This relative independence of network properties suggests that multiple neurobiological mechanisms might be at play in the development of human brain network architecture. Together, the network models that we develop and employ provide a potentially useful

  2. A porcine model of haematogenous brain infectionwith staphylococcus aureus

    DEFF Research Database (Denmark)

    Astrup, Lærke Boye; Agerholm, Jørgen Steen; Nielsen, Ole Lerberg

    2012-01-01

    A PORCINE MODEL OF HAEMATOGENOUS BRAIN INFECTION WITH STAPHYLOCOCCUS AUREUS Astrup Lærke1, Agerholm Jørgen1, Nielsen Ole1, Jensen Henrik1, Leifsson Páll1, Iburg Tine2. 1: Faculty of Health and Medical Sciences, University of Copenhagen, Denmark boye@life.ku.dk 2: National Veterinary Institute......, Uppsala, Sweden Introduction Staphylococcus aureus (S.aureus) is a common cause of sepsis and brain abscesses in man and a frequent cause of porcine pyaemia. Here we present a porcine model of haematogenous S. aureus-induced brain infection. Materials and Methods Four pigs had two intravenous catheters...... inserted surgically, one in a. carotis communis and one in v. jugularis externa. All pigs received 106 CFU/kg body weight S. aureus through the arterial catheter. Bacteria were either suspended in isotonic saline infused at constant flow for 60 minutes (two pigs) or given as a bolus injection of autologoue...

  3. Data-driven forward model inference for EEG brain imaging

    DEFF Research Database (Denmark)

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

    2016-01-01

    . Combined with only a recorded EEG signal, we are able to estimate both the brain sources and a person-specific forward model by optimizing this parametrization. We thus not only solve an inverse problem, but also optimize over its specification. Our work demonstrates that personalized EEG brain imaging......Electroencephalography (EEG) is a flexible and accessible tool with excellent temporal resolution but with a spatial resolution hampered by volume conduction. Reconstruction of the cortical sources of measured EEG activity partly alleviates this problem and effectively turns EEG into a brain...... imaging device. The quality of the source reconstruction depends on the forward model which details head geometry and conductivities of different head compartments. These person-specific factors are complex to determine, requiring detailed knowledge of the subject’s anatomy and physiology. In this proof...

  4. Characterisation and modelling of brain tissue for surgical simulation.

    Science.gov (United States)

    Mendizabal, A; Aguinaga, I; Sánchez, E

    2015-05-01

    Interactive surgical simulators capable of providing a realistic visual and haptic feedback to users are a promising technology for medical training and surgery planification. However, modelling the physical behaviour of human organs and tissues for surgery simulation remains a challenge. On the one hand, this is due to the difficulty to characterise the physical properties of biological soft tissues. On the other hand, the challenge still remains in the computation time requirements of real-time simulation required in interactive systems. Real-time surgical simulation and medical training must employ a sufficiently accurate and simple model of soft tissues in order to provide a realistic haptic and visual response. This study attempts to characterise the brain tissue at similar conditions to those that take place on surgical procedures. With this aim, porcine brain tissue is characterised, as a surrogate of human brain, on a rotational rheometer at low strain rates and large strains. In order to model the brain tissue with an adequate level of accuracy and simplicity, linear elastic, hyperelastic and quasi-linear viscoelastic models are defined. These models are simulated using the ABAQUS finite element platform and compared with the obtained experimental data. Copyright © 2015 Elsevier Ltd. All rights reserved.

  5. Multilayer modeling and analysis of human brain networks.

    Science.gov (United States)

    De Domenico, Manlio

    2017-05-01

    Understanding how the human brain is structured, and how its architecture is related to function, is of paramount importance for a variety of applications, including but not limited to new ways to prevent, deal with, and cure brain diseases, such as Alzheimer's or Parkinson's, and psychiatric disorders, such as schizophrenia. The recent advances in structural and functional neuroimaging, together with the increasing attitude toward interdisciplinary approaches involving computer science, mathematics, and physics, are fostering interesting results from computational neuroscience that are quite often based on the analysis of complex network representation of the human brain. In recent years, this representation experienced a theoretical and computational revolution that is breaching neuroscience, allowing us to cope with the increasing complexity of the human brain across multiple scales and in multiple dimensions and to model structural and functional connectivity from new perspectives, often combined with each other. In this work, we will review the main achievements obtained from interdisciplinary research based on magnetic resonance imaging and establish de facto, the birth of multilayer network analysis and modeling of the human brain. © The Author 2017. Published by Oxford University Press.

  6. An Evolutionary Game Theory Model of Spontaneous Brain Functioning.

    Science.gov (United States)

    Madeo, Dario; Talarico, Agostino; Pascual-Leone, Alvaro; Mocenni, Chiara; Santarnecchi, Emiliano

    2017-11-22

    Our brain is a complex system of interconnected regions spontaneously organized into distinct networks. The integration of information between and within these networks is a continuous process that can be observed even when the brain is at rest, i.e. not engaged in any particular task. Moreover, such spontaneous dynamics show predictive value over individual cognitive profile and constitute a potential marker in neurological and psychiatric conditions, making its understanding of fundamental importance in modern neuroscience. Here we present a theoretical and mathematical model based on an extension of evolutionary game theory on networks (EGN), able to capture brain's interregional dynamics by balancing emulative and non-emulative attitudes among brain regions. This results in the net behavior of nodes composing resting-state networks identified using functional magnetic resonance imaging (fMRI), determining their moment-to-moment level of activation and inhibition as expressed by positive and negative shifts in BOLD fMRI signal. By spontaneously generating low-frequency oscillatory behaviors, the EGN model is able to mimic functional connectivity dynamics, approximate fMRI time series on the basis of initial subset of available data, as well as simulate the impact of network lesions and provide evidence of compensation mechanisms across networks. Results suggest evolutionary game theory on networks as a new potential framework for the understanding of human brain network dynamics.

  7. Nano-Modeling and Computation in Bio and Brain Dynamics

    Directory of Open Access Journals (Sweden)

    Paolo Di Sia

    2016-04-01

    Full Text Available The study of brain dynamics currently utilizes the new features of nanobiotechnology and bioengineering. New geometric and analytical approaches appear very promising in all scientific areas, particularly in the study of brain processes. Efforts to engage in deep comprehension lead to a change in the inner brain parameters, in order to mimic the external transformation by the proper use of sensors and effectors. This paper highlights some crossing research areas of natural computing, nanotechnology, and brain modeling and considers two interesting theoretical approaches related to brain dynamics: (a the memory in neural network, not as a passive element for storing information, but integrated in the neural parameters as synaptic conductances; and (b a new transport model based on analytical expressions of the most important transport parameters, which works from sub-pico-level to macro-level, able both to understand existing data and to give new predictions. Complex biological systems are highly dependent on the context, which suggests a “more nature-oriented” computational philosophy.

  8. A fractional motion diffusion model for grading pediatric brain tumors.

    Science.gov (United States)

    Karaman, M Muge; Wang, He; Sui, Yi; Engelhard, Herbert H; Li, Yuhua; Zhou, Xiaohong Joe

    2016-01-01

    To demonstrate the feasibility of a novel fractional motion (FM) diffusion model for distinguishing low- versus high-grade pediatric brain tumors; and to investigate its possible advantage over apparent diffusion coefficient (ADC) and/or a previously reported continuous-time random-walk (CTRW) diffusion model. With approval from the institutional review board and written informed consents from the legal guardians of all participating patients, this study involved 70 children with histopathologically-proven brain tumors (30 low-grade and 40 high-grade). Multi- b -value diffusion images were acquired and analyzed using the FM, CTRW, and mono-exponential diffusion models. The FM parameters, D fm , φ , ψ (non-Gaussian diffusion statistical measures), and the CTRW parameters, D m , α , β (non-Gaussian temporal and spatial diffusion heterogeneity measures) were compared between the low- and high-grade tumor groups by using a Mann-Whitney-Wilcoxon U test. The performance of the FM model for differentiating between low- and high-grade tumors was evaluated and compared with that of the CTRW and the mono-exponential models using a receiver operating characteristic (ROC) analysis. The FM parameters were significantly lower ( p  CTRW model. Similar to the CTRW model, the FM model can improve differentiation between low- and high-grade pediatric brain tumors over ADC.

  9. Calcium-activated potassium channels mediated blood-brain tumor barrier opening in a rat metastatic brain tumor model

    Directory of Open Access Journals (Sweden)

    Ong John M

    2007-03-01

    Full Text Available Abstract Background The blood-brain tumor barrier (BTB impedes the delivery of therapeutic agents to brain tumors. While adequate delivery of drugs occurs in systemic tumors, the BTB limits delivery of anti-tumor agents into brain metastases. Results In this study, we examined the function and regulation of calcium-activated potassium (KCa channels in a rat metastatic brain tumor model. We showed that intravenous infusion of NS1619, a KCa channel agonist, and bradykinin selectively enhanced BTB permeability in brain tumors, but not in normal brain. Iberiotoxin, a KCa channel antagonist, significantly attenuated NS1619-induced BTB permeability increase. We found KCa channels and bradykinin type 2 receptors (B2R expressed in cultured human metastatic brain tumor cells (CRL-5904, non-small cell lung cancer, metastasized to brain, human brain microvessel endothelial cells (HBMEC and human lung cancer brain metastasis tissues. Potentiometric assays demonstrated the activity of KCa channels in metastatic brain tumor cells and HBMEC. Furthermore, we detected higher expression of KCa channels in the metastatic brain tumor tissue and tumor capillary endothelia as compared to normal brain tissue. Co-culture of metastatic brain tumor cells and brain microvessel endothelial cells showed an upregulation of KCa channels, which may contribute to the overexpression of KCa channels in tumor microvessels and selectivity of BTB opening. Conclusion These findings suggest that KCa channels in metastatic brain tumors may serve as an effective target for biochemical modulation of BTB permeability to enhance selective delivery of chemotherapeutic drugs to metastatic brain tumors.

  10. Riemannian multi-manifold modeling and clustering in brain networks

    Science.gov (United States)

    Slavakis, Konstantinos; Salsabilian, Shiva; Wack, David S.; Muldoon, Sarah F.; Baidoo-Williams, Henry E.; Vettel, Jean M.; Cieslak, Matthew; Grafton, Scott T.

    2017-08-01

    This paper introduces Riemannian multi-manifold modeling in the context of brain-network analytics: Brainnetwork time-series yield features which are modeled as points lying in or close to a union of a finite number of submanifolds within a known Riemannian manifold. Distinguishing disparate time series amounts thus to clustering multiple Riemannian submanifolds. To this end, two feature-generation schemes for brain-network time series are put forth. The first one is motivated by Granger-causality arguments and uses an auto-regressive moving average model to map low-rank linear vector subspaces, spanned by column vectors of appropriately defined observability matrices, to points into the Grassmann manifold. The second one utilizes (non-linear) dependencies among network nodes by introducing kernel-based partial correlations to generate points in the manifold of positivedefinite matrices. Based on recently developed research on clustering Riemannian submanifolds, an algorithm is provided for distinguishing time series based on their Riemannian-geometry properties. Numerical tests on time series, synthetically generated from real brain-network structural connectivity matrices, reveal that the proposed scheme outperforms classical and state-of-the-art techniques in clustering brain-network states/structures.

  11. Models to Tailor Brain Stimulation Therapies in Stroke

    Directory of Open Access Journals (Sweden)

    E. B. Plow

    2016-01-01

    Full Text Available A great challenge facing stroke rehabilitation is the lack of information on how to derive targeted therapies. As such, techniques once considered promising, such as brain stimulation, have demonstrated mixed efficacy across heterogeneous samples in clinical studies. Here, we explain reasons, citing its one-type-suits-all approach as the primary cause of variable efficacy. We present evidence supporting the role of alternate substrates, which can be targeted instead in patients with greater damage and deficit. Building on this groundwork, this review will also discuss different frameworks on how to tailor brain stimulation therapies. To the best of our knowledge, our report is the first instance that enumerates and compares across theoretical models from upper limb recovery and conditions like aphasia and depression. Here, we explain how different models capture heterogeneity across patients and how they can be used to predict which patients would best respond to what treatments to develop targeted, individualized brain stimulation therapies. Our intent is to weigh pros and cons of testing each type of model so brain stimulation is successfully tailored to maximize upper limb recovery in stroke.

  12. A porcine model of haematogenous brain infectionwith staphylococcus aureus

    DEFF Research Database (Denmark)

    Astrup, Lærke Boye; Agerholm, Jørgen Steen; Nielsen, Ole Lerberg

    2012-01-01

    thromboemboli (two pigs). The venous catheter was used for blood sampling before, during and after inoculation. The pigs were euthanized either 24 or 48 hours after inoculation. The brains were collected and examined histologically. Results We describe unifocal suppurative encephalitis 48 hours after......, Uppsala, Sweden Introduction Staphylococcus aureus (S.aureus) is a common cause of sepsis and brain abscesses in man and a frequent cause of porcine pyaemia. Here we present a porcine model of haematogenous S. aureus-induced brain infection. Materials and Methods Four pigs had two intravenous catheters...... inserted surgically, one in a. carotis communis and one in v. jugularis externa. All pigs received 106 CFU/kg body weight S. aureus through the arterial catheter. Bacteria were either suspended in isotonic saline infused at constant flow for 60 minutes (two pigs) or given as a bolus injection of autologoue...

  13. Modeling and Targeting MYC Genes in Childhood Brain Tumors

    Science.gov (United States)

    Hutter, Sonja; Bolin, Sara; Weishaupt, Holger; Swartling, Fredrik J.

    2017-01-01

    Brain tumors are the second most common group of childhood cancers, accounting for about 20%–25% of all pediatric tumors. Deregulated expression of the MYC family of transcription factors, particularly c-MYC and MYCN genes, has been found in many of these neoplasms, and their expression levels are often correlated with poor prognosis. Elevated c-MYC/MYCN initiates and drives tumorigenesis in many in vivo model systems of pediatric brain tumors. Therefore, inhibition of their oncogenic function is an attractive therapeutic target. In this review, we explore the roles of MYC oncoproteins and their molecular targets during the formation, maintenance, and recurrence of childhood brain tumors. We also briefly summarize recent progress in the development of therapeutic approaches for pharmacological inhibition of MYC activity in these tumors. PMID:28333115

  14. Dosha brain-types: A neural model of individual differences.

    Science.gov (United States)

    Travis, Frederick T; Wallace, Robert Keith

    2015-01-01

    This paper explores brain patterns associated with the three categories of regulatory principles of the body, mind, and behavior in Ayurveda, called Vata, Pitta, and Kapha dosha. A growing body of research has reported patterns of blood chemistry, genetic expression, physiological states, and chronic diseases associated with each dosha type. Since metabolic and growth factors are controlled by the nervous system, each dosha type should be associated with patterns of functioning of six major areas of the nervous system: The prefrontal cortex, the reticular activating system, the autonomic nervous system, the enteric nervous system, the limbic system, and the hypothalamus. For instance, the prefrontal cortex, which includes the anterior cingulate, ventral medial, and the dorsal lateral cortices, would exhibit a high range of functioning in the Vata brain-type leading to the possibility of being easily overstimulated. The Vata brain-type performs activity quickly. Learns quickly and forgets quickly. Their fast mind gives them an edge in creative problem solving. The Pitta brain-type reacts strongly to all challenges leading to purposeful and resolute actions. They never give up and are very dynamic and goal oriented. The Kapha brain-type is slow and steady leading to methodical thinking and action. They prefer routine and needs stimulation to get going. A model of dosha brain-types could provide a physiological foundation to understand individual differences. This model could help individualize treatment modalities to address different mental and physical dysfunctions. It also could explain differences in behavior seen in clinical as well as in normal populations.

  15. Dosha brain-types: A neural model of individual differences

    Directory of Open Access Journals (Sweden)

    Frederick T Travis

    2015-01-01

    Full Text Available This paper explores brain patterns associated with the three categories of regulatory principles of the body, mind, and behavior in Ayurveda, called Vata, Pitta, and Kapha dosha. A growing body of research has reported patterns of blood chemistry, genetic expression, physiological states, and chronic diseases associated with each dosha type. Since metabolic and growth factors are controlled by the nervous system, each dosha type should be associated with patterns of functioning of six major areas of the nervous system: The prefrontal cortex, the reticular activating system, the autonomic nervous system, the enteric nervous system, the limbic system, and the hypothalamus. For instance, the prefrontal cortex, which includes the anterior cingulate, ventral medial, and the dorsal lateral cortices, would exhibit a high range of functioning in the Vata brain-type leading to the possibility of being easily overstimulated. The Vata brain-type performs activity quickly. Learns quickly and forgets quickly. Their fast mind gives them an edge in creative problem solving. The Pitta brain-type reacts strongly to all challenges leading to purposeful and resolute actions. They never give up and are very dynamic and goal oriented. The Kapha brain-type is slow and steady leading to methodical thinking and action. They prefer routine and needs stimulation to get going. A model of dosha brain-types could provide a physiological foundation to understand individual differences. This model could help individualize treatment modalities to address different mental and physical dysfunctions. It also could explain differences in behavior seen in clinical as well as in normal populations.

  16. Quantitative genetic analysis of brain size variation in sticklebacks: support for the mosaic model of brain evolution.

    Science.gov (United States)

    Noreikiene, Kristina; Herczeg, Gábor; Gonda, Abigél; Balázs, Gergely; Husby, Arild; Merilä, Juha

    2015-07-07

    The mosaic model of brain evolution postulates that different brain regions are relatively free to evolve independently from each other. Such independent evolution is possible only if genetic correlations among the different brain regions are less than unity. We estimated heritabilities, evolvabilities and genetic correlations of relative size of the brain, and its different regions in the three-spined stickleback (Gasterosteus aculeatus). We found that heritabilities were low (average h(2) = 0.24), suggesting a large plastic component to brain architecture. However, evolvabilities of different brain parts were moderate, suggesting the presence of additive genetic variance to sustain a response to selection in the long term. Genetic correlations among different brain regions were low (average rG = 0.40) and significantly less than unity. These results, along with those from analyses of phenotypic and genetic integration, indicate a high degree of independence between different brain regions, suggesting that responses to selection are unlikely to be severely constrained by genetic and phenotypic correlations. Hence, the results give strong support for the mosaic model of brain evolution. However, the genetic correlation between brain and body size was high (rG = 0.89), suggesting a constraint for independent evolution of brain and body size in sticklebacks. © 2015 The Author(s) Published by the Royal Society. All rights reserved.

  17. MR Vascular Fingerprinting in Stroke and Brain Tumors Models.

    Science.gov (United States)

    Lemasson, B; Pannetier, N; Coquery, N; Boisserand, Ligia S B; Collomb, Nora; Schuff, N; Moseley, M; Zaharchuk, G; Barbier, E L; Christen, T

    2016-11-24

    In this study, we evaluated an MRI fingerprinting approach (MRvF) designed to provide high-resolution parametric maps of the microvascular architecture (i.e., blood volume fraction, vessel diameter) and function (blood oxygenation) simultaneously. The method was tested in rats (n = 115), divided in 3 models: brain tumors (9 L, C6, F98), permanent stroke, and a control group of healthy animals. We showed that fingerprinting can robustly distinguish between healthy and pathological brain tissues with different behaviors in tumor and stroke models. In particular, fingerprinting revealed that C6 and F98 glioma models have similar signatures while 9 L present a distinct evolution. We also showed that it is possible to improve the results of MRvF and obtain supplemental information by changing the numerical representation of the vascular network. Finally, good agreement was found between MRvF and conventional MR approaches in healthy tissues and in the C6, F98, and permanent stroke models. For the 9 L glioma model, fingerprinting showed blood oxygenation measurements that contradict results obtained with a quantitative BOLD approach. In conclusion, MR vascular fingerprinting seems to be an efficient technique to study microvascular properties in vivo. Multiple technical improvements are feasible and might improve diagnosis and management of brain diseases.

  18. Computational brain models: Advances from system biology and future challenges

    Directory of Open Access Journals (Sweden)

    George E. Barreto

    2015-02-01

    Full Text Available Computational brain models focused on the interactions between neurons and astrocytes, modeled via metabolic reconstructions, are reviewed. The large source of experimental data provided by the -omics techniques and the advance/application of computational and data-management tools are being fundamental. For instance, in the understanding of the crosstalk between these cells, the key neuroprotective mechanisms mediated by astrocytes in specific metabolic scenarios (1 and the identification of biomarkers for neurodegenerative diseases (2,3. However, the modeling of these interactions demands a clear view of the metabolic and signaling pathways implicated, but most of them are controversial and are still under evaluation (4. Hence, to gain insight into the complexity of these interactions a current view of the main pathways implicated in the neuron-astrocyte communication processes have been made from recent experimental reports and reviews. Furthermore, target problems, limitations and main conclusions have been identified from metabolic models of the brain reported from 2010. Finally, key aspects to take into account into the development of a computational model of the brain and topics that could be approached from a systems biology perspective in future research are highlighted.

  19. Using computational models to relate structural and functional brain connectivity

    Czech Academy of Sciences Publication Activity Database

    Hlinka, Jaroslav; Coombes, S.

    2012-01-01

    Roč. 36, č. 2 (2012), s. 2137-2145 ISSN 0953-816X R&D Projects: GA MŠk 7E08027 EU Projects: European Commission(XE) 200728 - BRAINSYNC Institutional research plan: CEZ:AV0Z10300504 Keywords : brain disease * computational modelling * functional connectivity * graph theory * structural connectivity Subject RIV: FH - Neurology Impact factor: 3.753, year: 2012

  20. Globalization and migration: A "unified brain drain" model

    OpenAIRE

    Brezis, Elise S.; Soueri, Ariel

    2012-01-01

    Globalization has led to a vast flow of migration of workers but also of students. The purpose of this paper is to analyze the migration of individuals encompassing decisions already at the level of education. We develop a unified brain drain model that incorporates the decisions of an individual vis - à - vis both education and migration. In the empirical part, this paper addresses international flows of migration within the EU and presents strong evidence of concentration of students in cou...

  1. Rotenone exerts developmental neurotoxicity in a human brain spheroid model.

    Science.gov (United States)

    Pamies, David; Block, Katharina; Lau, Pierre; Gribaldo, Laura; Pardo, Carlos A; Barreras, Paula; Smirnova, Lena; Wiersma, Daphne; Zhao, Liang; Harris, Georgina; Hartung, Thomas; Hogberg, Helena T

    2018-02-08

    Growing concern suggests that some chemicals exert (developmental) neurotoxicity (DNT and NT) and are linked to the increase in incidence of autism, attention deficit and hyperactivity disorders. The high cost of routine tests for DNT and NT assessment make it difficult to test the high numbers of existing chemicals. Thus, more cost effective neurodevelopmental models are needed. The use of induced pluripotent stem cells (iPSC) in combination with the emerging human 3D tissue culture platforms, present a novel tool to predict and study human toxicity. By combining these technologies, we generated multicellular brain spheroids (BrainSpheres) from human iPSC. The model has previously shown to be reproducible and recapitulates several neurodevelopmental features. Our results indicate, rotenone's toxic potency varies depending on the differentiation status of the cells, showing higher reactive oxygen species (ROS) and higher mitochondrial dysfunction during early than later differentiation stages. Immuno-fluorescence morphology analysis after rotenone exposure indicated dopaminergic-neuron selective toxicity at non-cytotoxic concentrations (1 μM), while astrocytes and other neuronal cell types were affected at (general) cytotoxic concentrations (25 μM). Omics analysis showed changes in key pathways necessary for brain development, indicating rotenone as a developmental neurotoxicant and show a possible link between previously shown effects on neurite outgrowth and presently observed effects on Ca2+ reabsorption, synaptogenesis and PPAR pathway disruption. In conclusion, our BrainSpheres model has shown to be a reproducible and novel tool to study neurotoxicity and developmental neurotoxicity. Results presented here support the idea that rotenone can potentially be a developmental neurotoxicant. Copyright © 2018. Published by Elsevier Inc.

  2. Drosophila melanogaster as a Model Organism of Brain Diseases

    Directory of Open Access Journals (Sweden)

    Werner Paulus

    2009-02-01

    Full Text Available Drosophila melanogaster has been utilized to model human brain diseases. In most of these invertebrate transgenic models, some aspects of human disease are reproduced. Although investigation of rodent models has been of significant impact, invertebrate models offer a wide variety of experimental tools that can potentially address some of the outstanding questions underlying neurological disease. This review considers what has been gleaned from invertebrate models of neurodegenerative diseases, including Alzheimer’s disease, Parkinson’s disease, metabolic diseases such as Leigh disease, Niemann-Pick disease and ceroid lipofuscinoses, tumor syndromes such as neurofibromatosis and tuberous sclerosis, epilepsy as well as CNS injury. It is to be expected that genetic tools in Drosophila will reveal new pathways and interactions, which hopefully will result in molecular based therapy approaches.

  3. Longitudinal Examination of Resilience After Traumatic Brain Injury: A Traumatic Brain Injury Model Systems Study.

    Science.gov (United States)

    Marwitz, Jennifer H; Sima, Adam P; Kreutzer, Jeffrey S; Dreer, Laura E; Bergquist, Thomas F; Zafonte, Ross; Johnson-Greene, Douglas; Felix, Elizabeth R

    2018-02-01

    To evaluate (1) the trajectory of resilience during the first year after a moderate-severe traumatic brain injury (TBI); (2) factors associated with resilience at 3, 6, and 12 months postinjury; and (3) changing relationships over time between resilience and other factors. Longitudinal analysis of an observational cohort. Five inpatient rehabilitation centers. Patients with TBI (N=195) enrolled in the resilience module of the TBI Model Systems study with data collected at 3-, 6-, and 12-month follow-up. Not applicable. Connor-Davidson Resilience Scale. Initially, resilience levels appeared to be stable during the first year postinjury. Individual growth curve models were used to examine resilience over time in relation to demographic, psychosocial, and injury characteristics. After adjusting for these characteristics, resilience actually declined over time. Higher levels of resilience were related to nonminority status, absence of preinjury substance abuse, lower anxiety and disability level, and greater life satisfaction. Resilience is a construct that is relevant to understanding brain injury outcomes and has potential value in planning clinical interventions. Copyright © 2017 American Congress of Rehabilitation Medicine. Published by Elsevier Inc. All rights reserved.

  4. Internet and Social Media Use After Traumatic Brain Injury: A Traumatic Brain Injury Model Systems Study.

    Science.gov (United States)

    Baker-Sparr, Christina; Hart, Tessa; Bergquist, Thomas; Bogner, Jennifer; Dreer, Laura; Juengst, Shannon; Mellick, David; OʼNeil-Pirozzi, Therese M; Sander, Angelle M; Whiteneck, Gale G

    To characterize Internet and social media use among adults with moderate to severe traumatic brain injury (TBI) and to compare demographic and socioeconomic factors associated with Internet use between those with and without TBI. Ten Traumatic Brain Injury Model Systems centers. Persons with moderate to severe TBI (N = 337) enrolled in the TBI Model Systems National Database and eligible for follow-up from April 1, 2014, to March 31, 2015. Prospective cross-sectional observational cohort study. Internet usage survey. The proportion of Internet users with TBI was high (74%) but significantly lower than those in the general population (84%). Smartphones were the most prevalent means of Internet access for persons with TBI. The majority of Internet users with TBI had a profile account on a social networking site (79%), with more than half of the sample reporting multiplatform use of 2 or more social networking sites. Despite the prevalence of Internet use among persons with TBI, technological disparities remain in comparison with the general population. The extent of social media use among persons with TBI demonstrates the potential of these platforms for social engagement and other purposes. However, further research examining the quality of online activities and identifying potential risk factors of problematic use is recommended.

  5. Multiscale modeling and simulation of brain blood flow

    Energy Technology Data Exchange (ETDEWEB)

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

    2016-02-15

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

  6. Cyclosporin safety in a simplified rat brain tumor implantation model

    Directory of Open Access Journals (Sweden)

    Francisco H. C. Felix

    2012-01-01

    Full Text Available Brain cancer is the second neurological cause of death. A simplified animal brain tumor model using W256 (carcinoma 256, Walker cell line was developed to permit the testing of novel treatment modalities. Wistar rats had a cell tumor solution inoculated stereotactically in the basal ganglia (right subfrontal caudate. This model yielded tumor growth in 95% of the animals, and showed absence of extracranial metastasis and systemic infection. Survival median was 10 days. Estimated tumor volume was 17.08±6.7 mm³ on the 7th day and 67.25±19.8 mm³ on 9th day post-inoculation. Doubling time was 24.25 h. Tumor growth induced cachexia, but no hematological or biochemical alterations. This model behaved as an undifferentiated tumor and can be promising for studying tumor cell migration in the central nervous system. Dexamethasone 3.0 mg/kg/day diminished significantly survival in this model. Cyclosporine 10 mg/kg/day administration was safely tolerated.

  7. Dyadic Brain - A Biological Model for Deliberative Inference

    Directory of Open Access Journals (Sweden)

    Iliyan Ivanov

    2017-10-01

    Full Text Available The human brain is arguably the most complex information processing system. It operates by acquiring data from the environment, recognizing patterns of events’ occurrence, anticipating their re-occurrence and in turn generating appropriate behavioral responses. Through the lenses of the free-energy principle any self-organizing system that is at equilibrium with its environment must minimize its free energy either by manipulating the environmental sensory input or by manipulating its internal states thus altering the recognition density of the outside stimuli. However, several sets of challenges interfere with the human brain's ability to learn and adapt in such a theoretically optimal fashion. These may include, and are not limited to, functional inconsistencies related to attention and memory processes, the functions of “fast” and “slow” thinking and responding, and the ability of emotional states to generate unintended behavioral outcomes that are less adaptive or inappropriate. This paper will review literature on the subject of how ideal learning viewed from the free-energy principle perspective may be affected by the above mentioned limitations and will suggest a model of information processing that may have developed as a way of overcoming these challenges. This neurobiological model stipulates that a neuronal network is formed in response to environmental input and is paralleled by at least one and possibly multiple networks that activate intrinsically and represent “virtual responses” to a situation that demands a behavioral response. This model accounts for how the brain generates a multiplicity of potential behavioral responses and may “choose” the one that seems most appropriate and also explains the uncanny ability of humans to socialize and collaborate. Implications for understanding humans’ ability to learn from others, deliberate on opposing constructs and access and utilize information outside of individual

  8. Brain Dynamics An Introduction to Models and Simualtions

    CERN Document Server

    Haken, Hermann

    2008-01-01

    Brain Dynamics serves to introduce graduate students and nonspecialists from various backgrounds to the field of mathematical and computational neurosciences. Some of the advanced chapters will also be of interest to the specialists. The book approaches the subject through pulse-coupled neural networks, with at their core the lighthouse and integrate-and-fire models, which allow for the highly flexible modelling of realistic synaptic activity, synchronization and spatio-temporal pattern formation. Topics also include pulse-averaged equations and their application to movement coordination. The book closes with a short analysis of models versus the real neurophysiological system. The second edition has been thoroughly updated and augmented by two extensive chapters that discuss the interplay between pattern recognition and synchronization. Further, to enhance the usefulness as textbook and for self-study, the detailed solutions for all 34 exercises throughout the text have been added.

  9. Model sparsity and brain pattern interpretation of classification models in neuroimaging

    DEFF Research Database (Denmark)

    Rasmussen, Peter Mondrup; Madsen, Kristoffer Hougaard; Churchill, Nathan W

    2012-01-01

    Interest is increasing in applying discriminative multivariate analysis techniques to the analysis of functional neuroimaging data. Model interpretation is of great importance in the neuroimaging context, and is conventionally based on a ‘brain map’ derived from the classification model. In this ...

  10. Modeling the brain-pituitary-gonad axis in salmon

    Energy Technology Data Exchange (ETDEWEB)

    Kim, Jonghan; Hayton, William L.; Schultz, Irv R.

    2006-08-24

    To better understand the complexity of the brain-pituitary-gonad axis (BPG) in fish, we developed a biologically based pharmacodynamic model capable of accurately predicting the normal functioning of the BPG axis in salmon. This first-generation model consisted of a set of 13 equations whose formulation was guided by published values for plasma concentrations of pituitary- (FSH, LH) and ovary- (estradiol, 17a,20b-dihydroxy-4-pregnene-3-one) derived hormones measured in Coho salmon over an annual spawning period. In addition, the model incorporated pertinent features of previously published mammalian models and indirect response pharmacodynamic models. Model-based equations include a description of gonadotropin releasing hormone (GnRH) synthesis and release from the hypothalamus, which is controlled by environmental variables such as photoperiod and water temperature. GnRH stimulated the biosynthesis of mRNA for FSH and LH, which were also influenced by estradiol concentration in plasma. The level of estradiol in the plasma was regulated by the oocytes, which moved along a maturation progression. Estradiol was synthesized at a basal rate and as oocytes matured, stimulation of its biosynthesis occurred. The BPG model can be integrated with toxico-genomic, -proteomic data, allowing linkage between molecular based biomarkers and reproduction in fish.

  11. 3D brain Organoids derived from pluripotent stem cells: promising experimental models for brain development and neurodegenerative disorders.

    Science.gov (United States)

    Lee, Chun-Ting; Bendriem, Raphael M; Wu, Wells W; Shen, Rong-Fong

    2017-08-20

    Three-dimensional (3D) brain organoids derived from human pluripotent stem cells (hPSCs), including embryonic stem cells (ESCs) and induced pluripotent stem cells (iPSCs), appear to recapitulate the brain's 3D cytoarchitectural arrangement and provide new opportunities to explore disease pathogenesis in the human brain. Human iPSC (hiPSC) reprogramming methods, combined with 3D brain organoid tools, may allow patient-derived organoids to serve as a preclinical platform to bridge the translational gap between animal models and human clinical trials. Studies using patient-derived brain organoids have already revealed novel insights into molecular and genetic mechanisms of certain complex human neurological disorders such as microcephaly, autism, and Alzheimer's disease. Furthermore, the combination of hiPSC technology and small-molecule high-throughput screening (HTS) facilitates the development of novel pharmacotherapeutic strategies, while transcriptome sequencing enables the transcriptional profiling of patient-derived brain organoids. Finally, the addition of CRISPR/Cas9 genome editing provides incredible potential for personalized cell replacement therapy with genetically corrected hiPSCs. This review describes the history and current state of 3D brain organoid differentiation strategies, a survey of applications of organoids towards studies of neurodevelopmental and neurodegenerative disorders, and the challenges associated with their use as in vitro models of neurological disorders.

  12. Modeling Brain Responses in an Arithmetic Working Memory Task

    Science.gov (United States)

    Hamid, Aini Ismafairus Abd; Yusoff, Ahmad Nazlim; Mukari, Siti Zamratol-Mai Sarah; Mohamad, Mazlyfarina; Manan, Hanani Abdul; Hamid, Khairiah Abdul

    2010-07-01

    Functional magnetic resonance imaging (fMRI) was used to investigate brain responses due to arithmetic working memory. Nine healthy young male subjects were given simple addition and subtraction instructions in noise and in quiet. The general linear model (GLM) and random field theory (RFT) were implemented in modelling the activation. The results showed that addition and subtraction evoked bilateral activation in Heschl's gyrus (HG), superior temporal gyrus (STG), inferior frontal gyrus (IFG), supramarginal gyrus (SG) and precentral gyrus (PCG). The HG, STG, SG and PCG activate higher number of voxels in noise as compared to in quiet for addition and subtraction except for IFG that showed otherwise. The percentage of signal change (PSC) in all areas is higher in quiet as compared to in noise. Surprisingly addition (not subtraction) exhibits stronger activation.

  13. Effects of Ecballium elaterium on brain in a rat model of sepsis ...

    African Journals Online (AJOL)

    Demet Arslan

    2017-08-31

    Aug 31, 2017 ... Ecballium elaterium (EE) on brain, and explored its therapeutic potential in an animal model of sepsis-associated ... Twenty-four hours after laparotomy, animals were sacrificied and the brains were removed. Brain homogenates were .... as mean ± standard deviation and median ± mini- mum-maximum.

  14. Cluster imaging of multi-brain networks (CIMBN: a general framework for hyperscanning and modeling a group of interacting brains

    Directory of Open Access Journals (Sweden)

    Lian eDuan

    2015-07-01

    Full Text Available Studying the neural basis of human social interactions is a key topic in the field of social neuroscience. Brain imaging studies in this field usually focus on the neural correlates of the social interactions between two participants. However, as the participant number further increases, even by a small amount, great difficulties raise. One challenge is how to concurrently scan all the interacting brains with high ecological validity, especially for a large number of participants. The other challenge is how to effectively model the complex group interaction behaviors emerging from the intricate neural information exchange among a group of socially organized people. Confronting these challenges, we propose a new approach called Cluster Imaging of Multi-brain Networks (CIMBN. CIMBN consists of two parts. The first part is a cluster imaging technique with high ecological validity based on multiple functional near-infrared spectroscopy (fNIRS systems. Using this technique, we can easily extend the simultaneous imaging capacity of social neuroscience studies up to dozens of participants. The second part of CIMBN is a multi-brain network (MBN modeling method based on graph theory. By taking each brain as a network node and the relationship between any two brains as a network edge, one can construct a network model for a group of interacting brains. The emergent group social behaviors can then be studied using the network’s properties, such as its topological structure and information exchange efficiency. Although there is still much work to do, as a general framework for hyperscanning and modeling a group of interacting brains, CIMBN can provide new insights into the neural correlates of group social interactions, and advance social neuroscience and social psychology.

  15. Language Model Applications to Spelling with Brain-Computer Interfaces

    Directory of Open Access Journals (Sweden)

    Anderson Mora-Cortes

    2014-03-01

    Full Text Available Within the Ambient Assisted Living (AAL community, Brain-Computer Interfaces (BCIs have raised great hopes as they provide alternative communication means for persons with disabilities bypassing the need for speech and other motor activities. Although significant advancements have been realized in the last decade, applications of language models (e.g., word prediction, completion have only recently started to appear in BCI systems. The main goal of this article is to review the language model applications that supplement non-invasive BCI-based communication systems by discussing their potential and limitations, and to discern future trends. First, a brief overview of the most prominent BCI spelling systems is given, followed by an in-depth discussion of the language models applied to them. These language models are classified according to their functionality in the context of BCI-based spelling: the static/dynamic nature of the user interface, the use of error correction and predictive spelling, and the potential to improve their classification performance by using language models. To conclude, the review offers an overview of the advantages and challenges when implementing language models in BCI-based communication systems when implemented in conjunction with other AAL technologies.

  16. Language model applications to spelling with Brain-Computer Interfaces.

    Science.gov (United States)

    Mora-Cortes, Anderson; Manyakov, Nikolay V; Chumerin, Nikolay; Van Hulle, Marc M

    2014-03-26

    Within the Ambient Assisted Living (AAL) community, Brain-Computer Interfaces (BCIs) have raised great hopes as they provide alternative communication means for persons with disabilities bypassing the need for speech and other motor activities. Although significant advancements have been realized in the last decade, applications of language models (e.g., word prediction, completion) have only recently started to appear in BCI systems. The main goal of this article is to review the language model applications that supplement non-invasive BCI-based communication systems by discussing their potential and limitations, and to discern future trends. First, a brief overview of the most prominent BCI spelling systems is given, followed by an in-depth discussion of the language models applied to them. These language models are classified according to their functionality in the context of BCI-based spelling: the static/dynamic nature of the user interface, the use of error correction and predictive spelling, and the potential to improve their classification performance by using language models. To conclude, the review offers an overview of the advantages and challenges when implementing language models in BCI-based communication systems when implemented in conjunction with other AAL technologies.

  17. Multistability in Large Scale Models of Brain Activity.

    Directory of Open Access Journals (Sweden)

    Mathieu Golos

    2015-12-01

    Full Text Available Noise driven exploration of a brain network's dynamic repertoire has been hypothesized to be causally involved in cognitive function, aging and neurodegeneration. The dynamic repertoire crucially depends on the network's capacity to store patterns, as well as their stability. Here we systematically explore the capacity of networks derived from human connectomes to store attractor states, as well as various network mechanisms to control the brain's dynamic repertoire. Using a deterministic graded response Hopfield model with connectome-based interactions, we reconstruct the system's attractor space through a uniform sampling of the initial conditions. Large fixed-point attractor sets are obtained in the low temperature condition, with a bigger number of attractors than ever reported so far. Different variants of the initial model, including (i a uniform activation threshold or (ii a global negative feedback, produce a similarly robust multistability in a limited parameter range. A numerical analysis of the distribution of the attractors identifies spatially-segregated components, with a centro-medial core and several well-delineated regional patches. Those different modes share similarity with the fMRI independent components observed in the "resting state" condition. We demonstrate non-stationary behavior in noise-driven generalizations of the models, with different meta-stable attractors visited along the same time course. Only the model with a global dynamic density control is found to display robust and long-lasting non-stationarity with no tendency toward either overactivity or extinction. The best fit with empirical signals is observed at the edge of multistability, a parameter region that also corresponds to the highest entropy of the attractors.

  18. Modeling Early Postnatal Brain Growth and Development with CT: Changes in the Brain Radiodensity Histogram from Birth to 2 Years.

    Science.gov (United States)

    Cauley, K A; Hu, Y; Och, J; Yorks, P J; Fielden, S W

    2018-02-15

    The majority of brain growth and development occur in the first 2 years of life. This study investigated these changes by analysis of the brain radiodensity histogram of head CT scans from the clinical population, 0-2 years of age. One hundred twenty consecutive head CTs with normal findings meeting the inclusion criteria from children from birth to 2 years were retrospectively identified from 3 different CT scan platforms. Histogram analysis was performed on brain-extracted images, and histogram mean, mode, full width at half maximum, skewness, kurtosis, and SD were correlated with subject age. The effects of scan platform were investigated. Normative curves were fitted by polynomial regression analysis. Average total brain volume was 360 cm 3 at birth, 948 cm 3 at 1 year, and 1072 cm 3 at 2 years. Total brain tissue density showed an 11% increase in mean density at 1 year and 19% at 2 years. Brain radiodensity histogram skewness was positive at birth, declining logarithmically in the first 200 days of life. The histogram kurtosis also decreased in the first 200 days to approach a normal distribution. Direct segmentation of CT images showed that changes in brain radiodensity histogram skewness correlated with, and can be explained by, a relative increase in gray matter volume and an increase in gray and white matter tissue density that occurs during this period of brain maturation. Normative metrics of the brain radiodensity histogram derived from routine clinical head CT images can be used to develop a model of normal brain development. © 2018 by American Journal of Neuroradiology.

  19. Clostridium butyricum exerts a neuroprotective effect in a mouse model of traumatic brain injury via the gut-brain axis.

    Science.gov (United States)

    Li, H; Sun, J; Du, J; Wang, F; Fang, R; Yu, C; Xiong, J; Chen, W; Lu, Z; Liu, J

    2017-11-27

    Traumatic brain injury (TBI) is a common occurrence following gastrointestinal dysfunction. Recently, more and more attentions are being focused on gut microbiota in brain and behavior. Glucagon-like peptide-1 (GLP-1) is considered as a mediator that links the gut-brain axis. The aim of this study was to explore the neuroprotective effects of Clostridium butyricum (Cb) on brain damage in a mouse model of TBI. Male C57BL/6 mice were subjected to a model of TBI-induced by weight-drop impact head injury and were treated intragastrically with Cb. The cognitive deficits, brain water content, neuronal death, and blood-brain barrier (BBB) permeability were evaluated. The expression of tight junction (TJ) proteins, Bcl-2, Bax, GLP-1 receptor (GLP-1R), and phosphorylation of Akt (p-Akt) in the brain were also measured. Moreover, the intestinal barrier permeability, the expression of TJ protein and GLP-1, and IL-6 level in the intestine were detected. Cb treatment significantly improved neurological dysfunction, brain edema, neurodegeneration, and BBB impairment. Meanwhile, Cb treatment also significantly increased the expression of TJ proteins (occludin and zonula occluden-1), p-Akt and Bcl-2, but decreased expression of Bax. Moreover, Cb treatment exhibited more prominent effects on decreasing the levels of plasma d-lactate and colonic IL-6, upregulating expression of Occludin, and protecting intestinal barrier integrity. Furthermore, Cb-treated mice showed increased the secretion of intestinal GLP-1 and upregulated expression of cerebral GLP-1R. Our findings demonstrated the neuroprotective effect of Cb in TBI mice and the involved mechanisms were partially attributed to the elevating GLP-1 secretion through the gut-brain axis. © 2017 John Wiley & Sons Ltd.

  20. Modeling Brain Circuitry over a Wide Range of Scales

    Directory of Open Access Journals (Sweden)

    Pascal eFua

    2015-04-01

    Full Text Available If we are ever to unravel the mysteries of brain function at its most fundamental level, we will need a precise understanding of how its component neurons connect to each other. Electron Microscopes (EM can now provide the nanometer resolution that is needed to image synapses, and therefore connections, while Light Microscopes (LM see at the micrometer resolution required to model the 3D structure of the dendritic network. Since both the topology and the connection strength are integral parts of the brain's wiring diagram, being able to combine these two modalities is critically important.In fact, these microscopes now routinely produce high-resolution imagery in such large quantities that the bottleneck becomes automated processing and interpretation, which is needed for such data to be exploited to its full potential. In this paper, we briefly review the Computer Vision techniques we have developed at EPFL to address this need. They include delineating dendritic arbors from LM imagery, segmenting organelles from EM, and combining the two into a consistent representation.

  1. Ultrasound-mediated delivery and distribution of polymeric nanoparticles in the normal brain parenchyma of a metastatic brain tumour model.

    Directory of Open Access Journals (Sweden)

    Habib Baghirov

    Full Text Available The treatment of brain diseases is hindered by the blood-brain barrier (BBB preventing most drugs from entering the brain. Focused ultrasound (FUS with microbubbles can open the BBB safely and reversibly. Systemic drug injection might induce toxicity, but encapsulation into nanoparticles reduces accumulation in normal tissue. Here we used a novel platform based on poly(2-ethyl-butyl cyanoacrylate nanoparticle-stabilized microbubbles to permeabilize the BBB in a melanoma brain metastasis model. With a dual-frequency ultrasound transducer generating FUS at 1.1 MHz and 7.8 MHz, we opened the BBB using nanoparticle-microbubbles and low-frequency FUS, and applied high-frequency FUS to generate acoustic radiation force and push nanoparticles through the extracellular matrix. Using confocal microscopy and image analysis, we quantified nanoparticle extravasation and distribution in the brain parenchyma. We also evaluated haemorrhage, as well as the expression of P-glycoprotein, a key BBB component. FUS and microbubbles distributed nanoparticles in the brain parenchyma, and the distribution depended on the extent of BBB opening. The results from acoustic radiation force were not conclusive, but in a few animals some effect could be detected. P-glycoprotein was not significantly altered immediately after sonication. In summary, FUS with our nanoparticle-stabilized microbubbles can achieve accumulation and displacement of nanoparticles in the brain parenchyma.

  2. Ultrasound-mediated delivery and distribution of polymeric nanoparticles in the normal brain parenchyma of a metastatic brain tumour model

    Science.gov (United States)

    Baghirov, Habib; Snipstad, Sofie; Sulheim, Einar; Berg, Sigrid; Hansen, Rune; Thorsen, Frits; Mørch, Yrr; Åslund, Andreas K. O.

    2018-01-01

    The treatment of brain diseases is hindered by the blood-brain barrier (BBB) preventing most drugs from entering the brain. Focused ultrasound (FUS) with microbubbles can open the BBB safely and reversibly. Systemic drug injection might induce toxicity, but encapsulation into nanoparticles reduces accumulation in normal tissue. Here we used a novel platform based on poly(2-ethyl-butyl cyanoacrylate) nanoparticle-stabilized microbubbles to permeabilize the BBB in a melanoma brain metastasis model. With a dual-frequency ultrasound transducer generating FUS at 1.1 MHz and 7.8 MHz, we opened the BBB using nanoparticle-microbubbles and low-frequency FUS, and applied high-frequency FUS to generate acoustic radiation force and push nanoparticles through the extracellular matrix. Using confocal microscopy and image analysis, we quantified nanoparticle extravasation and distribution in the brain parenchyma. We also evaluated haemorrhage, as well as the expression of P-glycoprotein, a key BBB component. FUS and microbubbles distributed nanoparticles in the brain parenchyma, and the distribution depended on the extent of BBB opening. The results from acoustic radiation force were not conclusive, but in a few animals some effect could be detected. P-glycoprotein was not significantly altered immediately after sonication. In summary, FUS with our nanoparticle-stabilized microbubbles can achieve accumulation and displacement of nanoparticles in the brain parenchyma. PMID:29338016

  3. Resuscitation speed affects brain injury in a large animal model of traumatic brain injury and shock

    DEFF Research Database (Denmark)

    Sillesen, Martin; Jin, Guang; Johansson, Pär I

    2014-01-01

    infusion speed increment NS (n¿=¿7). Hemodynamic variables over a 6-hour observation phase were recorded. Following euthanasia, brains were harvested and lesion size as well as brain swelling was measured.ResultsBolus FFP resuscitation resulted in greater brain swelling (22.36¿±¿1.03% vs. 15.58¿±¿2.52%, p...

  4. Dendrimer brain uptake and targeted therapy for brain injury in a large animal model of hypothermic circulatory arrest.

    Science.gov (United States)

    Mishra, Manoj K; Beaty, Claude A; Lesniak, Wojciech G; Kambhampati, Siva P; Zhang, Fan; Wilson, Mary A; Blue, Mary E; Troncoso, Juan C; Kannan, Sujatha; Johnston, Michael V; Baumgartner, William A; Kannan, Rangaramanujam M

    2014-03-25

    Treatment of brain injury following circulatory arrest is a challenging health issue with no viable therapeutic options. Based on studies in a clinically relevant large animal (canine) model of hypothermic circulatory arrest (HCA)-induced brain injury, neuroinflammation and excitotoxicity have been identified as key players in mediating the brain injury after HCA. Therapy with large doses of valproic acid (VPA) showed some neuroprotection but was associated with adverse side effects. For the first time in a large animal model, we explored whether systemically administered polyamidoamine (PAMAM) dendrimers could be effective in reaching target cells in the brain and deliver therapeutics. We showed that, upon systemic administration, hydroxyl-terminated PAMAM dendrimers are taken up in the brain of injured animals and selectively localize in the injured neurons and microglia in the brain. The biodistribution in other major organs was similar to that seen in small animal models. We studied systemic dendrimer-drug combination therapy with two clinically approved drugs, N-acetyl cysteine (NAC) (attenuating neuroinflammation) and valproic acid (attenuating excitotoxicity), building on positive outcomes in a rabbit model of perinatal brain injury. We prepared and characterized dendrimer-NAC (D-NAC) and dendrimer-VPA (D-VPA) conjugates in multigram quantities. A glutathione-sensitive linker to enable for fast intracellular release. In preliminary efficacy studies, combination therapy with D-NAC and D-VPA showed promise in this large animal model, producing 24 h neurological deficit score improvements comparable to high dose combination therapy with VPA and NAC, or free VPA, but at one-tenth the dose, while significantly reducing the adverse side effects. Since adverse side effects of drugs are exaggerated in HCA, the reduced side effects with dendrimer conjugates and suggestions of neuroprotection offer promise for these nanoscale drug delivery systems.

  5. Knowledge Modeling for the Outcome of Brain Stereotactic Radiosurgery

    Science.gov (United States)

    Hauck, Jillian E.

    Purpose: To build a model that will predict the survival time for patients that were treated with stereotactic radiosurgery for brain metastases using support vector machine (SVM) regression. Methods and Materials: This study utilized data from 481 patients, which were equally divided into training and validation datasets randomly. The SVM model used a Gaussian RBF function, along with various parameters, such as the size of the epsilon insensitive region and the cost parameter (C) that are used to control the amount of error tolerated by the model. The predictor variables for the SVM model consisted of the actual survival time of the patient, the number of brain metastases, the graded prognostic assessment (GPA) and Karnofsky Performance Scale (KPS) scores, prescription dose, and the largest planning target volume (PTV). The response of the model is the survival time of the patient. The resulting survival time predictions were analyzed against the actual survival times by single parameter classification and two-parameter classification. The predicted mean survival times within each classification were compared with the actual values to obtain the confidence interval associated with the model's predictions. In addition to visualizing the data on plots using the means and error bars, the correlation coefficients between the actual and predicted means of the survival times were calculated during each step of the classification. Results: The number of metastases and KPS scores, were consistently shown to be the strongest predictors in the single parameter classification, and were subsequently used as first classifiers in the two-parameter classification. When the survival times were analyzed with the number of metastases as the first classifier, the best correlation was obtained for patients with 3 metastases, while patients with 4 or 5 metastases had significantly worse results. When the KPS score was used as the first classifier, patients with a KPS score of 60 and

  6. Informing pedagogy through the brain-targeted teaching model.

    Science.gov (United States)

    Hardiman, Mariale

    2012-01-01

    Improving teaching to foster creative thinking and problem-solving for students of all ages will require two essential changes in current educational practice. First, to allow more time for deeper engagement with material, it is critical to reduce the vast number of topics often required in many courses. Second, and perhaps more challenging, is the alignment of pedagogy with recent research on cognition and learning. With a growing focus on the use of research to inform teaching practices, educators need a pedagogical framework that helps them interpret and apply research findings. This article describes the Brain-Targeted Teaching Model, a scheme that relates six distinct aspects of instruction to research from the neuro- and cognitive sciences.

  7. Parallel modeling of the electric field distribution in the brain

    OpenAIRE

    De Marco, Tommaso

    2011-01-01

    The term "Brain Imaging" identi�es a set of techniques to analyze the structure and/or functional behavior of the brain in normal and/or pathological situations. These techniques are largely used in the study of brain activity. In addition to clinical usage, analysis of brain activity is gaining popularity in others recent �fields, i.e. Brain Computer Interfaces (BCI) and the study of cognitive processes. In this context, usage of classical solutions (e.g. f MRI, PET-CT) could be unfeasib...

  8. A propositional representation model of anatomical and functional brain data.

    Science.gov (United States)

    Maturana, Pablo; Batrancourt, Bénédicte

    2011-01-01

    Networks can represent a large number of systems. Recent advances in the domain of networks have been transferred to the field of neuroscience. For example, the graph model has been used in neuroscience research as a methodological tool to examine brain networks organization, topology and complex dynamics, as well as a framework to test the structure-function hypothesis using neuroimaging data. In the current work we propose a graph-theoretical framework to represent anatomical, functional and neuropsychological assessment instruments information. On the one hand, interrelationships between anatomic elements constitute an anatomical graph. On the other hand, a functional graph contains several cognitive functions and their more elementary cognitive processes. Finally, the neuropsychological assessment instruments graph includes several neuropsychological tests and scales linked with their different sub-tests and variables. The two last graphs are connected by relations of type "explore" linking a particular instrument with the cognitive function it explores. We applied this framework to a sample of patients with focal brain damage. Each patient was related to: (i) the cerebral entities injured (assessed with structural neuroimaging data) and (ii) the neusopsychological assessment tests carried out (weight by performance). Our model offers a suitable platform to visualize patients' relevant information, facilitating the representation, standardization and sharing of clinical data. At the same time, the integration of a large number of patients in this framework will make possible to explore relations between anatomy (injured entities) and function (performance in different tests assessing different cognitive functions) and the use of neurocomputational tools for graph analysis may help diagnostic and contribute to the comprehension of neural bases of cognitive functions. Copyright © 2011 Elsevier Ltd. All rights reserved.

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

    Science.gov (United States)

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

    2013-08-15

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

  10. A reproducible brain tumour model established from human glioblastoma biopsies

    Directory of Open Access Journals (Sweden)

    Li Xingang

    2009-12-01

    Full Text Available Abstract Background Establishing clinically relevant animal models of glioblastoma multiforme (GBM remains a challenge, and many commonly used cell line-based models do not recapitulate the invasive growth patterns of patient GBMs. Previously, we have reported the formation of highly invasive tumour xenografts in nude rats from human GBMs. However, implementing tumour models based on primary tissue requires that these models can be sufficiently standardised with consistently high take rates. Methods In this work, we collected data on growth kinetics from a material of 29 biopsies xenografted in nude rats, and characterised this model with an emphasis on neuropathological and radiological features. Results The tumour take rate for xenografted GBM biopsies were 96% and remained close to 100% at subsequent passages in vivo, whereas only one of four lower grade tumours engrafted. Average time from transplantation to the onset of symptoms was 125 days ± 11.5 SEM. Histologically, the primary xenografts recapitulated the invasive features of the parent tumours while endothelial cell proliferations and necrosis were mostly absent. After 4-5 in vivo passages, the tumours became more vascular with necrotic areas, but also appeared more circumscribed. MRI typically revealed changes related to tumour growth, several months prior to the onset of symptoms. Conclusions In vivo passaging of patient GBM biopsies produced tumours representative of the patient tumours, with high take rates and a reproducible disease course. The model provides combinations of angiogenic and invasive phenotypes and represents a good alternative to in vitro propagated cell lines for dissecting mechanisms of brain tumour progression.

  11. Traumatic brain injury–Modeling neuropsychiatric symptoms in rodents

    Directory of Open Access Journals (Sweden)

    Oz eMalkesman

    2013-10-01

    Full Text Available Each year in the United States, approximately 1.5 million people sustain a traumatic brain injury (TBI. Victims of TBI can suffer from chronic post-TBI symptoms, such as sensory and motor deficits, cognitive impairments including problems with memory, learning, and attention, and neuropsychiatric symptoms such as depression, anxiety, irritability, aggression, and suicidal rumination. Although partially associated with the site and severity of injury, the biological mechanisms associated with many of these symptoms—and why some patients experience differing assortments of persistent maladies—are largely unknown. The use of animal models is a promising strategy for elucidation of the mechanisms of impairment and treatment, and learning, memory, sensory and motor tests have widespread utility in rodent models of TBI and psychopharmacology. Comparatively, behavioral tests for the evaluation of neuropsychiatric symptomatology are rarely employed in animal models of TBI and, as determined in this review, the results have been inconsistent. Animal behavioral studies contribute to the understanding of the biological mechanisms by which TBI is associated with neurobehavioral symptoms and offer a powerful means for pre-clinical treatment validation. Therefore, further exploration of the utility of animal behavioral tests for the study of injury mechanisms and therapeutic strategies for the alleviation of emotional symptoms are relevant and essential.

  12. Local Model of Arteriovenous Malformation of the Human Brain

    International Nuclear Information System (INIS)

    Telegina, Nadezhda; Chupakhin, Aleksandr; Cherevko, Aleksandr

    2013-01-01

    Vascular diseases of the human brain are one of the reasons of deaths and people's incapacitation not only in Russia, but also in the world. The danger of an arteriovenous malformation (AVM) is in premature rupture of pathological vessels of an AVM which may cause haemorrhage. Long-term prognosis without surgical treatment is unfavorable. The reduced impact method of AVM treatment is embolization of a malformation which often results in complete obliteration of an AVM. Pre-surgical mathematical modeling of an arteriovenous malformation can help surgeons with an optimal sequence of the operation. During investigations, the simple mathematical model of arteriovenous malformation is developed and calculated, and stationary and non-stationary processes of its embolization are considered. Various sequences of embolization of a malformation are also considered. Calculations were done with approximate steady flow on the basis of balanced equations derived from conservation laws. Depending on pressure difference, a fistula-type AVM should be embolized at first, and then small racemose AVMs are embolized. Obtained results are in good correspondence with neurosurgical AVM practice.

  13. A Comparative Study of Theoretical Graph Models for Characterizing Structural Networks of Human Brain

    Directory of Open Access Journals (Sweden)

    Xiaojin Li

    2013-01-01

    Full Text Available 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.

  14. Brain hubs in lesion models: Predicting functional network topology with lesion patterns in patients.

    Science.gov (United States)

    Yuan, Binke; Fang, Yuxing; Han, Zaizhu; Song, Luping; He, Yong; Bi, Yanchao

    2017-12-20

    Various important topological properties of healthy brain connectome have recently been identified. However, the manner in which brain lesion changes the functional network topology is unknown. We examined how critical specific brain areas are in the maintenance of network topology using multivariate support vector regression analysis on brain structural and resting-state functional imaging data in 96 patients with brain damages. Patients' cortical lesion distribution patterns could significantly predict the functional network topology and a set of regions with significant weights in the prediction models were identified as "lesion hubs". Intriguingly, we found two different types of lesion hubs, whose lesions associated with changes of network topology towards relatively different directions, being either more integrated (global) or more segregated (local), and correspond to hubs identified in healthy functional network in complex manners. Our results pose further important questions about the potential dynamics of the functional brain network after brain damage.

  15. Stroke and Drug Delivery--In Vitro Models of the Ischemic Blood-Brain Barrier

    DEFF Research Database (Denmark)

    Tornabene, Erica; Brodin, Birger

    2016-01-01

    Stroke is a major cause of death and disability worldwide. Both cerebral hypoperfusion and focal cerebral infarcts are caused by a reduction of blood flow to the brain, leading to stroke and subsequent brain damage. At present, only few medical treatments of stroke are available, with the Food...... and Drug Administration-approved tissue plasminogen activator for treatment of acute ischemic stroke being the most prominent example. A large number of potential drug candidates for treatment of ischemic brain tissue have been developed and subsequently failed in clinical trials. A deeper understanding...... of permeation pathways across the barrier in ischemic and postischemic brain endothelium is important for development of new medical treatments. The blood-brain barrier, that is, the endothelial monolayer lining the brain capillaries, changes properties during an ischemic event. In vitro models of the blood-brain...

  16. A physical multifield model predicts the development of volume and structure in the human brain

    Science.gov (United States)

    Rooij, Rijk de; Kuhl, Ellen

    2018-03-01

    The prenatal development of the human brain is characterized by a rapid increase in brain volume and a development of a highly folded cortex. At the cellular level, these events are enabled by symmetric and asymmetric cell division in the ventricular regions of the brain followed by an outwards cell migration towards the peripheral regions. The role of mechanics during brain development has been suggested and acknowledged in past decades, but remains insufficiently understood. Here we propose a mechanistic model that couples cell division, cell migration, and brain volume growth to accurately model the developing brain between weeks 10 and 29 of gestation. Our model accurately predicts a 160-fold volume increase from 1.5 cm3 at week 10 to 235 cm3 at week 29 of gestation. In agreement with human brain development, the cortex begins to form around week 22 and accounts for about 30% of the total brain volume at week 29. Our results show that cell division and coupling between cell density and volume growth are essential to accurately model brain volume development, whereas cell migration and diffusion contribute mainly to the development of the cortex. We demonstrate that complex folding patterns, including sinusoidal folds and creases, emerge naturally as the cortex develops, even for low stiffness contrasts between the cortex and subcortex.

  17. Permeability of PEGylated immunoarsonoliposomes through in vitro blood brain barrier-medulloblastoma co-culture models for brain tumor therapy.

    Science.gov (United States)

    Al-Shehri, Abdulghani; Favretto, Marco E; Ioannou, Panayiotis V; Romero, Ignacio A; Couraud, Pierre-Olivier; Weksler, Babette Barbash; Parker, Terry L; Kallinteri, Paraskevi

    2015-03-01

    Owing to restricted access of pharmacological agents into the brain due to blood brain barrier (BBB) there is a need: 1. to develop a more representative 3-D-co-culture model of tumor-BBB interaction to investigate drug and nanoparticle transport into the brain for diagnostic and therapeutic evaluation. 2. to address the lack of new alternative methods to animal testing according to replacement-reduction-refinement principles. In this work, in vitro BBB-medulloblastoma 3-D-co-culture models were established using immortalized human primary brain endothelial cells (hCMEC/D3). hCMEC/D3 cells were cultured in presence and in absence of two human medulloblastoma cell lines on Transwell membranes. In vitro models were characterized for BBB formation, zonula occludens-1 expression and permeability to dextran. Transferrin receptors (Tfr) expressed on hCMEC/D3 were exploited to facilitate arsonoliposome (ARL) permeability through the BBB to the tumor by covalently attaching an antibody specific to human Tfr. The effect of anticancer ARLs on hCMEC/D3 was assessed. In vitro BBB and BBB-tumor co-culture models were established successfully. BBB permeability was affected by the presence of tumor aggregates as suggested by increased permeability of ARLs. There was a 6-fold and 8-fold increase in anti-Tfr-ARL uptake into VC312R and BBB-DAOY co-culture models, respectively, compared to plain ARLs. The three-dimensional models might be appropriate models to study the transport of various drugs and nanocarriers (liposomes and immunoarsonoliposomes) through the healthy and diseased BBB. The immunoarsonoliposomes can be potentially used as anticancer agents due to good tolerance of the in vitro BBB model to their toxic effect.

  18. Approaches to Modelling the Dynamical Activity of Brain Function Based on the Electroencephalogram

    Science.gov (United States)

    Liley, David T. J.; Frascoli, Federico

    The brain is arguably the quintessential complex system as indicated by the patterns of behaviour it produces. Despite many decades of concentrated research efforts, we remain largely ignorant regarding the essential processes that regulate and define its function. While advances in functional neuroimaging have provided welcome windows into the coarse organisation of the neuronal networks that underlie a range of cognitive functions, they have largely ignored the fact that behaviour, and by inference brain function, unfolds dynamically. Modelling the brain's dynamics is therefore a critical step towards understanding the underlying mechanisms of its functioning. To date, models have concentrated on describing the sequential organisation of either abstract mental states (functionalism, hard AI) or the objectively measurable manifestations of the brain's ongoing activity (rCBF, EEG, MEG). While the former types of modelling approach may seem to better characterise brain function, they do so at the expense of not making a definite connection with the actual physical brain. Of the latter, only models of the EEG (or MEG) offer a temporal resolution well matched to the anticipated temporal scales of brain (mental processes) function. This chapter will outline the most pertinent of these modelling approaches, and illustrate, using the electrocortical model of Liley et al, how the detailed application of the methods of nonlinear dynamics and bifurcation theory is central to exploring and characterising their various dynamical features. The rich repertoire of dynamics revealed by such dynamical systems approaches arguably represents a critical step towards an understanding of the complexity of brain function.

  19. Effect of pharmacologic resuscitation on the brain gene expression profiles in a swine model of traumatic brain injury and hemorrhage

    DEFF Research Database (Denmark)

    Dekker, Simone E; Bambakidis, Ted; Sillesen, Martin

    2014-01-01

    BACKGROUND: We have previously shown that addition of valproic acid (VPA; a histone deacetylase inhibitor) to hetastarch (Hextend [HEX]) resuscitation significantly decreases lesion size in a swine model of traumatic brain injury (TBI) and hemorrhagic shock (HS). However, the precise mechanisms...... have not been well defined. As VPA is a transcriptional modulator, the aim of this study was to investigate its effect on brain gene expression profiles. METHODS: Swine were subjected to controlled TBI and HS (40% blood volume), kept in shock for 2 hours, and resuscitated with HEX or HEX + VPA (n = 5...... per group). Following 6 hours of observation, brain RNA was isolated, and gene expression profiles were measured using a Porcine Gene ST 1.1 microarray (Affymetrix, Santa Clara, CA). Pathway analysis was done using network analysis tools Gene Ontology, Ingenuity Pathway Analysis, and Parametric Gene...

  20. Observation and modeling of deep brain stimulation electrode depth in the pallidal target of the developing brain.

    Science.gov (United States)

    Lumsden, Daniel E; Ashmore, Jonathan; Charles-Edwards, Geoffrey; Selway, Richard; Lin, Jean-Pierre; Ashkan, Keyoumars

    2015-04-01

    It is unclear how brain growth with age affects electrode position in relation to target for children undergoing deep brain stimulation surgery. We aimed to model projected change in the distance between the entry point of the electrode into the brain and target during growth to adulthood. Modeling was performed using a neurodevelopmental magnetic resonance imaging database of age-specific templates in 6-month increments from 4 to 18 years of age. Coordinates were chosen for a set of entry points into both cerebral hemispheres and target positions within the globus pallidus internus on the youngest magnetic resonance imaging template. The youngest template was nonlinearly registered to the older templates, and the transformations generated by these registrations were applied to the original coordinates of entry and target positions, mapping these positions with increasing age. Euclidean geometry was used to calculate the distance between projected electrode entry and target with increasing age. A projected increase in distance between entry point and target of 5-10 mm was found from age 4 to 18 years. Most change appeared to occur before 7 years of age, after which minimal change in distance was found. Electrodes inserted during deep brain stimulation surgery are tethered at the point of entry to the skull. Brain growth, which could result in a relative retraction with respect to the original target position, appears to occur before 7 years of age, suggesting careful monitoring is needed for children undergoing implantation before this age. Reengineering of electrode design could avoid reimplantation surgery in young children undergoing deep brain stimulation. Copyright © 2015 Elsevier Inc. All rights reserved.

  1. Material properties of the brain in injury-relevant conditions - Experiments and computational modeling.

    Science.gov (United States)

    Zhao, Wei; Choate, Bryan; Ji, Songbai

    2018-04-01

    Material properties of the brain have been extensively studied but remain poorly characterized. The vast variations in constitutive models and material constants are well documented. However, no study exists to translate the variations into disparities in impact-induced brain strains most relevant to brain injury. Here, we reviewed a subset of injury-relevant brain material properties either characterized in experiments or adopted in recent head injury models. To highlight how variations in measured brain material properties manifested in simulated brain strains, we selected six experiments that have provided a complete set of brain material model and constants to implement a common head injury model. Responses resulting from two extreme events representing a high-rate cadaveric head impact and a low-rate in vivo head rotation, respectively, varied substantially. We hypothesized, and further confirmed, that the time-varying shear moduli at the appropriate time scales (e.g., ~5 ms and ~40 ms corresponding to the impulse durations of the major acceleration peaks for the two impacts, respectively), rather than the initial or long-term shear moduli, were the most indicative of impact-induced brain strains. These results underscored the need to implement measured brain material properties into an actual head injury model for evaluation. They may also provide guidelines to better characterize brain material properties in future experiments and head injury models. Finally, our finding provided a practical solution to satisfy head injury model validation requirements at both ends of the impact severity spectrum. This would improve the confidence in model simulation performance across a range of time scales relevant to concussion and sub-concussion in the real-world. Copyright © 2018 Elsevier Ltd. All rights reserved.

  2. Bridging the Gap of Standardized Animals Models for Blast Neurotrauma: Methodology for Appropriate Experimental Testing.

    Science.gov (United States)

    VandeVord, Pamela J; Leonardi, Alessandra Dal Cengio; Ritzel, David

    2016-01-01

    Recent military combat has heightened awareness to the complexity of blast-related traumatic brain injuries (bTBI). Experiments using animal, cadaver, or biofidelic physical models remain the primary measures to investigate injury biomechanics as well as validate computational simulations, medical diagnostics and therapies, or protection technologies. However, blast injury research has seen a range of irregular and inconsistent experimental methods for simulating blast insults generating results which may be misleading, cannot be cross-correlated between laboratories, or referenced to any standard for exposure. Both the US Army Medical Research and Materiel Command and the National Institutes of Health have noted that there is a lack of standardized preclinical models of TBI. It is recommended that the blast injury research community converge on a consistent set of experimental procedures and reporting of blast test conditions. This chapter describes the blast conditions which can be recreated within a laboratory setting and methodology for testing in vivo models within the appropriate environment.

  3. Revisiting hydrocephalus as a model to study brain resilience.

    Directory of Open Access Journals (Sweden)

    Matheus Fernandes De Oliveira

    2012-01-01

    Full Text Available Hydrocephalus is an entity which embraces a variety of diseases whose final result is the enlarged size of cerebral ventricular system, partially or completely. The physiopathology of hydrocephalus lies in the dynamics of circulation of cerebrospinal fluid (CSF. The consequent CSF stasis in hydrocephalus interferes with cerebral and ventricular system development. Children and adults who sustain congenital or acquired brain injury typically experience a diffuse insult that impacts many areas of the brain. Development and recovery after such injuries reflects both restoration and reorganization of cognitive functions. Classic examples were already reported in literature. This suggests the presence of biological mechanisms associated with resilient adaptation of brain networks. We will settle a link between the notable modifications to neurophysiology secondary to hydrocephalus and the ability of neuronal tissue to reassume and reorganize its functions.Key words: hydrocephalus; resilience; brain; neural networks; plasticity.

  4. Mild traumatic brain injury: Graph-model characterization of brain networks for episodic memory

    NARCIS (Netherlands)

    Tsirka, V.; Simos, P.G.; Vakis, A.; Kanatsouli, K.; Vourkas, M.; Erimaki, S.; Pachou, E.; Stam, C.J.; Micheloyannis, S.

    2011-01-01

    Episodic memory is among the cognitive functions that can be affected in the acute phase following mild traumatic brain injury (MTBI). The present study used EEG recordings to evaluate global synchronization and network organization of rhythmic activity during the encoding and recognition phases of

  5. Modeling the effects of noninvasive transcranial brain stimulation at the biophysical, network, and cognitive Level

    DEFF Research Database (Denmark)

    Hartwigsen, Gesa; Bergmann, Til Ole; Herz, Damian Marc

    2015-01-01

    Noninvasive transcranial brain stimulation (NTBS) is widely used to elucidate the contribution of different brain regions to various cognitive functions. Here we present three modeling approaches that are informed by functional or structural brain mapping or behavior profiling and discuss how...... these approaches advance the scientific potential of NTBS as an interventional tool in cognitive neuroscience. (i) Leveraging the anatomical information provided by structural imaging, the electric field distribution in the brain can be modeled and simulated. Biophysical modeling approaches generate testable...... predictions regarding the impact of interindividual variations in cortical anatomy on the injected electric fields or the influence of the orientation of current flow on the physiological stimulation effects. (ii) Functional brain mapping of the spatiotemporal neural dynamics during cognitive tasks can...

  6. Allostasis and the Human Brain: Integrating Models of Stress from the Social and Life Sciences

    Science.gov (United States)

    Ganzel, Barbara L.; Morris, Pamela A.; Wethington, Elaine

    2010-01-01

    We draw on the theory of allostasis to develop an integrative model of the current stress process that highlights the brain as a dynamically adapting interface between the changing environment and the biological self. We review evidence that the core emotional regions of the brain constitute the primary mediator of the well-established association…

  7. Paving the way towards complex blood-brain barrier models using pluripotent stem cells

    DEFF Research Database (Denmark)

    Lauschke, Karin; Frederiksen, Lise; Hall, Vanessa Jane

    2017-01-01

    to the unique tightness and selective permeability of the BBB and has been shown to be disrupted in many diseases and brain disorders, such as, vascular dementia, stroke, multiple sclerosis and Alzheimer's disease. Given the progress that pluripotent stem cells (PSCs) have made in the last two decades......A tissue with great need to be modelled in vitro is the blood-brain barrier (BBB). The BBB is a tight barrier that covers all blood vessels in the brain and separates the brain microenvironment from the blood system. It consists of three cell types (neurovascular unit (NVU)) that contribute...

  8. Deep Neural Networks: A New Framework for Modeling Biological Vision and Brain Information Processing.

    Science.gov (United States)

    Kriegeskorte, Nikolaus

    2015-11-24

    Recent advances in neural network modeling have enabled major strides in computer vision and other artificial intelligence applications. Human-level visual recognition abilities are coming within reach of artificial systems. Artificial neural networks are inspired by the brain, and their computations could be implemented in biological neurons. Convolutional feedforward networks, which now dominate computer vision, take further inspiration from the architecture of the primate visual hierarchy. However, the current models are designed with engineering goals, not to model brain computations. Nevertheless, initial studies comparing internal representations between these models and primate brains find surprisingly similar representational spaces. With human-level performance no longer out of reach, we are entering an exciting new era, in which we will be able to build biologically faithful feedforward and recurrent computational models of how biological brains perform high-level feats of intelligence, including vision.

  9. An improved in vitro blood-brain barrier model: rat brain endothelial cells co-cultured with astrocytes.

    Science.gov (United States)

    Abbott, N Joan; Dolman, Diana E M; Drndarski, Svetlana; Fredriksson, Sarah M

    2012-01-01

    In vitro blood-brain barrier (BBB) models using primary cultured brain endothelial cells are important for establishing cellular and molecular mechanisms of BBB function. Co-culturing with BBB-associated cells especially astrocytes to mimic more closely the in vivo condition leads to upregulation of the BBB phenotype in the brain endothelial cells. Rat brain endothelial cells (RBECs) are a valuable tool allowing ready comparison with in vivo studies in rodents; however, it has been difficult to obtain pure brain endothelial cells, and few models achieve a transendothelial electrical resistance (TEER, measure of tight junction efficacy) of >200 Ω cm(2), i.e. the models are still relatively leaky. Here, we describe methods for preparing high purity RBECs and neonatal rat astrocytes, and a co-culture method that generates a robust, stable BBB model that can achieve TEER >600 Ω cm(2). The method is based on >20 years experience with RBEC culture, together with recent improvements to kill contaminating cells and encourage BBB differentiation.Astrocytes are isolated by mechanical dissection and cell straining and are frozen for later co-culture. RBECs are isolated from 3-month-old rat cortices. The brains are cleaned of meninges and white matter and enzymatically and mechanically dissociated. Thereafter, the tissue homogenate is centrifuged in bovine serum albumin to separate vessel fragments from other cells that stick to the myelin plug. The vessel fragments undergo a second enzyme digestion to separate pericytes from vessels and break down vessels into shorter segments, after which a Percoll gradient is used to separate capillaries from venules, arterioles, and single cells. To kill remaining contaminating cells such as pericytes, the capillary fragments are plated in puromycin-containing medium and RBECs grown to 50-60% confluence. They are then passaged onto filters for co-culture with astrocytes grown in the bottom of the wells. The whole procedure takes ∼2

  10. Integrating Traumatic Brain Injury Model Systems Data into the Federal Interagency Traumatic Brain Injury Research Informatics Systems

    Science.gov (United States)

    2016-10-01

    Research Informatics Systems PRINCIPAL INVESTIGATOR: Cynthia Harrison-Felix, PhD CONTRACTING ORGANIZATION: Craig Hospital Englewood, CO 80113...Traumatic Brain Injury Research Informatics Systems 5a. CONTRACT NUMBER 5b. GRANT NUMBER W81XWH-14-1-0564 5c. PROGRAM ELEMENT NUMBER 6. AUTHOR(S...Research (FITBIR) Informatics System. Local IRB approval and HRPO approval has been obtained for the TBI Model System (TBIMS) National Data and

  11. Gut-brain and brain-gut axis in Parkinson's disease models: Effects of a uridine and fish oil diet.

    Science.gov (United States)

    Perez-Pardo, Paula; Dodiya, Hemraj B; Broersen, Laus M; Douna, Hidde; van Wijk, Nick; Lopes da Silva, Sofia; Garssen, Johan; Keshavarzian, Ali; Kraneveld, Aletta D

    2017-03-09

    Recent investigations have focused on the potential role of gastrointestinal (GI) abnormalities in the pathogenesis of Parkinson's disease (PD). The 'dual-hit' hypothesis of PD speculates that a putative pathogen enters the brain via two routes: the olfactory system and the GI system. Here, we investigated (1) whether local exposures of the neurotoxin rotenone in the gut or the brain of mice could induce PD-like neurological and GI phenotypes as well as a characteristic neuropathology in accordance with this 'dual-hit hypothesis' and (2) the effects of a diet containing uridine and fish oil providing docosahexaenoic acid (DHA), in both models. Mice were given rotenone either orally or by an injection in the striatum. Dietary interventions were started 1 week before rotenone exposures. We found that (1) both oral and intrastriatal administration of rotenone induced similar PD-like motor deficits, dopaminergic cell loss, delayed intestinal transit, inflammation, and alpha-synuclein accumulation in the colon; (2) the uridine and DHA containing diet prevented rotenone-induced motor and GI dysfunctions in both models. The models suggest possible bidirectional communication between the gut and the brain for the genesis of PD-like phenotype and pathology. The dietary intervention may provide benefits in the prevention of motor and non-motor symptoms in PD.

  12. Standing and travelling waves in a spherical brain model: The Nunez model revisited

    Science.gov (United States)

    Visser, S.; Nicks, R.; Faugeras, O.; Coombes, S.

    2017-06-01

    The Nunez model for the generation of electroencephalogram (EEG) signals is naturally described as a neural field model on a sphere with space-dependent delays. For simplicity, dynamical realisations of this model either as a damped wave equation or an integro-differential equation, have typically been studied in idealised one dimensional or planar settings. Here we revisit the original Nunez model to specifically address the role of spherical topology on spatio-temporal pattern generation. We do this using a mixture of Turing instability analysis, symmetric bifurcation theory, centre manifold reduction and direct simulations with a bespoke numerical scheme. In particular we examine standing and travelling wave solutions using normal form computation of primary and secondary bifurcations from a steady state. Interestingly, we observe spatio-temporal patterns which have counterparts seen in the EEG patterns of both epileptic and schizophrenic brain conditions.

  13. Decreased integration and information capacity in stroke measured by whole brain models of resting state activity.

    Science.gov (United States)

    Adhikari, Mohit H; Hacker, Carl D; Siegel, Josh S; Griffa, Alessandra; Hagmann, Patric; Deco, Gustavo; Corbetta, Maurizio

    2017-04-01

    While several studies have shown that focal lesions affect the communication between structurally normal regions of the brain, and that these changes may correlate with behavioural deficits, their impact on brain's information processing capacity is currently unknown. Here we test the hypothesis that focal lesions decrease the brain's information processing capacity, of which changes in functional connectivity may be a measurable correlate. To measure processing capacity, we turned to whole brain computational modelling to estimate the integration and segregation of information in brain networks. First, we measured functional connectivity between different brain areas with resting state functional magnetic resonance imaging in healthy subjects (n = 26), and subjects who had suffered a cortical stroke (n = 36). We then used a whole-brain network model that coupled average excitatory activities of local regions via anatomical connectivity. Model parameters were optimized in each healthy or stroke participant to maximize correlation between model and empirical functional connectivity, so that the model's effective connectivity was a veridical representation of healthy or lesioned brain networks. Subsequently, we calculated two model-based measures: 'integration', a graph theoretical measure obtained from functional connectivity, which measures the connectedness of brain networks, and 'information capacity', an information theoretical measure that cannot be obtained empirically, representative of the segregative ability of brain networks to encode distinct stimuli. We found that both measures were decreased in stroke patients, as compared to healthy controls, particularly at the level of resting-state networks. Furthermore, we found that these measures, especially information capacity, correlate with measures of behavioural impairment and the segregation of resting-state networks empirically measured. This study shows that focal lesions affect the brain's ability to

  14. Novel brain arteriovenous malformation mouse models for type 1 hereditary hemorrhagic telangiectasia.

    Directory of Open Access Journals (Sweden)

    Eun-Jung Choi

    Full Text Available Endoglin (ENG is a causative gene of type 1 hereditary hemorrhagic telangiectasia (HHT1. HHT1 patients have a higher prevalence of brain arteriovenous malformation (AVM than the general population and patients with other HHT subtypes. The pathogenesis of brain AVM in HHT1 patients is currently unknown and no specific medical therapy is available to treat patients. Proper animal models are crucial for identifying the underlying mechanisms for brain AVM development and for testing new therapies. However, creating HHT1 brain AVM models has been quite challenging because of difficulties related to deleting Eng-floxed sequence in Eng(2fl/2fl mice. To create an HHT1 brain AVM mouse model, we used several Cre transgenic mouse lines to delete Eng in different cell-types in Eng(2fl/2fl mice: R26CreER (all cell types after tamoxifen treatment, SM22α-Cre (smooth muscle and endothelial cell and LysM-Cre (lysozyme M-positive macrophage. An adeno-associated viral vector expressing vascular endothelial growth factor (AAV-VEGF was injected into the brain to induce focal angiogenesis. We found that SM22α-Cre-mediated Eng deletion in the embryo caused AVMs in the postnatal brain, spinal cord, and intestines. Induction of Eng deletion in adult mice using R26CreER plus local VEGF stimulation induced the brain AVM phenotype. In both models, Eng-null endothelial cells were detected in the brain AVM lesions, and formed mosaicism with wildtype endothelial cells. However, LysM-Cre-mediated Eng deletion in the embryo did not cause AVM in the postnatal brain even after VEGF stimulation. In this study, we report two novel HHT1 brain AVM models that mimic many phenotypes of human brain AVM and can thus be used for studying brain AVM pathogenesis and testing new therapies. Further, our data indicate that macrophage Eng deletion is insufficient and that endothelial Eng homozygous deletion is required for HHT1 brain AVM development.

  15. Life-time and hierarchy of memory in the dissipative quantum model of brain

    OpenAIRE

    Alfinito, Eleonora; Vitiello, Giuseppe

    1999-01-01

    Some recent developments of the dissipative quantum model of brain are reported. In particular, the time-dependent frequency case is considered with its implications on the different life-times of the collective modes.

  16. Technical pitfalls in a porcine brain retraction model. The impact of brain spatula on the retracted brain tissue in a porcine model: a feasibility study and its technical pitfalls

    International Nuclear Information System (INIS)

    Thiex, R.; Hans, F.J.; Gilsbach, J.M.; Krings, T.; Sellhaus, B.

    2005-01-01

    We describe technical pitfalls of a porcine brain injury model for identifying primary and secondary pathological sequelae following brain retraction by brain spatula. In 16 anaesthetised male pigs, the right frontal brain was retracted in the interhemispheric fissure by a brain spatulum with varying pressures applied by the gravitational force of weights from 10 to 70 g for a duration of 30 min. The retracted brain tissue was monitored for changes in intracranial pressure and perfusion of the cortex using a Laser Doppler Perfusion Imager (MoorLDI). To evaluate the extent of oedema and cortical contusions, MRI was performed 30 min and 72 h after brain retraction. Following the MR scan, the retracted brain areas were histopathologically assessed using H and E and Fluoro-Jade B staining for neuronal damage. Sinus occlusion occurred in four animals, resulting in bilateral cortical contusions and extensive brain oedema. Retracting the brain with weights of 70 g (n=4) caused extensive oedema on FLAIR images that correlated clinically with a hemiparesis in three animals. Morphologically, an increased number of Fluoro-Jade B-positive neurons were found. A sequential decrease in weights prevented functional deficits in animals. A retraction pressure applied by 10-g weights (n=7) caused a mean rise in intracranial pressure to 4.0±3.1 mm Hg, and a decrement in mean cortical perfusion from 740.8±41.5 to 693.8±72.4 PU/cm2, (P<0.24). A meticulous dissection of the interhemispheric fissure and a reduction of weights to 10 g were found to be mandatory to study the cortical impact caused by brain spatula reproducibly. (orig.)

  17. Creating rat model for hypoxic brain damage in neonates by oxygen deprivation.

    Science.gov (United States)

    Zhang, Qiaoli; Ding, Yingxue; Yao, Yanqing; Yu, Yang; Yang, Lijun; Cui, Hong

    2013-01-01

    Current study explores the feasibility of using a non-surgical method of oxygen deprivation to create Hypoxic brain damage in neonatal rats for medical studies. 7-day-old Sprague Dowley (SD) rats were kept in a container with low oxygen level (8%) for 1.5h. A second group had bilateral cephalic artery ligation before the 1.5h-low oxygen treatment, a method similar to the popular Rice method, to expose the brain to both hypoxic and ischemic situations. Short term neural functions and brain water weights were evaluated 1 day after the hypoxic treatment. Brain pathology and histology were also examined at 1 day and 3 days after the hypoxic treatment. Both groups showed impaired neural functions and increased brain water weight compared to the controls. Histology studies also revealed injuries in the subcortex, hippocampus and lateral ventricle in the brains from both groups. There is no significant difference in the degree of brain damages observed in the two groups. Our work demonstrated that oxygen deprivation alone is sufficient to cause brain damages similar to those seen in Hypoxic-ischemic brain disease (HIBD). Because this method avoids the invasive surgical procedure and therefore reduces the stress and mortality of laboratory animals during the experiment, we recommend it to be the favorable method for creating rat models for HIBD studies.

  18. Creating rat model for hypoxic brain damage in neonates by oxygen deprivation.

    Directory of Open Access Journals (Sweden)

    Qiaoli Zhang

    Full Text Available Current study explores the feasibility of using a non-surgical method of oxygen deprivation to create Hypoxic brain damage in neonatal rats for medical studies. 7-day-old Sprague Dowley (SD rats were kept in a container with low oxygen level (8% for 1.5h. A second group had bilateral cephalic artery ligation before the 1.5h-low oxygen treatment, a method similar to the popular Rice method, to expose the brain to both hypoxic and ischemic situations. Short term neural functions and brain water weights were evaluated 1 day after the hypoxic treatment. Brain pathology and histology were also examined at 1 day and 3 days after the hypoxic treatment. Both groups showed impaired neural functions and increased brain water weight compared to the controls. Histology studies also revealed injuries in the subcortex, hippocampus and lateral ventricle in the brains from both groups. There is no significant difference in the degree of brain damages observed in the two groups. Our work demonstrated that oxygen deprivation alone is sufficient to cause brain damages similar to those seen in Hypoxic-ischemic brain disease (HIBD. Because this method avoids the invasive surgical procedure and therefore reduces the stress and mortality of laboratory animals during the experiment, we recommend it to be the favorable method for creating rat models for HIBD studies.

  19. Brain temperature profiles during epidural cooling with the ChillerPad in a monkey model of traumatic brain injury.

    Science.gov (United States)

    King, Christopher; Robinson, Timothy; Dixon, C Edward; Rao, Gutti R; Larnard, Donald; Nemoto, C Edwin M

    2010-10-01

    Therapeutic hypothermia remains a promising treatment for patients with severe traumatic brain injury (TBI). Multiple animal studies have suggested that hypothermia is neuroprotective after TBI, but clinical trials have been inconclusive. Systemic hypothermia, the method used in almost all major clinical trials, is limited by the time to target temperature, the depth of hypothermia, and complications, problems that may be solved by selective brain cooling. We evaluated the effects on brain temperature of a cooling device called the ChillerPad,™ which is applied to the dura in a non-human primate TBI model using controlled cortical impact (CCI). The cortical surface was rapidly cooled to approximately 15°C and maintained at that level for 24 h, followed by rewarming over about 10 h. Brain temperatures fell to 34-35°C at a depth of 15 mm at the cortical gray/white matter interface, and to 28-32°C at 10 mm deep. Intracranial pressure was mildly elevated (8-12 mm Hg) after cooling and rewarming, likely due to TBI. Other physiological variables were unchanged. Cooling was rapidly diminished at points distant from the cooling pad. The ChillerPad may be useful for highly localized cooling of the brain in circumstances in which a craniotomy is clinically indicated. However, because of the delay required by the craniotomy, other methods that are more readily available for inducing hypothermia may be used as a bridge between the time of injury to placement of the ChillerPad.

  20. Optically enhanced blood-brain-barrier crossing of plasmonic-active nanoparticles in preclinical brain tumor animal models

    Science.gov (United States)

    Yuan, Hsiangkuo; Wilson, Christy M.; Li, Shuqin; Fales, Andrew M.; Liu, Yang; Grant, Gerald; Vo-Dinh, Tuan

    2014-02-01

    Nanotechnology provides tremendous biomedical opportunities for cancer diagnosis, imaging, and therapy. In contrast to conventional chemotherapeutic agents where their actual target delivery cannot be easily imaged, integrating imaging and therapeutic properties into one platform facilitates the understanding of pharmacokinetic profiles, and enables monitoring of the therapeutic process in each individual. Such a concept dubbed "theranostics" potentiates translational research and improves precision medicine. One particular challenging application of theranostics involves imaging and controlled delivery of nanoplatforms across blood-brain-barrier (BBB) into brain tissues. Typically, the BBB hinders paracellular flux of drug molecules into brain parenchyma. BBB disrupting agents (e.g. mannitol, focused ultrasound), however, suffer from poor spatial confinement. It has been a challenge to design a nanoplatform not only acts as a contrast agent but also improves the BBB permeation. In this study, we demonstrated the feasibility of plasmonic gold nanoparticles as both high-resolution optical contrast agent and focalized tumor BBB permeation-inducing agent. We specifically examined the microscopic distribution of nanoparticles in tumor brain animal models. We observed that most nanoparticles accumulated at the tumor periphery or perivascular spaces. Nanoparticles were present in both endothelial cells and interstitial matrices. This study also demonstrated a novel photothermal-induced BBB permeation. Fine-tuning the irradiating energy induced gentle disruption of the vascular integrity, causing short-term extravasation of nanomaterials but without hemorrhage. We conclude that our gold nanoparticles are a powerful biocompatible contrast agent capable of inducing focal BBB permeation, and therefore envision a strong potential of plasmonic gold nanoparticle in future brain tumor imaging and therapy.

  1. Mathematical model in post-mortem estimation of brain edema using morphometric parameters.

    Science.gov (United States)

    Radojevic, Nemanja; Radnic, Bojana; Vucinic, Jelena; Cukic, Dragana; Lazovic, Ranko; Asanin, Bogdan; Savic, Slobodan

    2017-01-01

    Current autopsy principles for evaluating the existence of brain edema are based on a macroscopic subjective assessment performed by pathologists. The gold standard is a time-consuming histological verification of the presence of the edema. By measuring the diameters of the cranial cavity, as individually determined morphometric parameters, a mathematical model for rapid evaluation of brain edema was created, based on the brain weight measured during the autopsy. A cohort study was performed on 110 subjects, divided into two groups according to the histological presence or absence of (the - deleted from the text) brain edema. In all subjects, the following measures were determined: the volume and the diameters of the cranial cavity (longitudinal and transverse distance and height), the brain volume, and the brain weight. The complex mathematical algorithm revealed a formula for the coefficient ε, which is useful to conclude whether a brain edema is present or not. The average density of non-edematous brain is 0.967 g/ml, while the average density of edematous brain is 1.148 g/ml. The resulting formula for the coefficient ε is (5.79 x longitudinal distance x transverse distance)/brain weight. Coefficient ε can be calculated using measurements of the diameters of the cranial cavity and the brain weight, performed during the autopsy. If the resulting ε is less than 0.9484, it could be stated that there is cerebral edema with a reliability of 98.5%. The method discussed in this paper aims to eliminate the burden of relying on subjective assessments when determining the presence of a brain edema. Copyright © 2016 Elsevier Ltd and Faculty of Forensic and Legal Medicine. All rights reserved.

  2. Biomarkers of Blast-Induced Neurotrauma: Profiling Molecular and Cellular Mechanisms of Blast Brain Injury

    Science.gov (United States)

    2009-06-01

    common locations are the corticome- dullary (gray matter-white matter) junction (particularly in the frontal and temporal areas), the internal capsule ...Vascular responses and dysregulation of cell adhesion molecules as bridges connecting vascular-endothelial- neural tissue disturbances, including but not...3371–3376. Lew, H.L. (2005). Rehabilitation needs of an increasing popula- tion of patients: Traumatic brain injury, polytrauma, and blast-related

  3. Investigation of Brain Arterial Circle Malformations Using Electrical Modelling and Simulation

    Directory of Open Access Journals (Sweden)

    Klara Capova

    2006-01-01

    Full Text Available The paper deals with the cerebral arterial system investigation by means of electrical modelling and simulations. The main attention is paid to the brain arterial circle malformations (stenoses and aneurysms and their determination and evaluation by computer-aided methods as tools of a non-invasive diagnostics. The compensation possibilities of brain arterial circle in case of presence of concrete arterial malformations are modelled and simulated. The simulation results of brain arteries blood pressures and volume flow velocities time dependences are presented and discussed under various health conditions.

  4. High Intensity Focused Ultrasound: A Novel Model of Mild Traumatic Brain Injury

    Science.gov (United States)

    2013-11-07

    Berry A, Capone F, Giorgio M, Pelicci P, de Kloet E, et al . 2007. Deletion of the life span determinant p66Shc prevents age-dependent increases in...in humans. Limitations to animal research must be recognized as well. Shanks et al (78) argue that animal models are not predictive of responses in...brain injury in animals to model mild traumatic brain injuries (mTBI) in humans. Wahab et al (95) reported that HIFU can impair neural axonal

  5. Growth Mixture Modeling of Depression Symptoms Following Traumatic Brain Injury

    Directory of Open Access Journals (Sweden)

    Rapson Gomez

    2017-08-01

    Full Text Available Growth Mixture Modeling (GMM was used to investigate the longitudinal trajectory of groups (classes of depression symptoms, and how these groups were predicted by the covariates of age, sex, severity, and length of hospitalization following Traumatic Brain Injury (TBI in a group of 1074 individuals (696 males, and 378 females from the Royal Hobart Hospital, who sustained a TBI. The study began in late December 2003 and recruitment continued until early 2007. Ages ranged from 14 to 90 years, with a mean of 35.96 years (SD = 16.61. The study also examined the associations between the groups and causes of TBI. Symptoms of depression were assessed using the Hospital Anxiety and Depression Scale within 3 weeks of injury, and at 1, 3, 6, 12, and 24 months post-injury. The results revealed three groups: low, high, and delayed depression. In the low group depression scores remained below the clinical cut-off at all assessment points during the 24-months post-TBI, and in the high group, depression scores were above the clinical cut-off at all assessment points. The delayed group showed an increase in depression symptoms to 12 months after injury, followed by a return to initial assessment level during the following 12 months. Covariates were found to be differentially associated with the three groups. For example, relative to the low group, the high depression group was associated with more severe TBI, being female, and a shorter period of hospitalization. The delayed group also had a shorter period of hospitalization, were younger, and sustained less severe TBI. Our findings show considerable fluctuation of depression over time, and that a non-clinical level of depression at any one point in time does not necessarily mean that the person will continue to have non-clinical levels in the future. As we used GMM, we were able to show new findings and also bring clarity to contradictory past findings on depression and TBI. Consequently, we recommend the use

  6. Modeling and simulation of deep brain stimulation in Parkinson's disease

    NARCIS (Netherlands)

    Heida, Tjitske; Moroney, R.; Marani, Enrico; Usunoff, K.G.; Pereira, M.; Freire, M.

    2009-01-01

    Deep Brain Stimulation (DBS) is effective in the Parkinsonian state, while it seems to produce rather non-selective stimulation over an unknown volume of tissue. Despite a huge amount of anatomical and physiological data regarding the structure of the basal ganglia (BG) and their connections, the

  7. Embodied modeling of the organization of the brain

    NARCIS (Netherlands)

    Janssen, J.H.; Goosen, A.E.A.; Sprinkhuizen-Kuyper, I.G.; Haselager, W.F.G.

    2007-01-01

    In this study embodied embedded agents are evolved in order to gain a better understanding of aspects of the distribution of cognitive functions in the brain. We found that a symmetrical body plan facilitates the evolution of two hemispheres. Furthermore, individuals with an asymmetrical body plan,

  8. Opioid Abuse after Traumatic Brain Injury: Evaluation Using Rodent Models

    Science.gov (United States)

    2015-09-01

    compulsive buying and the burden perceived by caregivers after moderate-to-severe traumatic brain injury. Psychopathology. 2011;44:158-164. Rochat L...well as the progression from abuse to compulsive drug taking and addiction (Coluzzi and Pappagallo, 2005; Koob and Volkow, 2010). Physical dependence

  9. Opioid Abuse After Traumatic Brain Injury: Evaluation Using Rodet Models

    Science.gov (United States)

    2014-07-01

    impulsivity relates to compulsive buying and the burden perceived by caregivers after moderate-to-severe traumatic brain injury. Psychopathology...mechanism for the continued misuse/abuse of opioid drugs as well as the progression from abuse to compulsive drug taking and addiction (Coluzzi and

  10. Using induced pluripotent stem cells derived neurons to model brain diseases

    Directory of Open Access Journals (Sweden)

    Cindy E McKinney

    2017-01-01

    Full Text Available The ability to use induced pluripotent stem cells (iPSC to model brain diseases is a powerful tool for unraveling mechanistic alterations in these disorders. Rodent models of brain diseases have spurred understanding of pathology but the concern arises that they may not recapitulate the full spectrum of neuron disruptions associated with human neuropathology. iPSC derived neurons, or other neural cell types, provide the ability to access pathology in cells derived directly from a patient's blood sample or skin biopsy where availability of brain tissue is limiting. Thus, utilization of iPSC to study brain diseases provides an unlimited resource for disease modelling but may also be used for drug screening for effective therapies and may potentially be used to regenerate aged or damaged cells in the future. Many brain diseases across the spectrum of neurodevelopment, neurodegenerative and neuropsychiatric are being approached by iPSC models. The goal of an iPSC based disease model is to identify a cellular phenotype that discriminates the disease-bearing cells from the control cells. In this mini-review, the importance of iPSC cell models validated for pluripotency, germline competency and function assessments is discussed. Selected examples for the variety of brain diseases that are being approached by iPSC technology to discover or establish the molecular basis of the neuropathology are discussed.

  11. Brain functional BOLD perturbation modelling for forward fMRI and inverse mapping

    Science.gov (United States)

    Robinson, Jennifer; Calhoun, Vince

    2018-01-01

    Purpose To computationally separate dynamic brain functional BOLD responses from static background in a brain functional activity for forward fMRI signal analysis and inverse mapping. Methods A brain functional activity is represented in terms of magnetic source by a perturbation model: χ = χ0 +δχ, with δχ for BOLD magnetic perturbations and χ0 for background. A brain fMRI experiment produces a timeseries of complex-valued images (T2* images), whereby we extract the BOLD phase signals (denoted by δP) by a complex division. By solving an inverse problem, we reconstruct the BOLD δχ dataset from the δP dataset, and the brain χ distribution from a (unwrapped) T2* phase image. Given a 4D dataset of task BOLD fMRI, we implement brain functional mapping by temporal correlation analysis. Results Through a high-field (7T) and high-resolution (0.5mm in plane) task fMRI experiment, we demonstrated in detail the BOLD perturbation model for fMRI phase signal separation (P + δP) and reconstructing intrinsic brain magnetic source (χ and δχ). We also provided to a low-field (3T) and low-resolution (2mm) task fMRI experiment in support of single-subject fMRI study. Our experiments show that the δχ-depicted functional map reveals bidirectional BOLD χ perturbations during the task performance. Conclusions The BOLD perturbation model allows us to separate fMRI phase signal (by complex division) and to perform inverse mapping for pure BOLD δχ reconstruction for intrinsic functional χ mapping. The full brain χ reconstruction (from unwrapped fMRI phase) provides a new brain tissue image that allows to scrutinize the brain tissue idiosyncrasy for the pure BOLD δχ response through an automatic function/structure co-localization. PMID:29351339

  12. Brain functional BOLD perturbation modelling for forward fMRI and inverse mapping.

    Science.gov (United States)

    Chen, Zikuan; Robinson, Jennifer; Calhoun, Vince

    2018-01-01

    To computationally separate dynamic brain functional BOLD responses from static background in a brain functional activity for forward fMRI signal analysis and inverse mapping. A brain functional activity is represented in terms of magnetic source by a perturbation model: χ = χ0 +δχ, with δχ for BOLD magnetic perturbations and χ0 for background. A brain fMRI experiment produces a timeseries of complex-valued images (T2* images), whereby we extract the BOLD phase signals (denoted by δP) by a complex division. By solving an inverse problem, we reconstruct the BOLD δχ dataset from the δP dataset, and the brain χ distribution from a (unwrapped) T2* phase image. Given a 4D dataset of task BOLD fMRI, we implement brain functional mapping by temporal correlation analysis. Through a high-field (7T) and high-resolution (0.5mm in plane) task fMRI experiment, we demonstrated in detail the BOLD perturbation model for fMRI phase signal separation (P + δP) and reconstructing intrinsic brain magnetic source (χ and δχ). We also provided to a low-field (3T) and low-resolution (2mm) task fMRI experiment in support of single-subject fMRI study. Our experiments show that the δχ-depicted functional map reveals bidirectional BOLD χ perturbations during the task performance. The BOLD perturbation model allows us to separate fMRI phase signal (by complex division) and to perform inverse mapping for pure BOLD δχ reconstruction for intrinsic functional χ mapping. The full brain χ reconstruction (from unwrapped fMRI phase) provides a new brain tissue image that allows to scrutinize the brain tissue idiosyncrasy for the pure BOLD δχ response through an automatic function/structure co-localization.

  13. MR-guided transcranial brain HIFU in small animal models

    Energy Technology Data Exchange (ETDEWEB)

    Larrat, B; Pernot, M; Aubry, J-F; Sinkus, R; Fink, M; Tanter, M [Institut Langevin, ESPCI ParisTech, CNRS UMR 7587, INSERM U979, Universite Paris VII, Laboratoire Ondes et Acoustique, 10 rue Vauquelin, 75 231 Paris Cedex 05 (France); Dervishi, E; Boch, A-L [Hopital de la Pitie-Salpetriere-INSERM, U495, 47 Boulevard de l' Hopital, 75651 Paris Cedex 13 (France); Seilhean, D [Hopital de la Pitie-Salpetriere-Neuropathology Department, 47 Boulevard de l' Hopital, 75651 Paris Cedex 13 (France); Marie, Y [Hopital de la Pitie-Salpetriere-Neurosurgery Department, 47 Boulevard de l' Hopital, 75651 Paris Cedex 13 (France)], E-mail: benoit.larrat@espci.fr

    2010-01-21

    Recent studies have demonstrated the feasibility of transcranial high-intensity focused ultrasound (HIFU) therapy in the brain using adaptive focusing techniques. However, the complexity of the procedures imposes provision of accurate targeting, monitoring and control of this emerging therapeutic modality in order to ensure the safety of the treatment and avoid potential damaging effects of ultrasound on healthy tissues. For these purposes, a complete workflow and setup for HIFU treatment under magnetic resonance (MR) guidance is proposed and implemented in rats. For the first time, tissue displacements induced by the acoustic radiation force are detected in vivo in brain tissues and measured quantitatively using motion-sensitive MR sequences. Such a valuable target control prior to treatment assesses the quality of the focusing pattern in situ and enables us to estimate the acoustic intensity at focus. This MR-acoustic radiation force imaging is then correlated with conventional MR-thermometry sequences which are used to follow the temperature changes during the HIFU therapeutic session. Last, pre- and post-treatment magnetic resonance elastography (MRE) datasets are acquired and evaluated as a new potential way to non-invasively control the stiffness changes due to the presence of thermal necrosis. As a proof of concept, MR-guided HIFU is performed in vitro in turkey breast samples and in vivo in transcranial rat brain experiments. The experiments are conducted using a dedicated MR-compatible HIFU setup in a high-field MRI scanner (7 T). Results obtained on rats confirmed that both the MR localization of the US focal point and the pre- and post-HIFU measurement of the tissue stiffness, together with temperature control during HIFU are feasible and valuable techniques for efficient monitoring of HIFU in the brain. Brain elasticity appears to be more sensitive to the presence of oedema than to tissue necrosis.

  14. MR-guided transcranial brain HIFU in small animal models

    Science.gov (United States)

    Larrat, B.; Pernot, M.; Aubry, J.-F.; Dervishi, E.; Sinkus, R.; Seilhean, D.; Marie, Y.; Boch, A.-L.; Fink, M.; Tanter, M.

    2010-01-01

    Recent studies have demonstrated the feasibility of transcranial high-intensity focused ultrasound (HIFU) therapy in the brain using adaptive focusing techniques. However, the complexity of the procedures imposes provision of accurate targeting, monitoring and control of this emerging therapeutic modality in order to ensure the safety of the treatment and avoid potential damaging effects of ultrasound on healthy tissues. For these purposes, a complete workflow and setup for HIFU treatment under magnetic resonance (MR) guidance is proposed and implemented in rats. For the first time, tissue displacements induced by the acoustic radiation force are detected in vivo in brain tissues and measured quantitatively using motion-sensitive MR sequences. Such a valuable target control prior to treatment assesses the quality of the focusing pattern in situ and enables us to estimate the acoustic intensity at focus. This MR-acoustic radiation force imaging is then correlated with conventional MR-thermometry sequences which are used to follow the temperature changes during the HIFU therapeutic session. Last, pre- and post-treatment magnetic resonance elastography (MRE) datasets are acquired and evaluated as a new potential way to non-invasively control the stiffness changes due to the presence of thermal necrosis. As a proof of concept, MR-guided HIFU is performed in vitro in turkey breast samples and in vivo in transcranial rat brain experiments. The experiments are conducted using a dedicated MR-compatible HIFU setup in a high-field MRI scanner (7 T). Results obtained on rats confirmed that both the MR localization of the US focal point and the pre- and post-HIFU measurement of the tissue stiffness, together with temperature control during HIFU are feasible and valuable techniques for efficient monitoring of HIFU in the brain. Brain elasticity appears to be more sensitive to the presence of oedema than to tissue necrosis.

  15. Brain Tumor Segmentation Using a Generative Model with an RBM Prior on Tumor Shape

    DEFF Research Database (Denmark)

    Agn, Mikael; Puonti, Oula; Rosenschöld, Per Munck af

    2016-01-01

    In this paper, we present a fully automated generative method for brain tumor segmentation in multi-modal magnetic resonance images. The method is based on the type of generative model often used for segmenting healthy brain tissues, where tissues are modeled by Gaussian mixture models combined...... with a spatial atlas-based tissue prior. We extend this basic model with a tumor prior, which uses convolutional restricted Boltzmann machines (cRBMs) to model the shape of both tumor core and complete tumor, which includes edema and core. The cRBMs are trained on expert segmentations of training images, without...

  16. A Triple Culture Model of the Blood-Brain Barrier Using Porcine Brain Endothelial cells, Astrocytes and Pericytes.

    Science.gov (United States)

    Thomsen, Louiza Bohn; Burkhart, Annette; Moos, Torben

    2015-01-01

    In vitro blood-brain barrier (BBB) models based on primary brain endothelial cells (BECs) cultured as monoculture or in co-culture with primary astrocytes and pericytes are useful for studying many properties of the BBB. The BECs retain their expression of tight junction proteins and efflux transporters leading to high trans-endothelial electric resistance (TEER) and low passive paracellular permeability. The BECs, astrocytes and pericytes are often isolated from small rodents. Larger species as cows and pigs however, reveal a higher yield, are readily available and have a closer resemblance to humans, which make them favorable high-throughput sources for cellular isolation. The aim of the present study has been to determine if the preferable combination of purely porcine cells isolated from the 6 months old domestic pigs, i.e. porcine brain endothelial cells (PBECs) in co-culture with porcine astrocytes and pericytes, would compare with PBECs co-cultured with astrocytes and pericytes isolated from newborn rats with respect to TEER value and low passive permeability. The astrocytes and pericytes were grown both as contact and non-contact co-cultures as well as in triple culture to examine their effects on the PBECs for barrier formation as revealed by TEER, passive permeability, and expression patterns of tight junction proteins, efflux transporters and the transferrin receptor. This syngenic porcine in vitro BBB model is comparable to triple cultures using PBECs, rat astrocytes and rat pericytes with respect to TEER formation, low passive permeability, and expression of hallmark proteins signifying the brain endothelium (tight junction proteins claudin 5 and occludin, the efflux transporters P-glycoprotein (PgP) and breast cancer related protein (BCRP), and the transferrin receptor).

  17. Energy metabolism in neuronal/glial induction and in iPSC models of brain disorders.

    Science.gov (United States)

    Mlody, Barbara; Lorenz, Carmen; Inak, Gizem; Prigione, Alessandro

    2016-04-01

    The metabolic switch associated with the reprogramming of somatic cells to pluripotency has received increasing attention in recent years. However, the impact of mitochondrial and metabolic modulation on stem cell differentiation into neuronal/glial cells and related brain disease modeling still remains to be fully addressed. Here, we seek to focus on this aspect by first addressing brain energy metabolism and its inter-cellular metabolic compartmentalization. We then review the findings related to the mitochondrial and metabolic reconfiguration occurring upon neuronal/glial specification from pluripotent stem cells (PSCs). Finally, we provide an update of the PSC-based models of mitochondria-related brain disorders and discuss the challenges and opportunities that may exist on the road to develop a new era of brain disease modeling and therapy. Copyright © 2016 Elsevier Ltd. All rights reserved.

  18. Non-human Primate Models for Brain Disorders - Towards Genetic Manipulations via Innovative Technology.

    Science.gov (United States)

    Qiu, Zilong; Li, Xiao

    2017-04-01

    Modeling brain disorders has always been one of the key tasks in neurobiological studies. A wide range of organisms including worms, fruit flies, zebrafish, and rodents have been used for modeling brain disorders. However, whether complicated neurological and psychiatric symptoms can be faithfully mimicked in animals is still debatable. In this review, we discuss key findings using non-human primates to address the neural mechanisms underlying stress and anxiety behaviors, as well as technical advances for establishing genetically-engineered non-human primate models of autism spectrum disorders and other disorders. Considering the close evolutionary connections and similarity of brain structures between non-human primates and humans, together with the rapid progress in genome-editing technology, non-human primates will be indispensable for pathophysiological studies and exploring potential therapeutic methods for treating brain disorders.

  19. Atomistic modeling of the structural components of the blood-brain barrier

    Science.gov (United States)

    Glukhova, O. E.; Grishina, O. A.; Slepchenkov, M. M.

    2015-03-01

    Blood-brain barrier, which is a barrage system between the brain and blood vessels, plays a key role in the "isolation" of the brain of unnecessary information, and reduce the "noise" in the interneuron communication. It is known that the barrier function of the BBB strictly depends on the initial state of the organism and changes significantly with age and, especially in developing the "vascular accidents". Disclosure mechanisms of regulation of the barrier function will develop new ways to deliver neurotrophic drugs to the brain in the newborn. The aim of this work is the construction of atomistic models of structural components of the blood-brain barrier to reveal the mechanisms of regulation of the barrier function.

  20. Multiresolution texture models for brain tumor segmentation in MRI.

    Science.gov (United States)

    Iftekharuddin, Khan M; Ahmed, Shaheen; Hossen, Jakir

    2011-01-01

    In this study we discuss different types of texture features such as Fractal Dimension (FD) and Multifractional Brownian Motion (mBm) for estimating random structures and varying appearance of brain tissues and tumors in magnetic resonance images (MRI). We use different selection techniques including KullBack - Leibler Divergence (KLD) for ranking different texture and intensity features. We then exploit graph cut, self organizing maps (SOM) and expectation maximization (EM) techniques to fuse selected features for brain tumors segmentation in multimodality T1, T2, and FLAIR MRI. We use different similarity metrics to evaluate quality and robustness of these selected features for tumor segmentation in MRI for real pediatric patients. We also demonstrate a non-patient-specific automated tumor prediction scheme by using improved AdaBoost classification based on these image features.

  1. Empirical Network Model of Human Higher Cognitive Brain Functions

    Science.gov (United States)

    1990-03-31

    inference of the cogni- tive psychologists, psychophysiologists, neu- tive processes tairing placa during brief analy- rologists and psychiatrists that so...John and Schwartz 1978) that result from direct communication between cortical distinguish between early exogenous and later en- 0 EVENT-RELATED...Bartlett. F.. Thatcher. R.. Kaye. H.. Valdes. P and Schwartz . E. i 1977a) Neurometmcs: numencal taxonomy identifies different profiles of brain functions

  2. Low resolution brain electromagnetic tomography in a realistic geometry head model: a simulation study

    International Nuclear Information System (INIS)

    Ding Lei; Lai Yuan; He Bin

    2005-01-01

    It is of importance to localize neural sources from scalp recorded EEG. Low resolution brain electromagnetic tomography (LORETA) has received considerable attention for localizing brain electrical sources. However, most such efforts have used spherical head models in representing the head volume conductor. Investigation of the performance of LORETA in a realistic geometry head model, as compared with the spherical model, will provide useful information guiding interpretation of data obtained by using the spherical head model. The performance of LORETA was evaluated by means of computer simulations. The boundary element method was used to solve the forward problem. A three-shell realistic geometry (RG) head model was constructed from MRI scans of a human subject. Dipole source configurations of a single dipole located at different regions of the brain with varying depth were used to assess the performance of LORETA in different regions of the brain. A three-sphere head model was also used to approximate the RG head model, and similar simulations performed, and results compared with the RG-LORETA with reference to the locations of the simulated sources. Multi-source localizations were discussed and examples given in the RG head model. Localization errors employing the spherical LORETA, with reference to the source locations within the realistic geometry head, were about 20-30 mm, for four brain regions evaluated: frontal, parietal, temporal and occipital regions. Localization errors employing the RG head model were about 10 mm over the same four brain regions. The present simulation results suggest that the use of the RG head model reduces the localization error of LORETA, and that the RG head model based LORETA is desirable if high localization accuracy is needed

  3. Modeling epileptic brain states using EEG spectral analysis and topographic mapping.

    Science.gov (United States)

    Direito, Bruno; Teixeira, César; Ribeiro, Bernardete; Castelo-Branco, Miguel; Sales, Francisco; Dourado, António

    2012-09-30

    Changes in the spatio-temporal behavior of the brain electrical activity are believed to be associated to epileptic brain states. We propose a novel methodology to identify the different states of the epileptic brain, based on the topographic mapping of the time varying relative power of delta, theta, alpha, beta and gamma frequency sub-bands, estimated from EEG. Using normalized-cuts segmentation algorithm, points of interest are identified in the topographic mappings and their trajectories over time are used for finding out relations with epileptogenic propagations in the brain. These trajectories are used to train a Hidden Markov Model (HMM), which models the different epileptic brain states and the transition among them. Applied to 10 patients suffering from focal seizures, with a total of 30 seizures over 497.3h of data, the methodology shows good results (an average point-by-point accuracy of 89.31%) for the identification of the four brain states--interictal, preictal, ictal and postictal. The results suggest that the spatio-temporal dynamics captured by the proposed methodology are related to the epileptic brain states and transitions involved in focal seizures. Copyright © 2012 Elsevier B.V. All rights reserved.

  4. Early treatment with lyophilized plasma protects the brain in a large animal model of combined traumatic brain injury and hemorrhagic shock

    DEFF Research Database (Denmark)

    Imam, Ayesha M; Jin, Guang; Sillesen, Martin

    2013-01-01

    Combination of traumatic brain injury (TBI) and hemorrhagic shock (HS) can result in significant morbidity and mortality. We have previously shown that early administration of fresh frozen plasma (FFP) in a large animal model of TBI and HS reduces the size of the brain lesion as well...

  5. Formation and life-time of memory domains in the dissipative quantum model of brain

    OpenAIRE

    Alfinito, E.; Vitiello, G.

    2000-01-01

    We show that in the dissipative quantum model of brain the time-dependence of the frequencies of the electrical dipole wave quanta leads to the dynamical organization of the memories in space (i.e. to their localization in more or less diffused regions of the brain) and in time (i.e. to their longer or shorter life-time). The life-time and the localization in domains of the memory states also depend on internal parameters and on the number of links that the brain establishes with the external...

  6. The Effects of Exercise on Cognitive Recovery after Acquired Brain Injury in Animal Models

    DEFF Research Database (Denmark)

    Wogensen, Elise; Rytter, Hana Malá; Mogensen, Jesper

    2015-01-01

    The objective of the present paper is to review the current status of exercise as a tool to promote cognitive rehabilitation after acquired brain injury (ABI) in animal model-based research. Searches were conducted on the PubMed, Scopus, and psycINFO databases in February 2014. Search strings used...... were: exercise (and) animal model (or) rodent (or) rat (and) traumatic brain injury (or) cerebral ischemia (or) brain irradiation. Studies were selected if they were (1) in English, (2) used adult animals subjected to acquired brain injury, (3) used exercise as an intervention tool after inflicted...... injury, (4) used exercise paradigms demanding movement of all extremities, (5) had exercise intervention effects that could be distinguished from other potential intervention effects, and (6) contained at least one measure of cognitive and/or emotional function. Out of 2308 hits, 22 publications...

  7. PET studies of brain energy metabolism in a model of subcortical dementia: progressive supranuclear Palsy

    International Nuclear Information System (INIS)

    Blin, J.; Baron, J.C.; Cambon, H.

    1988-01-01

    In 41 patients with clinically determined Progressive Supranuclear Palsy, a model of degenerative subcortical dementia, alterations in regional brain energy metabolism with respect to control subjects have been investigated using positron computed tomography and correlated to clinical and neuropsychological scores. A generalized significant reduction in brain metabolism was found, which predominated in the prefrontal cortex in accordance with, and statistically correlated to, the frontal neuropsychological score

  8. Bayesian exponential random graph modeling of whole-brain structural networks across lifespan

    OpenAIRE

    Sinke, Michel R T; Dijkhuizen, Rick M; Caimo, Alberto; Stam, Cornelis J; Otte, Wim

    2016-01-01

    Descriptive neural network analyses have provided important insights into the organization of structural and functional networks in the human brain. However, these analyses have limitations for inter-subject or between-group comparisons in which network sizes and edge densities may differ, such as in studies on neurodevelopment or brain diseases. Furthermore, descriptive neural network analyses lack an appropriate generic null model and a unifying framework. These issues may be solved with an...

  9. Mathematical modeling of human glioma growth based on brain topological structures: study of two clinical cases.

    Directory of Open Access Journals (Sweden)

    Cecilia Suarez

    Full Text Available Gliomas are the most common primary brain tumors and yet almost incurable due mainly to their great invasion capability. This represents a challenge to present clinical oncology. Here, we introduce a mathematical model aiming to improve tumor spreading capability definition. The model consists in a time dependent reaction-diffusion equation in a three-dimensional spatial domain that distinguishes between different brain topological structures. The model uses a series of digitized images from brain slices covering the whole human brain. The Talairach atlas included in the model describes brain structures at different levels. Also, the inclusion of the Brodmann areas allows prediction of the brain functions affected during tumor evolution and the estimation of correlated symptoms. The model is solved numerically using patient-specific parametrization and finite differences. Simulations consider an initial state with cellular proliferation alone (benign tumor, and an advanced state when infiltration starts (malign tumor. Survival time is estimated on the basis of tumor size and location. The model is used to predict tumor evolution in two clinical cases. In the first case, predictions show that real infiltrative areas are underestimated by current diagnostic imaging. In the second case, tumor spreading predictions were shown to be more accurate than those derived from previous models in the literature. Our results suggest that the inclusion of differential migration in glioma growth models constitutes another step towards a better prediction of tumor infiltration at the moment of surgical or radiosurgical target definition. Also, the addition of physiological/psychological considerations to classical anatomical models will provide a better and integral understanding of the patient disease at the moment of deciding therapeutic options, taking into account not only survival but also life quality.

  10. A novel ex vivo method for measuring whole brain metabolism in model systems.

    Science.gov (United States)

    Neville, Kathryn E; Bosse, Timothy L; Klekos, Mia; Mills, John F; Weicksel, Steven E; Waters, James S; Tipping, Marla

    2018-02-15

    Many neuronal and glial diseases have been associated with changes in metabolism. Therefore, metabolic reprogramming has become an important area of research to better understand disease at the cellular level, as well as to identify targets for treatment. Model systems are ideal for interrogating metabolic questions in a tissue dependent context. However, while new tools have been developed to study metabolism in cultured cells there has been less progress towards studies in vivo and ex vivo. We have developed a method using newly designed tissue restraints to adapt the Agilent XFe96 metabolic analyzer for whole brain analysis. These restraints create a chamber for Drosophila brains and other small model system tissues to reside undisrupted, while still remaining in the zone for measurements by sensor probes. This method generates reproducible oxygen consumption and extracellular acidification rate data for Drosophila larval and adult brains. Single brains are effectively treated with inhibitors and expected metabolic readings are observed. Measuring metabolic changes, such as glycolytic rate, in transgenic larval brains demonstrates the potential for studying how genotype affects metabolism. Current methodology either utilizes whole animal chambers to measure respiration, not allowing for targeted tissue analysis, or uses technically challenging MRI technology for in vivo analysis that is not suitable for smaller model systems. This new method allows for novel metabolic investigation of intact brains and other tissues ex vivo in a quick, and simplistic way with the potential for large-scale studies. Copyright © 2017 The Authors. Published by Elsevier B.V. All rights reserved.

  11. Reverse brain drain in South Korea: state-led model.

    Science.gov (United States)

    Yoon, B L

    1992-01-01

    Korea's reverse brain drain (RBD) has been an organized government effort, rather than a spontaneous social phenomenon, in that various policies and the political support of President Park, Chung-Hee were instrumental in laying the groundwork for its success. Particular features of Korea's RBD policies are the creation of a conducive domestic environment (i.e., government-sponsored strategic R & D institution-building, legal, and administrative reforms), and importantly, the empowerment of returnees (via, i.e., exceptionally good maternal benefits, guarantees of research autonomy). President Park played the cardinal role in empowering repatriates at the expense of his own civil bureaucracy, and his capacity for such patronage derived from Korea's bureaucratic-authoritarian political system. Returning scientists and engineers directly benefitted from this political system as well as Park's personal guardianship. For Park, empowerment of returning "brains" was necessary to accomplish his national industrialization plan, thereby enhancing his political legitimacy in domestic politics. An alliance with the R & D cadre was functionally necessary to successfully consolidate strong presidential power, and politically nonthreatening due to the particular form of "pact of domination" in Korea's power structure. RBD in Korea will continue in the near future given Korea's drive for high technology, and the remarkable expansion of local industrial and educational sectors. Korea's future RBD, however, needs to pay closer attention to the following 4 problems: research autonomy; equality issues; skill-based repatriation of technicians and engineers rather than Ph.Ds; and subsidies to small and medium industry for RBD.

  12. Embedding Anatomical or Functional Knowledge in Whole-Brain Multiple Kernel Learning Models.

    Science.gov (United States)

    Schrouff, Jessica; Monteiro, J M; Portugal, L; Rosa, M J; Phillips, C; Mourão-Miranda, J

    2018-01-01

    Pattern recognition models have been increasingly applied to neuroimaging data over the last two decades. These applications have ranged from cognitive neuroscience to clinical problems. A common limitation of these approaches is that they do not incorporate previous knowledge about the brain structure and function into the models. Previous knowledge can be embedded into pattern recognition models by imposing a grouping structure based on anatomically or functionally defined brain regions. In this work, we present a novel approach that uses group sparsity to model the whole brain multivariate pattern as a combination of regional patterns. More specifically, we use a sparse version of Multiple Kernel Learning (MKL) to simultaneously learn the contribution of each brain region, previously defined by an atlas, to the decision function. Our application of MKL provides two beneficial features: (1) it can lead to improved overall generalisation performance when the grouping structure imposed by the atlas is consistent with the data; (2) it can identify a subset of relevant brain regions for the predictive model. In order to investigate the effect of the grouping in the proposed MKL approach we compared the results of three different atlases using three different datasets. The method has been implemented in the new version of the open-source Pattern Recognition for Neuroimaging Toolbox (PRoNTo).

  13. A porcine astrocyte/endothelial cell co-culture model of the blood-brain barrier.

    Science.gov (United States)

    Jeliazkova-Mecheva, Valentina V; Bobilya, Dennis J

    2003-10-01

    A method for the isolation of porcine atrocytes as a simple extension of a previously described procedure for isolation of brain capillary endothelial cells from adolescent pigs [Methods Cell Sci. 17 (1995) 2] is described. The obtained astroglial culture purified through two passages and by the method of the selective detachment was validated by a phase contrast microscopy and through an immunofluorescent assay for the glial fibrillary acidic protein (GFAP). Porcine astrocytes were co-cultivated with porcine brain capillary endothelial cells (PBCEC) for the development of an in vitro blood-brain barrier (BBB) model. The model was visualized by an electron microscopy and showed elevated transendothellial electrical resistance and reduced inulin permeability. To our knowledge, this is the first report for the establishment of a porcine astrocyte/endothelial cell co-culture BBB model, which avoids interspecies and age differences between the two cell types, usually encountered in the other reported co-culture BBB models. Considering the availability of the porcine brain tissue and the close physiological and anatomical relation between the human and pig brain, the porcine astrocyte/endothelial cell co-culture system can serve as a reliable and easily reproducible model for different in vitro BBB studies.

  14. Models and theories of brain function in cognition within a framework of behavioral cognitive psychology.

    Science.gov (United States)

    Karakaş, Sirel; Başar, Erol

    2006-05-01

    The present article presents a nonexhaustive collection of contemporary models and theories on brain function and discusses these models and theories within a framework of explanatory formulations in behavioral cognitive psychology. Such a mission was accomplished by evaluating the cognitive implications in the explanatory formulations with respect to established laws/principles and models/theories of behavioral cognitive psychology. The article also points to problem areas of behavioral cognitive psychology for which the explanatory formulations have solutions to offer. The article shows that the cinematographic hypothesis, the new visual model, the synergetic model, and the theory of whole-brain-work emphasize various aspects of perception. The formulations on P300 theory emphasize attention and also working memory. The theory on cognits is a comprehensive account of memory. Characteristic to all of these explanatory formulations and also to that on the complexity and its evolution and that on neurocognitive networks is the emphasis on selective distribution, integration to the point of supersynergy, and dynamicity. Such a viewpoint was not only applied to the operations of the brain but also of cognition. With such a conceptualization, the explanatory formulations could account for cognitive processes other than the ones emphasized. A common aspect in a majority of the formulations is the utilization of the oscillatory activity as the valid activity of the brain. The article points out that a frontier in cognitive psychophysiology would be the study of the genetics of brain oscillations.

  15. Donor pretreatment with carbamylated erythropoietin in a brain death model reduces inflammation more effectively than erythropoietin while preserving renal function

    NARCIS (Netherlands)

    Nijboer, Willemijn N.; Ottens, Petra J.; van Dijk, Antony; van Goor, Harry; Ploeg, Rutger J.; Leuvenink, Henri G. D.

    Objective: We hypothesized that donor treatment of deceased brain dead donors would lead to a decrease in inflammatory responses seen in brain death and lead to a restoration of kidney function. Design: A standardized slow-induction rat brain death model followed by evaluation of kidney function in

  16. Whole-Brain Mapping of Neuronal Activity in the Learned Helplessness Model of Depression.

    Science.gov (United States)

    Kim, Yongsoo; Perova, Zinaida; Mirrione, Martine M; Pradhan, Kith; Henn, Fritz A; Shea, Stephen; Osten, Pavel; Li, Bo

    2016-01-01

    Some individuals are resilient, whereas others succumb to despair in repeated stressful situations. The neurobiological mechanisms underlying such divergent behavioral responses remain unclear. Here, we employed an automated method for mapping neuronal activity in search of signatures of stress responses in the entire mouse brain. We used serial two-photon tomography to detect expression of c-FosGFP - a marker of neuronal activation - in c-fosGFP transgenic mice subjected to the learned helplessness (LH) procedure, a widely used model of stress-induced depression-like phenotype in laboratory animals. We found that mice showing "helpless" behavior had an overall brain-wide reduction in the level of neuronal activation compared with mice showing "resilient" behavior, with the exception of a few brain areas, including the locus coeruleus, that were more activated in the helpless mice. In addition, the helpless mice showed a strong trend of having higher similarity in whole-brain activity profile among individuals, suggesting that helplessness is represented by a more stereotypic brain-wide activation pattern. This latter effect was confirmed in rats subjected to the LH procedure, using 2-deoxy-2[18F]fluoro-D-glucose positron emission tomography to assess neural activity. Our findings reveal distinct brain activity markings that correlate with adaptive and maladaptive behavioral responses to stress, and provide a framework for further studies investigating the contribution of specific brain regions to maladaptive stress responses.

  17. SCI with Brain Injury: Bedside-to-Bench Modeling for Developing Treatment and Rehabilitation Strategies

    Science.gov (United States)

    2012-10-01

    used for pain management), baclofen (used for spasticity control), and topiramate (used for controlling seizures), all identified as common treatment ...Modeling for Developing Treatment and Rehabilitation Strategies PRINCIPAL INVESTIGATOR: Michael S. Beattie, Ph.D...September 2012 4. TITLE AND SUBTITLE SCI with Brain Injury: Bedside To Bench Modeling For Developing Treatment And Rehabilitation Strategies 5a

  18. Dynamics of the brain: Mathematical models and non-invasive experimental studies

    Science.gov (United States)

    Toronov, V.; Myllylä, T.; Kiviniemi, V.; Tuchin, V. V.

    2013-10-01

    Dynamics is an essential aspect of the brain function. In this article we review theoretical models of neural and haemodynamic processes in the human brain and experimental non-invasive techniques developed to study brain functions and to measure dynamic characteristics, such as neurodynamics, neurovascular coupling, haemodynamic changes due to brain activity and autoregulation, and cerebral metabolic rate of oxygen. We focus on emerging theoretical biophysical models and experimental functional neuroimaging results, obtained mostly by functional magnetic resonance imaging (fMRI) and near-infrared spectroscopy (NIRS). We also included our current results on the effects of blood pressure variations on cerebral haemodynamics and simultaneous measurements of fast processes in the brain by near-infrared spectroscopy and a very novel functional MRI technique called magnetic resonance encephalography. Based on a rapid progress in theoretical and experimental techniques and due to the growing computational capacities and combined use of rapidly improving and emerging neuroimaging techniques we anticipate during next decade great achievements in the overall knowledge of the human brain.

  19. The CLAIR model: Extension of Brodmann areas based on brain oscillations and connectivity.

    Science.gov (United States)

    Başar, Erol; Düzgün, Aysel

    2016-05-01

    Since the beginning of the last century, the localization of brain function has been represented by Brodmann areas, maps of the anatomic organization of the brain. They are used to broadly represent cortical structures with their given sensory-cognitive functions. In recent decades, the analysis of brain oscillations has become important in the correlation of brain functions. Moreover, spectral connectivity can provide further information on the dynamic connectivity between various structures. In addition, brain responses are dynamic in nature and structural localization is almost impossible, according to Luria (1966). Therefore, brain functions are very difficult to localize; hence, a combined analysis of oscillation and event-related coherences is required. In this study, a model termed as "CLAIR" is described to enrich and possibly replace the concept of the Brodmann areas. A CLAIR model with optimum function may take several years to develop, but this study sets out to lay its foundation. Copyright © 2016 The Authors. Published by Elsevier B.V. All rights reserved.

  20. Ex vivo micro-CT imaging of murine brain models using non-ionic iodinated contrast

    Science.gov (United States)

    Salas Bautista, N.; Martínez-Dávalos, A.; Rodríguez-Villafuerte, M.; Murrieta-Rodríguez, T.; Manjarrez-Marmolejo, J.; Franco-Pérez, J.; Calvillo-Velasco, M. E.

    2014-11-01

    Preclinical investigation of brain tumors is frequently carried out by means of intracranial implantation of brain tumor xenografts or allografts, with subsequent analysis of tumor growth using conventional histopathology. However, very little has been reported on the use contrast-enhanced techniques in micro-CT imaging for the study of malignant brain tumors in small animal models. The aim of this study has been to test a protocol for ex vivo imaging of murine brain models of glioblastoma multiforme (GBM) after treatment with non-ionic iodinated solution, using an in-house developed laboratory micro-CT. We have found that the best compromise between acquisition time and image quality is obtained using a 50 kVp, 0.5 mAs, 1° angular step on a 360 degree orbit acquisition protocol, with 70 μm reconstructed voxel size using the Feldkamp algorithm. With this parameters up to 4 murine brains can be scanned in tandem in less than 15 minutes. Image segmentation and analysis of three sample brains allowed identifying tumor volumes as small as 0.4 mm3.

  1. Whitening of Background Brain Activity via Parametric Modeling

    Directory of Open Access Journals (Sweden)

    Nidal Kamel

    2007-01-01

    Full Text Available Several signal subspace techniques have been recently suggested for the extraction of the visual evoked potential signals from brain background colored noise. The majority of these techniques assume the background noise as white, and for colored noise, it is suggested to be whitened, without further elaboration on how this might be done. In this paper, we investigate the whitening capabilities of two parametric techniques: a direct one based on Levinson solution of Yule-Walker equations, called AR Yule-Walker, and an indirect one based on the least-squares solution of forward-backward linear prediction (FBLP equations, called AR-FBLP. The whitening effect of the two algorithms is investigated with real background electroencephalogram (EEG colored noise and compared in time and frequency domains.

  2. Terahertz spectroscopy of brain tissue from a mouse model of Alzheimer's disease

    Science.gov (United States)

    Shi, Lingyan; Shumyatsky, Pavel; Rodríguez-Contreras, Adrián; Alfano, Robert

    2016-01-01

    The terahertz (THz) absorption and index of refraction of brain tissues from a mouse model of Alzheimer's disease (AD) and a control wild-type (normal) mouse were compared using THz time-domain spectroscopy (THz-TDS). Three dominating absorption peaks associated to torsional-vibrational modes were observed in AD tissue, at about 1.44, 1.8, and 2.114 THz, closer to the peaks of free tryptophan molecules than in normal tissue. A possible reason is that there is more free tryptophan in AD brain tissue, while in normal brain tissue more tryptophan is attached to other molecules. Our study suggests that THz-absorption modes may be used as an AD biomarker fingerprint in brain, and that THz-TDS is a promising technique for early diagnosis of AD.

  3. BrainK for Structural Image Processing: Creating Electrical Models of the Human Head

    Directory of Open Access Journals (Sweden)

    Kai Li

    2016-01-01

    Full Text Available BrainK is a set of automated procedures for characterizing the tissues of the human head from MRI, CT, and photogrammetry images. The tissue segmentation and cortical surface extraction support the primary goal of modeling the propagation of electrical currents through head tissues with a finite difference model (FDM or finite element model (FEM created from the BrainK geometries. The electrical head model is necessary for accurate source localization of dense array electroencephalographic (dEEG measures from head surface electrodes. It is also necessary for accurate targeting of cerebral structures with transcranial current injection from those surface electrodes. BrainK must achieve five major tasks: image segmentation, registration of the MRI, CT, and sensor photogrammetry images, cortical surface reconstruction, dipole tessellation of the cortical surface, and Talairach transformation. We describe the approach to each task, and we compare the accuracies for the key tasks of tissue segmentation and cortical surface extraction in relation to existing research tools (FreeSurfer, FSL, SPM, and BrainVisa. BrainK achieves good accuracy with minimal or no user intervention, it deals well with poor quality MR images and tissue abnormalities, and it provides improved computational efficiency over existing research packages.

  4. Impact of brain tissue filtering on neurostimulation fields: a modeling study

    Science.gov (United States)

    Wagner, Tim; Eden, Uri; Rushmore, Jarrett; Russo, Christopher J.; Dipietro, Laura; Fregni, Felipe; Simon, Stephen; Rotman, Stephen; Pitskel, Naomi B.; Ramos-Estebanez, Ciro; Pascual-Leone, Alvaro; Grodzinsky, Alan J.; Zahn, Markus; Valero-Cabre, Antoni

    2013-01-01

    Electrical neurostimulation techniques, such as deep brain stimulation (DBS) and transcranial magnetic stimulation (TMS), are increasingly used in the neurosciences, e.g., for studying brain function, and for neurotherapeutics, e.g., for treating depression, epilepsy, and Parkinson’s disease. The characterization of electrical properties of brain tissue has guided our fundamental understanding and application of these methods, from electrophysiologic theory to clinical dosing-metrics. Nonetheless, prior computational models have primarily relied on ex-vivo impedance measurements. We recorded the in-vivo impedances of brain tissues during neurosurgical procedures and used these results to construct MRI guided computational models of TMS and DBS neurostimulatory fields and conductance-based models of neurons exposed to stimulation. We demonstrated that tissues carry neurostimulation currents through frequency dependent resistive and capacitive properties not typically accounted for by past neurostimulation modeling work. We show that these fundamental brain tissue properties can have significant effects on the neurostimulatory-fields (capacitive and resistive current composition and spatial/temporal dynamics) and neural responses (stimulation threshold, ionic currents, and membrane dynamics). These findings highlight the importance of tissue impedance properties on neurostimulation and impact our understanding of the biological mechanisms and technological potential of neurostimulatory methods. PMID:23850466

  5. Intelligence and the brain: a model-based approach

    NARCIS (Netherlands)

    Kievit, R.A.; van Rooijen, H.; Wicherts, J.M.; Waldorp, L.J.; Kan, K.-J.; Scholte, H.S.; Borsboom, D.

    2012-01-01

    Various biological correlates of general intelligence (g) have been reported. Despite this, however, the relationship between neurological measurements and g is not fully clear. We use structural equation modeling to model the relationship between behavioral Wechsler Adult Intelligence Scale (WAIS)

  6. Neurobehavioral Assessments in a Mouse Model of Neonatal Hypoxic-ischemic Brain Injury.

    Science.gov (United States)

    Kim, MinGi; Yu, Ji Hea; Seo, Jung Hwa; Shin, Yoon-Kyum; Wi, Soohyun; Baek, Ahreum; Song, Suk-Young; Cho, Sung-Rae

    2017-11-24

    We performed unilateral carotid artery occlusion on CD-1 mice to create a neonatal hypoxic-ischemic (HI) model and investigated the effects of neonatal HI brain injury by studying neurobehavioral functions in these mice compared to non-operated (i.e., normal) mice. During the study, Rice-Vannucci's method was used to induce neonatal HI brain damage in postnatal day 7-10 (P7-10) mice. The HI operation was performed on the pups by unilateral carotid artery ligation and exposure to hypoxia (8% O2 and 92% N2 for 90 min). One week after the operation, the damaged brains were evaluated with the naked eye through the semi-transparent skull and were categorized into subgroups based on the absence ("no cortical injury" group) or presence ("cortical injury" group) of cortical injury, such as a lesion in the right hemisphere. On week 6, the following neurobehavioral tests were performed to evaluate the cognitive and motor functions: passive avoidance task (PAT), ladder walking test, and grip strength test. These behavioral tests are helpful in determining the effects of neonatal HI brain injury and are used in other mouse models of neurodegenerative diseases. In this study, neonatal HI brain injury mice showed motor deficits that corresponded to right hemisphere damage. The behavioral test results are relevant to the deficits observed in human neonatal HI patients, such as cerebral palsy or neonatal stroke patients. In this study, a mouse model of neonatal HI brain injury was established and showed different degrees of motor deficits and cognitive impairment compared to non-operated mice. This work provides basic information on the HI mouse model. MRI images demonstrate the different phenotypes, separated according to the severity of brain damage by motor and cognitive tests.

  7. Frequency dependence of complex moduli of brain tissue using a fractional Zener model

    International Nuclear Information System (INIS)

    Kohandel, M; Sivaloganathan, S; Tenti, G; Darvish, K

    2005-01-01

    Brain tissue exhibits viscoelastic behaviour. If loading times are substantially short, static tests are not sufficient to determine the complete viscoelastic behaviour of the material, and dynamic test methods are more appropriate. The concept of complex modulus of elasticity is a powerful tool for characterizing the frequency domain behaviour of viscoelastic materials. On the other hand, it is well known that classical viscoelastic models can be generalized by means of fractional calculus to describe more complex viscoelastic behaviour of materials. In this paper, the fractional Zener model is investigated in order to describe the dynamic behaviour of brain tissue. The model is fitted to experimental data of oscillatory shear tests of bovine brain tissue to verify its behaviour and to obtain the material parameters

  8. Simultaneous Whole-Brain Segmentation and White Matter Lesion Detection Using Contrast-Adaptive Probabilistic Models

    DEFF Research Database (Denmark)

    Puonti, Oula; Van Leemput, Koen

    2016-01-01

    In this paper we propose a new generative model for simultaneous brain parcellation and white matter lesion segmentation from multi-contrast magnetic resonance images. The method combines an existing whole-brain segmentation technique with a novel spatial lesion model based on a convolutional...... in multiple sclerosis indicate that the method’s lesion segmentation accuracy compares well to that of the current state-of-the-art in the field, while additionally providing robust whole-brain segmentations....... restricted Boltzmann machine. Unlike current state-of-the-art lesion detection techniques based on discriminative modeling, the proposed method is not tuned to one specific scanner or imaging protocol, and simultaneously segments dozens of neuroanatomical structures. Experiments on a public benchmark dataset...

  9. Using 3D Printing to Create Personalized Brain Models for Neurosurgical Training and Preoperative Planning.

    Science.gov (United States)

    Ploch, Caitlin C; Mansi, Chris S S A; Jayamohan, Jayaratnam; Kuhl, Ellen

    2016-06-01

    Three-dimensional (3D) printing holds promise for a wide variety of biomedical applications, from surgical planning, practicing, and teaching to creating implantable devices. The growth of this cheap and easy additive manufacturing technology in orthopedic, plastic, and vascular surgery has been explosive; however, its potential in the field of neurosurgery remains underexplored. A major limitation is that current technologies are unable to directly print ultrasoft materials like human brain tissue. In this technical note, the authors present a new technology to create deformable, personalized models of the human brain. The method combines 3D printing, molding, and casting to create a physiologically, anatomically, and tactilely realistic model based on magnetic resonance images. Created from soft gelatin, the model is easy to produce, cost-efficient, durable, and orders of magnitude softer than conventionally printed 3D models. The personalized brain model cost $50, and its fabrication took 24 hours. In mechanical tests, the model stiffness (E = 25.29 ± 2.68 kPa) was 5 orders of magnitude softer than common 3D printed materials, and less than an order of magnitude stiffer than mammalian brain tissue (E = 2.64 ± 0.40 kPa). In a multicenter surgical survey, model size (100.00%), visual appearance (83.33%), and surgical anatomy (81.25%) were perceived as very realistic. The model was perceived as very useful for patient illustration (85.00%), teaching (94.44%), learning (100.00%), surgical training (95.00%), and preoperative planning (95.00%). With minor refinements, personalized, deformable brain models created via 3D printing will improve surgical training and preoperative planning with the ultimate goal to provide accurate, customized, high-precision treatment. Copyright © 2016 Elsevier Inc. All rights reserved.

  10. A geometric network model of intrinsic grey-matter connectivity of the human brain

    Science.gov (United States)

    Lo, Yi-Ping; O'Dea, Reuben; Crofts, Jonathan J.; Han, Cheol E.; Kaiser, Marcus

    2015-10-01

    Network science provides a general framework for analysing the large-scale brain networks that naturally arise from modern neuroimaging studies, and a key goal in theoretical neuroscience is to understand the extent to which these neural architectures influence the dynamical processes they sustain. To date, brain network modelling has largely been conducted at the macroscale level (i.e. white-matter tracts), despite growing evidence of the role that local grey matter architecture plays in a variety of brain disorders. Here, we present a new model of intrinsic grey matter connectivity of the human connectome. Importantly, the new model incorporates detailed information on cortical geometry to construct ‘shortcuts’ through the thickness of the cortex, thus enabling spatially distant brain regions, as measured along the cortical surface, to communicate. Our study indicates that structures based on human brain surface information differ significantly, both in terms of their topological network characteristics and activity propagation properties, when compared against a variety of alternative geometries and generative algorithms. In particular, this might help explain histological patterns of grey matter connectivity, highlighting that observed connection distances may have arisen to maximise information processing ability, and that such gains are consistent with (and enhanced by) the presence of short-cut connections.

  11. A deep learning model integrating FCNNs and CRFs for brain tumor segmentation.

    Science.gov (United States)

    Zhao, Xiaomei; Wu, Yihong; Song, Guidong; Li, Zhenye; Zhang, Yazhuo; Fan, Yong

    2018-01-01

    Accurate and reliable brain tumor segmentation is a critical component in cancer diagnosis, treatment planning, and treatment outcome evaluation. Build upon successful deep learning techniques, a novel brain tumor segmentation method is developed by integrating fully convolutional neural networks (FCNNs) and Conditional Random Fields (CRFs) in a unified framework to obtain segmentation results with appearance and spatial consistency. We train a deep learning based segmentation model using 2D image patches and image slices in following steps: 1) training FCNNs using image patches; 2) training CRFs as Recurrent Neural Networks (CRF-RNN) using image slices with parameters of FCNNs fixed; and 3) fine-tuning the FCNNs and the CRF-RNN using image slices. Particularly, we train 3 segmentation models using 2D image patches and slices obtained in axial, coronal and sagittal views respectively, and combine them to segment brain tumors using a voting based fusion strategy. Our method could segment brain images slice-by-slice, much faster than those based on image patches. We have evaluated our method based on imaging data provided by the Multimodal Brain Tumor Image Segmentation Challenge (BRATS) 2013, BRATS 2015 and BRATS 2016. The experimental results have demonstrated that our method could build a segmentation model with Flair, T1c, and T2 scans and achieve competitive performance as those built with Flair, T1, T1c, and T2 scans. Copyright © 2017 Elsevier B.V. All rights reserved.

  12. Is current brain injury rehabilitation enhancing the biopsychosocial model?

    DEFF Research Database (Denmark)

    Glintborg, Chalotte; Hansen, Tia G. B.; Thomsen, Ane Søndergaard

    2014-01-01

    Objective: To synthesize the best available evidence regarding the impact of non-surgical interventions on persistent symptoms after mild traumatic brain injury (MTBI). Data sources: MEDLINE and other databases were searched (2001–2012) with terms including ‘rehabilitation’. Inclusion criteria we...... that early reassuring educational information is beneficial after MTBI. Well-designed intervention studies are required in order to develop effective treatments and improve outcomes for adults and children at risk for persistent symptoms after MTBI....... original, peer-reviewed research published in English and other languages. References were also identified from the bibliographies of eligible articles. Study selection: Controlled trials and cohort and case-control studies were selected according to pre-defined criteria. Studies had to have a minimum......, only two of seven studies related to non-surgical interventions were found to have a low risk of bias. One studied the effect of a scheduled telephone intervention offering counselling and education on outcome and found a significantly better outcome for symptoms (6.6 differences in adjusted mean...

  13. Statistical models for brain signals with properties that evolve across trials.

    Science.gov (United States)

    Ombao, Hernando; Fiecas, Mark; Ting, Chee-Ming; Low, Yin Fen

    2017-12-07

    Most neuroscience cognitive experiments involve repeated presentations of various stimuli across several minutes or a few hours. It has been observed that brain responses, even to the same stimulus, evolve over the course of the experiment. These changes in brain activation and connectivity are believed to be associated with learning and/or habituation. In this paper, we present two general approaches to modeling dynamic brain connectivity using electroencephalograms (EEGs) recorded across replicated trials in an experiment. The first approach is the Markovian regime-switching vector autoregressive model (MS-VAR) which treats EEGs as realizations of an underlying brain process that switches between different states both within a trial and across trials in the entire experiment. The second is the slowly evolutionary locally stationary process (SEv-LSP) which characterizes the observed EEGs as a mixture of oscillatory activities at various frequency bands. The SEv-LSP model captures the dynamic nature of the amplitudes of the band-oscillations and cross-correlations between them. The MS-VAR model is able to capture abrupt changes in the dynamics while the SEv-LSP directly gives interpretable results. Moreover, it is nonparametric and hence does not suffer from model misspecification. For both of these models, time-evolving connectivity metrics in the frequency domain are derived from the model parameters for both functional and effective connectivity. We illustrate these two models for estimating cross-trial connectivity in selective attention using EEG data from an oddball paradigm auditory experiment where the goal is to characterize the evolution of brain responses to target stimuli and to standard tones presented randomly throughout the entire experiment. The results suggest dynamic changes in connectivity patterns over trials with inter-subject variability. Copyright © 2017. Published by Elsevier Inc.

  14. Statistical models for brain signals with properties that evolve across trials

    KAUST Repository

    Ombao, Hernando

    2017-12-07

    Most neuroscience cognitive experiments involve repeated presentations of various stimuli across several minutes or a few hours. It has been observed that brain responses, even to the same stimulus, evolve over the course of the experiment. These changes in brain activation and connectivity are believed to be associated with learning and/or habituation. In this paper, we present two general approaches to modeling dynamic brain connectivity using electroencephalograms (EEGs) recorded across replicated trials in an experiment. The first approach is the Markovian regime-switching vector autoregressive model (MS-VAR) which treats EEGs as realizations of an underlying brain process that switches between different states both within a trial and across trials in the entire experiment. The second is the slowly evolutionary locally stationary process (SEv-LSP) which characterizes the observed EEGs as a mixture of oscillatory activities at various frequency bands. The SEv-LSP model captures the dynamic nature of the amplitudes of the band-oscillations and cross-correlations between them. The MS-VAR model is able to capture abrupt changes in the dynamics while the SEv-LSP directly gives interpretable results. Moreover, it is nonparametric and hence does not suffer from model misspecification. For both of these models, time-evolving connectivity metrics in the frequency domain are derived from the model parameters for both functional and effective connectivity. We illustrate these two models for estimating cross-trial connectivity in selective attention using EEG data from an oddball paradigm auditory experiment where the goal is to characterize the evolution of brain responses to target stimuli and to standard tones presented randomly throughout the entire experiment. The results suggest dynamic changes in connectivity patterns over trials with inter-subject variability.

  15. Combining region- and network-level brain-behavior relationships in a structural equation model.

    Science.gov (United States)

    Bolt, Taylor; Prince, Emily B; Nomi, Jason S; Messinger, Daniel; Llabre, Maria M; Uddin, Lucina Q

    2018-01-15

    Brain-behavior associations in fMRI studies are typically restricted to a single level of analysis: either a circumscribed brain region-of-interest (ROI) or a larger network of brain regions. However, this common practice may not always account for the interdependencies among ROIs of the same network or potentially unique information at the ROI-level, respectively. To account for both sources of information, we combined measurement and structural components of structural equation modeling (SEM) approaches to empirically derive networks from ROI activity, and to assess the association of both individual ROIs and their respective whole-brain activation networks with task performance using three large task-fMRI datasets and two separate brain parcellation schemes. The results for working memory and relational tasks revealed that well-known ROI-performance associations are either non-significant or reversed when accounting for the ROI's common association with its corresponding network, and that the network as a whole is instead robustly associated with task performance. The results for the arithmetic task revealed that in certain cases, an ROI can be robustly associated with task performance, even when accounting for its associated network. The SEM framework described in this study provides researchers additional flexibility in testing brain-behavior relationships, as well as a principled way to combine ROI- and network-levels of analysis. Copyright © 2017 Elsevier Inc. All rights reserved.

  16. Neurodevelopmental Versus Neurodegenerative Model of Schizophrenia and Bipolar Disorder: Comparison with Physiological Brain Development and Aging.

    Science.gov (United States)

    Buoli, Massimiliano; Serati, Marta; Caldiroli, Alice; Cremaschi, Laura; Altamura, Alfredo Carlo

    2017-03-01

    Available data support a contribution of both neurodevelopmental and neurodegenerative factors in the etiology of schizophrenia (SCH) and bipolar disorder (BD). Of note, one of the most important issue of the current psychiatric research is to identify the specific factors that contribute to impaired brain development and neurodegeneration in SCH and BD, and especially how these factors alter normal brain development and physiological aging process. Our hypothesis is that only specific damages, taking place in precise brain development stages, are associated with future SCH /BD onset and that neurodegeneration consists of an acceleration of brain aging after SCH /BD onset. In support of our hypothesis, the results of the present narrative mini-review shows as neurodevelopmental damages generally contribute to neuropsychiatric syndromes (e.g. hypothyroidism or treponema pallidum), but only some of them are specifically associated with adult SCH and BD (e.g. toxoplasma or substance abuse), particularly if they happen in specific stages of brain development. On the other hand, cognitive impairment and brain changes, associated with long duration of SCH /BD, look like what happens during aging: memory, executive domains and prefrontal cortex are implicated both in aging and in SCH /BD progression. Future research will explore possible validity of this etiological model for SCH and BD.

  17. Electric field distribution in a finite-volume head model of deep brain stimulation

    OpenAIRE

    Grant, Peadar F.; Lowery, Madeleine M.

    2009-01-01

    This study presents a whole-head finite element model of deep brain stimulation to examine the effect of electrical grounding, the finite conducting volume of the head, and scalp, skull and cerebrospinal fluid layers. The impedance between the stimulating and reference electrodes in the whole-head model was found to lie within clinically reported values when the reference electrode was incorporated on a localized surface in the model. Incorporation of the finite volume of the head and inclusi...

  18. NKTR-102 Efficacy versus irinotecan in a mouse model of brain metastases of breast cancer

    International Nuclear Information System (INIS)

    Adkins, Chris E.; Nounou, Mohamed I.; Hye, Tanvirul; Mohammad, Afroz S.; Terrell-Hall, Tori; Mohan, Neel K.; Eldon, Michael A.; Hoch, Ute; Lockman, Paul R.

    2015-01-01

    Brain metastases are an increasing problem in women with invasive breast cancer. Strategies designed to treat brain metastases of breast cancer, particularly chemotherapeutics such as irinotecan, demonstrate limited efficacy. Conventional irinotecan distributes poorly to brain metastases; therefore, NKTR-102, a PEGylated irinotecan conjugate should enhance irinotecan and its active metabolite SN38 exposure in brain metastases leading to brain tumor cytotoxicity. Female nude mice were intracranially or intracardially implanted with human brain seeking breast cancer cells (MDA-MB-231Br) and dosed with irinotecan or NKTR-102 to determine plasma and tumor pharmacokinetics of irinotecan and SN38. Tumor burden and survival were evaluated in mice treated with vehicle, irinotecan (50 mg/kg), or NKTR-102 low and high doses (10 mg/kg, 50 mg/kg respectively). NKTR-102 penetrates the blood-tumor barrier and distributes to brain metastases. NKTR-102 increased and prolonged SN38 exposure (>20 ng/g for 168 h) versus conventional irinotecan (>1 ng/g for 4 h). Treatment with NKTR-102 extended survival time (from 35 days to 74 days) and increased overall survival for NKTR-102 low dose (30 % mice) and NKTR-102 high dose (50 % mice). Tumor burden decreased (37 % with 10 mg/kg NKTR-102 and 96 % with 50 mg/kg) and lesion sizes decreased (33 % with 10 mg/kg NKTR-102 and 83 % with 50 mg/kg NKTR-102) compared to conventional irinotecan treated animals. Elevated and prolonged tumor SN38 exposure after NKTR-102 administration appears responsible for increased survival in this model of breast cancer brain metastasis. Further, SN38 concentrations observed in this study are clinically achieved with 145 mg/m 2 NKTR-102, such as those used in the BEACON trial, underlining translational relevance of these results. The online version of this article (doi:10.1186/s12885-015-1672-4) contains supplementary material, which is available to authorized users

  19. A Multimodal Approach for Determining Brain Networks by Jointly Modeling Functional and Structural Connectivity

    Directory of Open Access Journals (Sweden)

    Wenqiong eXue

    2015-02-01

    Full Text Available Recent innovations in neuroimaging technology have provided opportunities for researchers to investigate connectivity in the human brain by examining the anatomical circuitry as well as functional relationships between brain regions. Existing statistical approaches for connectivity generally examine resting-state or task-related functional connectivity (FC between brain regions or separately examine structural linkages. As a means to determine brain networks, we present a unified Bayesian framework for analyzing FC utilizing the knowledge of associated structural connections, which extends an approach by Patel et al.(2006a that considers only functional data. We introduce an FC measure that rests upon assessments of functional coherence between regional brain activity identified from functional magnetic resonance imaging (fMRI data. Our structural connectivity (SC information is drawn from diffusion tensor imaging (DTI data, which is used to quantify probabilities of SC between brain regions. We formulate a prior distribution for FC that depends upon the probability of SC between brain regions, with this dependence adhering to structural-functional links revealed by our fMRI and DTI data. We further characterize the functional hierarchy of functionally connected brain regions by defining an ascendancy measure that compares the marginal probabilities of elevated activity between regions. In addition, we describe topological properties of the network, which is composed of connected region pairs, by performing graph theoretic analyses. We demonstrate the use of our Bayesian model using fMRI and DTI data from a study of auditory processing. We further illustrate the advantages of our method by comparisons to methods that only incorporate functional information.

  20. Deformable templates guided discriminative models for robust 3D brain MRI segmentation.

    Science.gov (United States)

    Liu, Cheng-Yi; Iglesias, Juan Eugenio; Tu, Zhuowen

    2013-10-01

    Automatically segmenting anatomical structures from 3D brain MRI images is an important task in neuroimaging. One major challenge is to design and learn effective image models accounting for the large variability in anatomy and data acquisition protocols. A deformable template is a type of generative model that attempts to explicitly match an input image with a template (atlas), and thus, they are robust against global intensity changes. On the other hand, discriminative models combine local image features to capture complex image patterns. In this paper, we propose a robust brain image segmentation algorithm that fuses together deformable templates and informative features. It takes advantage of the adaptation capability of the generative model and the classification power of the discriminative models. The proposed algorithm achieves both robustness and efficiency, and can be used to segment brain MRI images with large anatomical variations. We perform an extensive experimental study on four datasets of T1-weighted brain MRI data from different sources (1,082 MRI scans in total) and observe consistent improvement over the state-of-the-art systems.

  1. Improved Method for the Establishment of an In Vitro Blood-Brain Barrier Model Based on Porcine Brain Endothelial Cells.

    Science.gov (United States)

    Nielsen, Simone S E; Siupka, Piotr; Georgian, Ana; Preston, Jane E; Tóth, Andrea E; Yusof, Siti R; Abbott, N Joan; Nielsen, Morten S

    2017-09-24

    The aim of this protocol presents an optimized procedure for the purification and cultivation of pBECs and to establish in vitro blood-brain barrier (BBB) models based on pBECs in mono-culture (MC), MC with astrocyte-conditioned medium (ACM), and non-contact co-culture (NCC) with astrocytes of porcine or rat origin. pBECs were isolated and cultured from fragments of capillaries from the brain cortices of domestic pigs 5-6 months old. These fragments were purified by careful removal of meninges, isolation and homogenization of grey matter, filtration, enzymatic digestion, and centrifugation. To further eliminate contaminating cells, the capillary fragments were cultured with puromycin-containing medium. When 60-95% confluent, pBECs growing from the capillary fragments were passaged to permeable membrane filter inserts and established in the models. To increase barrier tightness and BBB characteristic phenotype of pBECs, the cells were treated with the following differentiation factors: membrane permeant 8-CPT-cAMP (here abbreviated cAMP), hydrocortisone, and a phosphodiesterase inhibitor, RO-20-1724 (RO). The procedure was carried out over a period of 9-11 days, and when establishing the NCC model, the astrocytes were cultured 2-8 weeks in advance. Adherence to the described procedures in the protocol has allowed the establishment of endothelial layers with highly restricted paracellular permeability, with the NCC model showing an average transendothelial electrical resistance (TEER) of 1249 ± 80 Ω cm 2 , and paracellular permeability (Papp) for Lucifer Yellow of 0.90 10 -6 ± 0.13 10 -6 cm sec -1 (mean ± SEM, n=55). Further evaluation of this pBEC phenotype showed good expression of the tight junctional proteins claudin 5, ZO-1, occludin and adherens junction protein p120 catenin. The model presented can be used for a range of studies of the BBB in health and disease and, with the highly restrictive paracellular permeability, this model is suitable for studies

  2. A statistical model describing combined irreversible electroporation and electroporation-induced blood-brain barrier disruption.

    Science.gov (United States)

    Sharabi, Shirley; Kos, Bor; Last, David; Guez, David; Daniels, Dianne; Harnof, Sagi; Mardor, Yael; Miklavcic, Damijan

    2016-03-01

    Electroporation-based therapies such as electrochemotherapy (ECT) and irreversible electroporation (IRE) are emerging as promising tools for treatment of tumors. When applied to the brain, electroporation can also induce transient blood-brain-barrier (BBB) disruption in volumes extending beyond IRE, thus enabling efficient drug penetration. The main objective of this study was to develop a statistical model predicting cell death and BBB disruption induced by electroporation. This model can be used for individual treatment planning. Cell death and BBB disruption models were developed based on the Peleg-Fermi model in combination with numerical models of the electric field. The model calculates the electric field thresholds for cell kill and BBB disruption and describes the dependence on the number of treatment pulses. The model was validated using in vivo experimental data consisting of rats brains MRIs post electroporation treatments. Linear regression analysis confirmed that the model described the IRE and BBB disruption volumes as a function of treatment pulses number (r(2) = 0.79; p disruption, the ratio increased with the number of pulses. BBB disruption radii were on average 67% ± 11% larger than IRE volumes. The statistical model can be used to describe the dependence of treatment-effects on the number of pulses independent of the experimental setup.

  3. Evaluation of 3D Additively Manufactured Canine Brain Models for Teaching Veterinary Neuroanatomy.

    Science.gov (United States)

    Schoenfeld-Tacher, Regina M; Horn, Timothy J; Scheviak, Tyler A; Royal, Kenneth D; Hudson, Lola C

    Physical specimens are essential to the teaching of veterinary anatomy. While fresh and fixed cadavers have long been the medium of choice, plastinated specimens have gained widespread acceptance as adjuncts to dissection materials. Even though the plastination process increases the durability of specimens, these are still derived from animal tissues and require periodic replacement if used by students on a regular basis. This study investigated the use of three-dimensional additively manufactured (3D AM) models (colloquially referred to as 3D-printed models) of the canine brain as a replacement for plastinated or formalin-fixed brains. The models investigated were built based on a micro-MRI of a single canine brain and have numerous practical advantages, such as durability, lower cost over time, and reduction of animal use. The effectiveness of the models was assessed by comparing performance among students who were instructed using either plastinated brains or 3D AM models. This study used propensity score matching to generate similar pairs of students. Pairings were based on gender and initial anatomy performance across two consecutive classes of first-year veterinary students. Students' performance on a practical neuroanatomy exam was compared, and no significant differences were found in scores based on the type of material (3D AM models or plastinated specimens) used for instruction. Students in both groups were equally able to identify neuroanatomical structures on cadaveric material, as well as respond to questions involving application of neuroanatomy knowledge. Therefore, we postulate that 3D AM canine brain models are an acceptable alternative to plastinated specimens in teaching veterinary neuroanatomy.

  4. Monkey models for brain-machine interfaces: the need for maintaining diversity.

    Science.gov (United States)

    Nuyujukian, Paul; Fan, Joline M; Gilja, Vikash; Kalanithi, Paul S; Chestek, Cindy A; Shenoy, Krishna V

    2011-01-01

    Brain-machine interfaces (BMIs) aim to help disabled patients by translating neural signals from the brain into control signals for guiding prosthetic arms, computer cursors, and other assistive devices. Animal models are central to the development of these systems and have helped enable the successful translation of the first generation of BMIs. As we move toward next-generation systems, we face the question of which animal models will aid broader patient populations and achieve even higher performance, robustness, and functionality. We review here four general types of rhesus monkey models employed in BMI research, and describe two additional, complementary models. Given the physiological diversity of neurological injury and disease, we suggest a need to maintain the current diversity of animal models and to explore additional alternatives, as each mimic different aspects of injury or disease.

  5. Generative models of rich clubs in Hebbian neuronal networks and large-scale human brain networks.

    Science.gov (United States)

    Vértes, Petra E; Alexander-Bloch, Aaron; Bullmore, Edward T

    2014-10-05

    Rich clubs arise when nodes that are 'rich' in connections also form an elite, densely connected 'club'. In brain networks, rich clubs incur high physical connection costs but also appear to be especially valuable to brain function. However, little is known about the selection pressures that drive their formation. Here, we take two complementary approaches to this question: firstly we show, using generative modelling, that the emergence of rich clubs in large-scale human brain networks can be driven by an economic trade-off between connection costs and a second, competing topological term. Secondly we show, using simulated neural networks, that Hebbian learning rules also drive the emergence of rich clubs at the microscopic level, and that the prominence of these features increases with learning time. These results suggest that Hebbian learning may provide a neuronal mechanism for the selection of complex features such as rich clubs. The neural networks that we investigate are explicitly Hebbian, and we argue that the topological term in our model of large-scale brain connectivity may represent an analogous connection rule. This putative link between learning and rich clubs is also consistent with predictions that integrative aspects of brain network organization are especially important for adaptive behaviour. © 2014 The Author(s) Published by the Royal Society. All rights reserved.

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

    Directory of Open Access Journals (Sweden)

    Yury Petrov

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

  7. Data-Driven Extraction of a Nested Model of Human Brain Function.

    Science.gov (United States)

    Bolt, Taylor; Nomi, Jason S; Yeo, B T Thomas; Uddin, Lucina Q

    2017-07-26

    Decades of cognitive neuroscience research have revealed two basic facts regarding task-driven brain activation patterns. First, distinct patterns of activation occur in response to different task demands. Second, a superordinate, dichotomous pattern of activation/deactivation, is common across a variety of task demands. We explore the possibility that a hierarchical model incorporates these two observed brain activation phenomena into a unifying framework. We apply a latent variable approach, exploratory bifactor analysis, to a large set of human (both sexes) brain activation maps ( n = 108) encompassing cognition, perception, action, and emotion behavioral domains, to determine the potential existence of a nested structure of factors that underlie a variety of commonly observed activation patterns. We find that a general factor, associated with a superordinate brain activation/deactivation pattern, explained the majority of the variance (52.37%) in brain activation patterns. The bifactor analysis also revealed several subfactors that explained an additional 31.02% of variance in brain activation patterns, associated with different manifestations of the superordinate brain activation/deactivation pattern, each emphasizing different contexts in which the task demands occurred. Importantly, this nested factor structure provided better overall fit to the data compared with a non-nested factor structure model. These results point to a domain-general psychological process, representing a "focused awareness" process or "attentional episode" that is variously manifested according to the sensory modality of the stimulus and degree of cognitive processing. This novel model provides the basis for constructing a biologically informed, data-driven taxonomy of psychological processes. SIGNIFICANCE STATEMENT A crucial step in identifying how the brain supports various psychological processes is a well-defined categorization or taxonomy of psychological processes and their

  8. Paving the Way Toward Complex Blood-Brain Barrier Models Using Pluripotent Stem Cells.

    Science.gov (United States)

    Lauschke, Karin; Frederiksen, Lise; Hall, Vanessa Jane

    2017-06-15

    A tissue with great need to be modeled in vitro is the blood-brain barrier (BBB). The BBB is a tight barrier that covers all blood vessels in the brain and separates the brain microenvironment from the blood system. It consists of three cell types [neurovascular unit (NVU)] that contribute to the unique tightness and selective permeability of the BBB and has been shown to be disrupted in many diseases and brain disorders, such as vascular dementia, stroke, multiple sclerosis, and Alzheimer's disease. Given the progress that pluripotent stem cells (PSCs) have made in the past two decades, it is now possible to produce many cell types from the BBB and even partially recapitulate this complex tissue in vitro. In this review, we summarize the most recent developments in PSC differentiation and modeling of the BBB. We also suggest how patient-specific human-induced PSCs could be used to model BBB dysfunction in the future. Lastly, we provide perspectives on how to improve production of the BBB in vitro, for example by improving pericyte differentiation protocols and by better modeling the NVU in the dish.

  9. Evaluation of three-dimensional anisotropic head model for mapping realistic electromagnetic fields of brain tissues

    Directory of Open Access Journals (Sweden)

    Woo Chul Jeong

    2015-08-01

    Full Text Available Electromagnetic fields provide fundamental data for the imaging of electrical tissue properties, such as conductivity and permittivity, in recent magnetic resonance (MR-based tissue property mapping. The induced voltage, current density, and magnetic flux density caused by externally injected current are critical factors for determining the image quality of electrical tissue conductivity. As a useful tool to identify bio-electromagnetic phenomena, precise approaches are required to understand the exact responses inside the human body subject to an injected currents. In this study, we provide the numerical simulation results of electromagnetic field mapping of brain tissues using a MR-based conductivity imaging method. First, we implemented a realistic three-dimensional human anisotropic head model using high-resolution anatomical and diffusion tensor MR images. The voltage, current density, and magnetic flux density of brain tissues were imaged by injecting 1 mA of current through pairs of electrodes on the surface of our head model. The current density map of anisotropic brain tissues was calculated from the measured magnetic flux density based on the linear relationship between the water diffusion tensor and the electrical conductivity tensor. Comparing the current density to the previous isotropic model, the anisotropic model clearly showed the differences between the brain tissues. This originates from the enhanced signals by the inherent conductivity contrast as well as the actual tissue condition resulting from the injected currents.

  10. Action and Language Mechanisms in the Brain: Data, Models and Neuroinformatics

    Science.gov (United States)

    Bonaiuto, James J.; Bornkessel-Schlesewsky, Ina; Kemmerer, David; MacWhinney, Brian; Nielsen, Finn Årup; Oztop, Erhan

    2014-01-01

    We assess the challenges of studying action and language mechanisms in the brain, both singly and in relation to each other to provide a novel perspective on neuroinformatics, integrating the development of databases for encoding – separately or together – neurocomputational models and empirical data that serve systems and cognitive neuroscience. PMID:24234916

  11. Action and Language Mechanisms in the Brain: Data, Models and Neuroinformatics

    DEFF Research Database (Denmark)

    Arbib, Michael A.; Bonaiuto, James J.; Bornkessel-Schlesewsky, Ina

    2014-01-01

    We assess the challenges of studying action and language mechanisms in the brain, both singly and in relation to each other to provide a novel perspective on neuroinformatics, integrating the development of databases for encoding - separately or together - neurocomputational models and empirical ...

  12. [Structural Equation Modeling on Living and Brain Death Organ Donation Intention in Nursing Students].

    Science.gov (United States)

    Kim, Eun A; Choi, So Eun

    2015-12-01

    The purpose of this study was to test and validate a model to predict living and brain death organ donation intention in nursing students. The conceptual model was based on the theory planned behavior. Quota sampling methodology was used to recruit 921 nursing students from all over the country and data collection was done from October 1 to December 20, 2013. The model fit indices for the hypothetical model were suitable for the recommended level. Knowledge, attitude, subjective norm and perceived behavioral control explained 40.2% and 40.1% respectively for both living and brain death organ donation intention. Subjective norm was the most direct influential factor for organ donation intention. Knowledge had significant direct effect on attitude and indirect effect on subjective norm and perceived behavioral control. These effects were higher in brain death organ donation intention than in living donation intention. The overall findings of this study suggest the need to develop systematic education programs to increases knowledge about brain death organ donation. The development, application, and evaluation of intervention programs are required to improve subjective norm.

  13. Effects of Ecballium elaterium on brain in a rat model of sepsis ...

    African Journals Online (AJOL)

    Here we examined the anti-inflammatory and antioxidant effects of Ecballium elaterium (EE) on brain, and explored its therapeutic potential in an animal model of sepsis-associated encephalopathy (SAE) [induced by cecal ligation and puncture (CLP)]. Thirty rats were divided into three groups of 10 each: control, sepsis, ...

  14. Brain scan in cerebral ischemia. An experimental model in the rat

    International Nuclear Information System (INIS)

    Turner, J.H.

    1975-01-01

    A rapid embolic method for consistent induction of stroke in the rat is described. Brain scans were performed using a micro-pinhole collimator system, and the value of the model for studies in localization of radiopharmaceuticals in cerebral ischemia is demonstrated

  15. Multigrid Nonlocal Gaussian Mixture Model for Segmentation of Brain Tissues in Magnetic Resonance Images

    Directory of Open Access Journals (Sweden)

    Yunjie Chen

    2016-01-01

    Full Text Available We propose a novel segmentation method based on regional and nonlocal information to overcome the impact of image intensity inhomogeneities and noise in human brain magnetic resonance images. With the consideration of the spatial distribution of different tissues in brain images, our method does not need preestimation or precorrection procedures for intensity inhomogeneities and noise. A nonlocal information based Gaussian mixture model (NGMM is proposed to reduce the effect of noise. To reduce the effect of intensity inhomogeneity, the multigrid nonlocal Gaussian mixture model (MNGMM is proposed to segment brain MR images in each nonoverlapping multigrid generated by using a new multigrid generation method. Therefore the proposed model can simultaneously overcome the impact of noise and intensity inhomogeneity and automatically classify 2D and 3D MR data into tissues of white matter, gray matter, and cerebral spinal fluid. To maintain the statistical reliability and spatial continuity of the segmentation, a fusion strategy is adopted to integrate the clustering results from different grid. The experiments on synthetic and clinical brain MR images demonstrate the superior performance of the proposed model comparing with several state-of-the-art algorithms.

  16. Global fractional anisotropy and mean diffusivity together with segmented brain volumes assemble a predictive discriminant model for young and elderly healthy brains: a pilot study at 3T

    Science.gov (United States)

    Garcia-Lazaro, Haydee Guadalupe; Becerra-Laparra, Ivonne; Cortez-Conradis, David; Roldan-Valadez, Ernesto

    2016-01-01

    Summary Several parameters of brain integrity can be derived from diffusion tensor imaging. These include fractional anisotropy (FA) and mean diffusivity (MD). Combination of these variables using multivariate analysis might result in a predictive model able to detect the structural changes of human brain aging. Our aim was to discriminate between young and older healthy brains by combining structural and volumetric variables from brain MRI: FA, MD, and white matter (WM), gray matter (GM) and cerebrospinal fluid (CSF) volumes. This was a cross-sectional study in 21 young (mean age, 25.71±3.04 years; range, 21–34 years) and 10 elderly (mean age, 70.20±4.02 years; range, 66–80 years) healthy volunteers. Multivariate discriminant analysis, with age as the dependent variable and WM, GM and CSF volumes, global FA and MD, and gender as the independent variables, was used to assemble a predictive model. The resulting model was able to differentiate between young and older brains: Wilks’ λ = 0.235, χ2 (6) = 37.603, p = .000001. Only global FA, WM volume and CSF volume significantly discriminated between groups. The total accuracy was 93.5%; the sensitivity, specificity and positive and negative predictive values were 91.30%, 100%, 100% and 80%, respectively. Global FA, WM volume and CSF volume are parameters that, when combined, reliably discriminate between young and older brains. A decrease in FA is the strongest predictor of membership of the older brain group, followed by an increase in WM and CSF volumes. Brain assessment using a predictive model might allow the follow-up of selected cases that deviate from normal aging. PMID:27027893

  17. Lévy-based modelling in brain imaging

    DEFF Research Database (Denmark)

    Jónsdóttir, Kristjana Ýr; Rønn-Nielsen, Anders; Mouridsen, Kim

    2013-01-01

    A substantive problem in neuroscience is the lack of valid statistical methods for non-Gaussian random fields. In the present study, we develop a flexible, yet tractable model for a random field based on kernel smoothing of a so-called Lévy basis. The resulting field may be Gaussian, but there ar...

  18. Fast, Sequence Adaptive Parcellation of Brain MR Using Parametric Models

    DEFF Research Database (Denmark)

    Puonti, Oula; Iglesias, Juan Eugenio; Van Leemput, Koen

    2013-01-01

    -of-the-art segmentation performance in both cortical and subcortical structures, while retaining all the benefits of generative parametric models, including high computational speed, automatic adaptiveness to changes in image contrast when different scanner platforms and pulse sequences are used, and the ability...

  19. A Generic Multi-Compartmental CNS Distribution Model Structure for 9 Drugs Allows Prediction of Human Brain Target Site Concentrations

    NARCIS (Netherlands)

    Yamamoto, Yumi; Valitalo, Pyry A.; van den Berg, Dirk-Jan; Hartman, Robin; van den Brink, Willem; Wong, Yin Cheong; Huntjens, Dymphy R.; Proost, Johannes H.; Vermeulen, An; Krauwinkel, Walter; Bakshi, Suruchi; Aranzana-Climent, Vincent; Marchand, Sandrine; Dahyot-Fizelier, Claire; Couet, William; Danhof, Meindert; van Hasselt, Johan G. C.; de lange, Elizabeth C. M.

    Purpose Predicting target site drug concentration in the brain is of key importance for the successful development of drugs acting on the central nervous system. We propose a generic mathematical model to describe the pharmacokinetics in brain compartments, and apply this model to predict human

  20. Thymoquinone attenuates brain injury via an antioxidative pathway in a status epilepticus rat model

    Directory of Open Access Journals (Sweden)

    Shao Yi-ye

    2017-03-01

    Full Text Available Status epilepticus (SE results in the generation of reactive oxygen species (ROS, which contribute to seizure-induced brain injury. It is well known that oxidative stress plays a pivotal role in status epilepticus (SE. Thymoquinone (TQ is a bioactive monomer extracted from black cumin (Nigella sativa seed oil that has anti-inflammatory, anti-cancer, and antioxidant activity in various diseases. This study evaluated the protective effects of TQ on brain injury in a lithium-pilocarpine rat model of SE and investigated the underlying mechanism related to antioxidative pathway.

  1. Sexual differentiation of the brain: a model for drug-induced alterations of the reproductive system

    International Nuclear Information System (INIS)

    Gorski, R.A.

    1986-01-01

    The process of the sexual differentiation of the brain represents a valuable model system for the study of the chemical modification of the mammalian brain. Although there are numerous functional and structural sex differences in the adult brain, these are imposed on an essentially feminine or bipotential brain by testicular hormones during a critical phase of perinatal development in the rat. It is suggested that a relatively marked structural sex difference in the rat brain, the sexually dimorphic nucleus of the preoptic area (SDN-POA), is a morphological signature of the permanent or organizational action of estradiol derived from the aromatization of testicular testosterone. The SDN-POA of the male rat is severalfold larger in volume and is composed of more neurons than that of the female. The observation that the mitotic formation of the neurons of the SDN-POA is specifically prolonged has enabled us to identify the time course and pathway of neuronal migration into the nucleus. Study of the development of the SDN-POA suggests that estradiol in the male increases the number of neurons which survive a phase of neuronal death by exerting a neurite growth promoting action and/or a direct neuronotrophic action. Finally, although it is clear that gonadal hormones have dramatic permanent effects on the brain during perinatal development, even after puberty and in adulthood gonadal steroids can alter neuronal structure and, perhaps as a corollary to this, have permanent effects on reproductive function. Although the brain may be most sensitive to gonadal hormones or exogenous chemical factors during perinatal development, such as sensitivity does not appear limited to this period

  2. Metabolic fingerprints of altered brain growth, osmoregulation and neurotransmission in a Rett syndrome model.

    Directory of Open Access Journals (Sweden)

    Angèle Viola

    Full Text Available BACKGROUND: Rett syndrome (RS is the leading cause of profound mental retardation of genetic origin in girls. Since RS is mostly caused by mutations in the MECP2 gene, transgenic animal models such as the Mecp2-deleted ("Mecp2-null" mouse have been employed to study neurological symptoms and brain function. However, an interdisciplinary approach drawing from chemistry, biology and neuroscience is needed to elucidate the mechanistic links between the genotype and phenotype of this genetic disorder. METHODOLOGY/PRINCIPAL FINDINGS: We performed, for the first time, a metabolomic study of brain extracts from Mecp2-null mice by using high-resolution magnetic resonance spectroscopy. A large number of individual water-soluble metabolites and phospholipids were quantified without prior selection for specific metabolic pathways. Results were interpreted in terms of Mecp2 gene deletion, brain cell function and brain morphology. This approach provided a "metabolic window" to brain characteristics in Mecp2-null mice (n = 4, revealing (i the first metabolic evidence of astrocyte involvement in RS (decreased levels of the astrocyte marker, myo-inositol, vs. wild-type mice; p = 0.034; (ii reduced choline phospholipid turnover in Mecp2-null vs. wild-type mice, implying a diminished potential of cells to grow, paralleled by globally reduced brain size and perturbed osmoregulation; (iii alterations of the platelet activating factor (PAF cycle in Mecp2-null mouse brains, where PAF is a bioactive lipid acting on neuronal growth, glutamate exocytosis and other processes; and (iv changes in glutamine/glutamate ratios (p = 0.034 in Mecp2-null mouse brains potentially indicating altered neurotransmitter recycling. CONCLUSIONS/SIGNIFICANCE: This study establishes, for the first time, detailed metabolic fingerprints of perturbed brain growth, osmoregulation and neurotransmission in a mouse model of Rett syndrome. Combined with morphological and neurological findings

  3. Modeling of activation data in the BrainMapTM database: Detection of outliers

    DEFF Research Database (Denmark)

    Nielsen, Finn Årup; Hansen, Lars Kai

    2002-01-01

    We describe a system for meta-analytical modeling of activation foci from functional neuroimaging studies. Our main vehicle is a set of density models in Talairach space capturing the distribution of activation foci in sets of experiments labeled by lobar anatomy. One important use of such densit...... of atlases for outlier detection. Hum. Brain Mapping 15:146-156, 2002. © 2002 Wiley-Liss, Inc....

  4. Neural mass modeling of power-line magnetic fields effects on brain activity.

    Science.gov (United States)

    Modolo, J; Thomas, A W; Legros, A

    2013-01-01

    Neural mass models are an appropriate framework to study brain activity, combining a high degree of biological realism while being mathematically tractable. These models have been used, with a certain success, to simulate brain electric (electroencephalography, EEG) and metabolic (functional magnetic resonance imaging, fMRI) activity. However, concrete applications of neural mass models have remained limited to date. Motivated by experimental results obtained in humans, we propose in this paper a neural mass model designed to study the interaction between power-line magnetic fields (MFs) (60 Hz in North America) and brain activity. The model includes pyramidal cells; dendrite-projecting, slow GABAergic neurons; soma-projecting, fast GABAergic neurons; and glutamatergic interneurons. A simple phenomenological model of interaction between the induced electric field and neuron membranes is also considered, along with a model of post-synaptic calcium concentration and associated changes in synaptic weights Simulated EEG signals are produced in a simple protocol, both in the absence and presence of a 60 Hz MF. These results are discussed based on results obtained previously in humans. Notably, results highlight that (1) EEG alpha (8-12 Hz) power can be modulated by weak membrane depolarizations induced by the exposure; (2) the level of input noise has a significant impact on EEG power modulation; and (3) the threshold value in MF flux density resulting in a significant effect on the EEG depends on the type of neuronal populations modulated by the MF exposure. Results obtained from the model shed new light on the effects of power-line MFs on brain activity, and will provide guidance in future human experiments. This may represent a valuable contribution to international regulation agencies setting guidelines on MF values to which the general public and workers can be exposed.

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

    Directory of Open Access Journals (Sweden)

    Romeo Cecchelli

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

  6. Novel models for studying the blood-brain and blood-eye barriers in Drosophila.

    Science.gov (United States)

    Pinsonneault, Robert L; Mayer, Nasima; Mayer, Fahima; Tegegn, Nebiyu; Bainton, Roland J

    2011-01-01

    In species as varied as humans and flies, humoral/central nervous system barrier structures are a major obstacle to the passive penetration of small molecules including endogenous compounds, environmental toxins, and drugs. In vivo measurement of blood-brain physiologic function in vertebrate animal models is difficult and current ex vivo models for more rapid experimentation using, for example, cultured brain endothelial cells, only partially reconstitute the anatomy and physiology of a fully intact blood-brain barrier (BBB). To address these problems, we and others continue to develop in vivo assays for studying the complex physiologic function of central nervous system (CNS) barriers using the fruit fly Drosophila melanogaster (Dm). These methods involve the introduction of small molecule reporters of BBB physiology into the fly humoral compartment by direct injection. Since these reporters must cross the Dm BBB in order to be visible in the eye, we can directly assess genetic or chemical modulators of BBB function by monitoring retinal fluorescence. This assay has the advantage of utilizing a physiologically intact BBB in a model organism that is economical and highly amenable to genetic manipulation. In combination with other approaches outlined here, such as brain dissection and behavioral assessment, one can produce a fuller picture of BBB biology and physiology. In this chapter, we provide detailed methods for examining BBB biology in the fly, including a Dm visual assay to screen for novel modulators of the BBB.

  7. New semi-automatic ROI setting system for brain PET images based on elastic model

    Energy Technology Data Exchange (ETDEWEB)

    Tanizaki, Naoaki; Okamura, Tetsuya (Sumitomo Heavy Industries Ltd., Kanagawa (Japan). Research and Development Center); Senda, Michio; Toyama, Hinako; Ishii, Kenji

    1994-10-01

    We have developed a semi-automatic ROI setting system for brain PET images. It is based on the elastic network model that fits the standard ROI atlas into individual brain image. The standard ROI atlas is a set of segments that represent each anatomical region. For transformation, the operator needs to set only three kinds of district anatomical features: manually determined midsagittal line, brain contour line determined with SNAKES algorithm semi-automatically, a few manually determined specific ROIs to be used for exact transformation. Improvement of the operation time and the inter-operator variance were demonstrated in the experiment by comparing with the conventional manual ROI setting. The operation time was reduced to 50% in almost all cases. And the inter-operator variance was reduced to one seventh in the maximum case. (author).

  8. Analysis of Biotinylated Generation 4 Poly(amidoamine (PAMAM Dendrimer Distribution in the Rat Brain and Toxicity in a Cellular Model of the Blood-Brain Barrier

    Directory of Open Access Journals (Sweden)

    Heather A. Bullen

    2013-09-01

    Full Text Available Dendrimers are highly customizable nanopolymers with qualities that make them ideal for drug delivery. The high binding affinity of biotin/avidin provides a useful approach to fluorescently label synthesized dendrimer-conjugates in cells and tissues. In addition, biotin may facilitate delivery of dendrimers through the blood-brain barrier (BBB via carrier-mediated endocytosis. The purpose of this research was to: (1 measure toxicity using lactate dehydrogenase (LDH assays of generation (G4 biotinylated and non-biotinylated poly(amidoamine (PAMAM dendrimers in a co-culture model of the BBB, (2 determine distribution of dendrimers in the rat brain, kidney, and liver following systemic administration of dendrimers, and (3 conduct atomic force microscopy (AFM on rat brain sections following systemic administration of dendrimers. LDH measurements showed that biotinylated dendrimers were toxic to cell co-culture after 48 h of treatment. Distribution studies showed evidence of biotinylated and non-biotinylated PAMAM dendrimers in brain. AFM studies showed evidence of dendrimers only in brain tissue of treated rats. These results indicate that biotinylation does not decrease toxicity associated with PAMAM dendrimers and that biotinylated PAMAM dendrimers distribute in the brain. Furthermore, this article provides evidence of nanoparticles in brain tissue following systemic administration of nanoparticles supported by both fluorescence microscopy and AFM.

  9. SMN deficiency disrupts brain development in a mouse model of severe spinal muscular atrophy

    Science.gov (United States)

    Wishart, Thomas M.; Huang, Jack P.-W.; Murray, Lyndsay M.; Lamont, Douglas J.; Mutsaers, Chantal A.; Ross, Jenny; Geldsetzer, Pascal; Ansorge, Olaf; Talbot, Kevin; Parson, Simon H.; Gillingwater, Thomas H.

    2010-01-01

    Reduced expression of the survival motor neuron (SMN) gene causes the childhood motor neuron disease spinal muscular atrophy (SMA). Low levels of ubiquitously expressed SMN protein result in the degeneration of lower motor neurons, but it remains unclear whether other regions of the nervous system are also affected. Here we show that reduced levels of SMN lead to impaired perinatal brain development in a mouse model of severe SMA. Regionally selective changes in brain morphology were apparent in areas normally associated with higher SMN levels in the healthy postnatal brain, including the hippocampus, and were associated with decreased cell density, reduced cell proliferation and impaired hippocampal neurogenesis. A comparative proteomics analysis of the hippocampus from SMA and wild-type littermate mice revealed widespread modifications in expression levels of proteins regulating cellular proliferation, migration and development when SMN levels were reduced. This study reveals novel roles for SMN protein in brain development and maintenance and provides the first insights into cellular and molecular pathways disrupted in the brain in a severe form of SMA. PMID:20705736

  10. Studying Brain Circuit Function with Dynamic Causal Modeling for Optogenetic fMRI.

    Science.gov (United States)

    Bernal-Casas, David; Lee, Hyun Joo; Weitz, Andrew J; Lee, Jin Hyung

    2017-02-08

    Defining the large-scale behavior of brain circuits with cell type specificity is a major goal of neuroscience. However, neuronal circuit diagrams typically draw upon anatomical and electrophysiological measurements acquired in isolation. Consequently, a dynamic and cell-type-specific connectivity map has never been constructed from simultaneous measurements across the brain. Here, we introduce dynamic causal modeling (DCM) for optogenetic fMRI experiments-which uniquely allow cell-type-specific, brain-wide functional measurements-to parameterize the causal relationships among regions of a distributed brain network with cell type specificity. Strikingly, when applied to the brain-wide basal ganglia-thalamocortical network, DCM accurately reproduced the empirically observed time series, and the strongest connections were key connections of optogenetically stimulated pathways. We predict that quantitative and cell-type-specific descriptions of dynamic connectivity, as illustrated here, will empower novel systems-level understanding of neuronal circuit dynamics and facilitate the design of more effective neuromodulation therapies. Copyright © 2017 Elsevier Inc. All rights reserved.

  11. Maternal Fructose Consumption Disrupts Brain Development of Offspring in a Murine Model of Autism Spectrum Disorder.

    Science.gov (United States)

    Saad, Antonio F; Alshehri, Wael; Lei, Jun; Kechichian, Talar B; Gamble, Phyllis; Alhejaily, Nader; Shabi, Yahya; Saade, George R; Costantine, Maged M; Burd, Irina

    2016-12-01

    Objective  The objective of this study was to localize by neuroimaging the altered structural brain development of these offspring using an autism model of transgenic mice lacking contactin-associated protein-like 2 (Cntnap2). Materials and Methods  Pregnant dams were randomly allocated to fructose solution (10% W/V) as only drinking fluid or water. Cntnap2 heterozygous (+/-) offspring from each group were euthanized at 6 months of age and their whole brains evaluated by magnetic resonance imaging. T2-weighted images were acquired to evaluate the volumes of 29 regions of interest involved in autism spectrum disorder (ASD) pathogenesis. Whole brains were washed and processed for Nissl staining. Mann-Whitney U test and one-way analysis of variance were used for statistical analysis (significance: p  brain alterations were found in the female counterparts. Nissl staining of the caudate putamen revealed higher neuronal cell count in the male fructose offspring. Female group revealed an increase in caudate putamen neuronal cell count. Conclusion  Metabolic dysregulation in pregnancy alters fetal brain development in genetically predisposed offspring. This is consistent with findings in human studies and supports the role of intrauterine factors in the etiology of autism. Thieme Medical Publishers 333 Seventh Avenue, New York, NY 10001, USA.

  12. Brain injury and discrimination: Two competing models-perceptions of responsibility and dangerousness.

    Science.gov (United States)

    Foster, Lynette A; Leathem, Janet M; Humphries, Steve

    2016-01-01

    (1) To examine whether the willingness of people to socialize with adolescents with brain injury is influenced by gender, visibility of injury and/or knowing how to interact with people with brain injury; and (2) To consider two models: the responsibility model (attributions about the cause of a condition) and the danger appraisal model (perceptions of dangerousness due to anger/aggression) for their effect on willingness to socialize and to understand how these perceptions lead to avoidant behaviour. Participants were recruited either by personal approach or via Facebook advertising and completed a survey after reading a brief vignette and seeing a photo of an adolescent male or female, with or without a head scar. Vignettes for some participants were varied to represent perceptions of responsibility and dangerousness Main outcomes and results: ANOVAs and structural equation modelling revealed that participants were more willing to socialize with the adolescents with a scar than with no scar. Knowledge about how to interact with survivors impacted willingness to socialize, but familiarity did not. The full danger appraisal model was supported, but only some aspects of the responsibility model were supported. The results provide useful information for rehabilitation health professionals working with survivors of brain injury. The implications of these findings are discussed with regards to assisting adolescents' re-entry into society post-injury.

  13. Role of Soft-Tissue Heterogeneity in Computational Models of Deep Brain Stimulation.

    Science.gov (United States)

    Howell, Bryan; McIntyre, Cameron C

    Bioelectric field models of deep brain stimulation (DBS) are commonly utilized in research and industrial applications. However, the wide range of different representations used for the human head in these models may be responsible for substantial variance in the stimulation predictions. Determine the relative error of ignoring cerebral vasculature and soft-tissue heterogeneity outside of the brain in computational models of DBS. We used a detailed atlas of the human head, coupled to magnetic resonance imaging data, to construct a range of subthalamic DBS volume conductor models. We incrementally simplified the most detailed base model and quantified changes in the stimulation thresholds for direct activation of corticofugal axons. Ignoring cerebral vasculature altered predictions of stimulation thresholds by brain altered predictions between -44 % and 174%. Heterogeneity in the soft tissues of the head, if unaccounted for, introduces a degree of uncertainty in predicting electrical stimulation of neural elements that is not negligible and thereby warrants consideration in future modeling studies. Copyright © 2016 Elsevier Inc. All rights reserved.

  14. Predicting 14-day mortality after severe traumatic brain injury: Application of the IMPACT models in the brain trauma foundation TBI-trac® New York state database

    NARCIS (Netherlands)

    B. Roozenbeek (Bob); Y.-L. Chiu (Ya-Lin); H.F. Lingsma (Hester); L.M. Gerber (Linda); E.W. Steyerberg (Ewout); J. Ghajar (Jam); A.I.R. Maas (Andrew)

    2012-01-01

    textabstractPrognostic models for outcome prediction in patients with traumatic brain injury (TBI) are important instruments in both clinical practice and research. To remain current a continuous process of model validation is necessary. We aimed to investigate the performance of the International

  15. Prenatal pharmacotherapy rescues brain development in a Down's syndrome mouse model.

    Science.gov (United States)

    Guidi, Sandra; Stagni, Fiorenza; Bianchi, Patrizia; Ciani, Elisabetta; Giacomini, Andrea; De Franceschi, Marianna; Moldrich, Randal; Kurniawan, Nyoman; Mardon, Karine; Giuliani, Alessandro; Calzà, Laura; Bartesaghi, Renata

    2014-02-01

    Intellectual impairment is a strongly disabling feature of Down's syndrome, a genetic disorder of high prevalence (1 in 700-1000 live births) caused by trisomy of chromosome 21. Accumulating evidence shows that widespread neurogenesis impairment is a major determinant of abnormal brain development and, hence, of intellectual disability in Down's syndrome. This defect is worsened by dendritic hypotrophy and connectivity alterations. Most of the pharmacotherapies designed to improve cognitive performance in Down's syndrome have been attempted in Down's syndrome mouse models during adult life stages. Yet, as neurogenesis is mainly a prenatal event, treatments aimed at correcting neurogenesis failure in Down's syndrome should be administered during pregnancy. Correction of neurogenesis during the very first stages of brain formation may, in turn, rescue improper brain wiring. The aim of our study was to establish whether it is possible to rescue the neurodevelopmental alterations that characterize the trisomic brain with a prenatal pharmacotherapy with fluoxetine, a drug that is able to restore post-natal hippocampal neurogenesis in the Ts65Dn mouse model of Down's syndrome. Pregnant Ts65Dn females were treated with fluoxetine from embryonic Day 10 until delivery. On post-natal Day 2 the pups received an injection of 5-bromo-2-deoxyuridine and were sacrificed after either 2 h or after 43 days (at the age of 45 days). Untreated 2-day-old Ts65Dn mice exhibited a severe neurogenesis reduction and hypocellularity throughout the forebrain (subventricular zone, subgranular zone, neocortex, striatum, thalamus and hypothalamus), midbrain (mesencephalon) and hindbrain (cerebellum and pons). In embryonically treated 2-day-old Ts65Dn mice, precursor proliferation and cellularity were fully restored throughout all brain regions. The recovery of proliferation potency and cellularity was still present in treated Ts65Dn 45-day-old mice. Moreover, embryonic treatment restored

  16. Dynamics of chaotic maps for modelling the multifractal spectrum of human brain Diffusion Tensor Images

    International Nuclear Information System (INIS)

    Provata, A.; Katsaloulis, P.; Verganelakis, D.A.

    2012-01-01

    Highlights: ► Calculation of human brain multifractal spectra. ► Calculations are based on Diffusion Tensor MRI Images. ► Spectra are modelled by coupled Ikeda map dynamics. ► Coupled lattice Ikeda maps model well only positive multifractal spectra. ► Appropriately modified coupled lattice Ikeda maps give correct spectra. - Abstract: The multifractal spectra of 3d Diffusion Tensor Images (DTI) obtained by magnetic resonance imaging of the human brain are studied. They are shown to deviate substantially from artificial brain images with the same white matter intensity. All spectra, obtained from 12 healthy subjects, show common characteristics indicating non-trivial moments of the intensity. To model the spectra the dynamics of the chaotic Ikeda map are used. The DTI multifractal spectra for positive q are best approximated by 3d coupled Ikeda maps in the fully developed chaotic regime. The coupling constants are as small as α = 0.01. These results reflect not only the white tissue non-trivial architectural complexity in the human brain, but also demonstrate the presence and importance of coupling between neuron axons. The architectural complexity is also mirrored by the deviations in the negative q-spectra, where the rare events dominate. To obtain a good agreement in the DTI negative q-spectrum of the brain with the Ikeda dynamics, it is enough to slightly modify the most rare events of the coupled Ikeda distributions. The representation of Diffusion Tensor Images with coupled Ikeda maps is not unique: similar conclusions are drawn when other chaotic maps (Tent, Logistic or Henon maps) are employed in the modelling of the neuron axons network.

  17. Deep brain stimulation during early adolescence prevents microglial alterations in a model of maternal immune activation.

    Science.gov (United States)

    Hadar, Ravit; Dong, Le; Del-Valle-Anton, Lucia; Guneykaya, Dilansu; Voget, Mareike; Edemann-Callesen, Henriette; Schweibold, Regina; Djodari-Irani, Anais; Goetz, Thomas; Ewing, Samuel; Kettenmann, Helmut; Wolf, Susanne A; Winter, Christine

    2017-07-01

    In recent years schizophrenia has been recognized as a neurodevelopmental disorder likely involving a perinatal insult progressively affecting brain development. The poly I:C maternal immune activation (MIA) rodent model is considered as a neurodevelopmental model of schizophrenia. Using this model we and others demonstrated the association between neuroinflammation in the form of altered microglia and a schizophrenia-like endophenotype. Therapeutic intervention using the anti-inflammatory drug minocycline affected altered microglia activation and was successful in the adult offspring. However, less is known about the effect of preventive therapeutic strategies on microglia properties. Previously we found that deep brain stimulation of the medial prefrontal cortex applied pre-symptomatically to adolescence MIA rats prevented the manifestation of behavioral and structural deficits in adult rats. We here studied the effects of deep brain stimulation during adolescence on microglia properties in adulthood. We found that in the hippocampus and nucleus accumbens, but not in the medial prefrontal cortex, microglial density and soma size were increased in MIA rats. Pro-inflammatory cytokine mRNA was unchanged in all brain areas before and after implantation and stimulation. Stimulation of either the medial prefrontal cortex or the nucleus accumbens normalized microglia density and soma size in main projection areas including the hippocampus and in the area around the electrode implantation. We conclude that in parallel to an alleviation of the symptoms in the rat MIA model, deep brain stimulation has the potential to prevent the neuroinflammatory component in this disease. Copyright © 2016 Elsevier Inc. All rights reserved.

  18. Multifactorial causal model of brain (dis)organization and therapeutic intervention: Application to Alzheimer's disease.

    Science.gov (United States)

    Iturria-Medina, Yasser; Carbonell, Félix M; Sotero, Roberto C; Chouinard-Decorte, Francois; Evans, Alan C

    2017-05-15

    Generative models focused on multifactorial causal mechanisms in brain disorders are scarce and generally based on limited data. Despite the biological importance of the multiple interacting processes, their effects remain poorly characterized from an integrative analytic perspective. Here, we propose a spatiotemporal multifactorial causal model (MCM) of brain (dis)organization and therapeutic intervention that accounts for local causal interactions, effects propagation via physical brain networks, cognitive alterations, and identification of optimum therapeutic interventions. In this article, we focus on describing the model and applying it at the population-based level for studying late onset Alzheimer's disease (LOAD). By interrelating six different neuroimaging modalities and cognitive measurements, this model accurately predicts spatiotemporal alterations in brain amyloid-β (Aβ) burden, glucose metabolism, vascular flow, resting state functional activity, structural properties, and cognitive integrity. The results suggest that a vascular dysregulation may be the most-likely initial pathologic event leading to LOAD. Nevertheless, they also suggest that LOAD it is not caused by a unique dominant biological factor (e.g. vascular or Aβ) but by the complex interplay among multiple relevant direct interactions. Furthermore, using theoretical control analysis of the identified population-based multifactorial causal network, we show the crucial advantage of using combinatorial over single-target treatments, explain why one-target Aβ based therapies might fail to improve clinical outcomes, and propose an efficiency ranking of possible LOAD interventions. Although still requiring further validation at the individual level, this work presents the first analytic framework for dynamic multifactorial brain (dis)organization that may explain both the pathologic evolution of progressive neurological disorders and operationalize the influence of multiple interventional

  19. Brain tumor modeling using the CRISPR/Cas9 system: state of the art and view to the future.

    Science.gov (United States)

    Mao, Xiao-Yuan; Dai, Jin-Xiang; Zhou, Hong-Hao; Liu, Zhao-Qian; Jin, Wei-Lin

    2016-05-31

    Although brain tumors have been known tremendously over the past decade, there are still many problems to be solved. The etiology of brain tumors is not well understood and the treatment remains modest. There is in great need to develop a suitable brain tumor models that faithfully mirror the etiology of human brain neoplasm and subsequently get more efficient therapeutic approaches for these disorders. In this review, we described the current status of animal models of brain tumors and analyzed their advantages and disadvantages. Additionally, prokaryotic clustered regularly interspaced short palindromic repeats (CRISPR)/CRISPR-associated protein 9 (Cas9), a versatile genome editing technology for investigating the functions of target genes, and its application were also introduced in our present work. We firstly proposed that brain tumor modeling could be well established via CRISPR/Cas9 techniques. And CRISPR/Cas9-mediated brain tumor modeling was likely to be more suitable for figuring out the pathogenesis of brain tumors, as CRISPR/Cas9 platform was a simple and more efficient biological toolbox for implementing mutagenesis of oncogenes or tumor suppressors that were closely linked with brain tumors.

  20. Computer modeling the boron compound factor in normal brain tissue

    International Nuclear Information System (INIS)

    Gavin, P.R.; Huiskamp, R.; Wheeler, F.J.; Griebenow, M.L.

    1993-01-01

    The macroscopic distribution of borocaptate sodium (Na 2 B 12 H 11 SH or BSH) in normal tissues has been determined and can be accurately predicted from the blood concentration. The compound para-borono-phenylalanine (p-BPA) has also been studied in dogs and normal tissue distribution has been determined. The total physical dose required to reach a biological isoeffect appears to increase directly as the proportion of boron capture dose increases. This effect, together with knowledge of the macrodistribution, led to estimates of the influence of the microdistribution of the BSH compound. This paper reports a computer model that was used to predict the compound factor for BSH and p-BPA and, hence, the equivalent radiation in normal tissues. The compound factor would need to be calculated for other compounds with different distributions. This information is needed to design appropriate normal tissue tolerance studies for different organ systems and/or different boron compounds

  1. Brain and behavioral pathology in an animal model of Wernicke's encephalopathy and Wernicke-Korsakoff Syndrome.

    Science.gov (United States)

    Vetreno, Ryan P; Ramos, Raddy L; Anzalone, Steven; Savage, Lisa M

    2012-02-03

    Animal models provide the opportunity for in-depth and experimental investigation into the anatomical and physiological underpinnings of human neurological disorders. Rodent models of thiamine deficiency have yielded significant insight into the structural, neurochemical and cognitive deficits associated with thiamine deficiency as well as proven useful toward greater understanding of memory function in the intact brain. In this review, we discuss the anatomical, neurochemical and behavioral changes that occur during the acute and chronic phases of thiamine deficiency and describe how rodent models of Wernicke-Korsakoff Syndrome aid in developing a more detailed picture of brain structures involved in learning and memory. Copyright © 2011 Elsevier B.V. All rights reserved.

  2. In Vitro and Ex Vivo Model Systems to Measure ABC Transporter Activity at the Blood-Brain Barrier.

    Science.gov (United States)

    de Wit, Nienke M; Kooij, Gijs; de Vries, Helga E

    2016-01-01

    With the aging population the occurrence of central nervous system diseases such as cancer, mental disorders and neurodegenerative diseases, is expected to increase and hence, the demand for effective drugs. However, the passage of drugs across the blood-brain barrier represents a major challenge in accomplishing efficient brain delivery of therapeutic agents. This highly efficient barrier is composed of a monolayer of capillary endothelial cells supported by pericytes and astrocytic end-feet, that together effectively shield the brain from the blood. The brain microvascular endothelial cells form a physical and metabolic barrier where paracellular and transcellular transport of molecules in and out of the brain is closely regulated, allowing nutrients to pass but preventing the entry of harmful neurotoxic substances, including drugs. For this purpose brain endothelial cells express efficient efflux pumps, such as ATP binding cassette (ABC) transporters, which limit the delivery of drugs into the brain. To treat the above-mentioned chronic central nervous system disorders, it is crucial to design compounds that can pass the blood-brain barrier and thus the ABC transporters. In order to achieve this, representative models of the blood-brain barrier with predictive validity are necessary. This review discusses the current in vitro and ex vivo model systems that are used to measure ABC transporter activity in order to study potential in vivo efficacy of blood-brain barrier-drug passage.

  3. Using human brain imaging studies as a guide towards animal models of schizophrenia

    Science.gov (United States)

    BOLKAN, Scott S.; DE CARVALHO, Fernanda D.; KELLENDONK, Christoph

    2015-01-01

    Schizophrenia is a heterogeneous and poorly understood mental disorder that is presently defined solely by its behavioral symptoms. Advances in genetic, epidemiological and brain imaging techniques in the past half century, however, have significantly advanced our understanding of the underlying biology of the disorder. In spite of these advances clinical research remains limited in its power to establish the causal relationships that link etiology with pathophysiology and symptoms. In this context, animal models provide an important tool for causally testing hypotheses about biological processes postulated to be disrupted in the disorder. While animal models can exploit a variety of entry points towards the study of schizophrenia, here we describe an approach that seeks to closely approximate functional alterations observed with brain imaging techniques in patients. By modeling these intermediate pathophysiological alterations in animals, this approach offers an opportunity to (1) tightly link a single functional brain abnormality with its behavioral consequences, and (2) to determine whether a single pathophysiology can causally produce alterations in other brain areas that have been described in patients. In this review we first summarize a selection of well-replicated biological abnormalities described in the schizophrenia literature. We then provide examples of animal models that were studied in the context of patient imaging findings describing enhanced striatal dopamine D2 receptor function, alterations in thalamo-prefrontal circuit function, and metabolic hyperfunction of the hippocampus. Lastly, we discuss the implications of findings from these animal models for our present understanding of schizophrenia, and consider key unanswered questions for future research in animal models and human patients. PMID:26037801

  4. 3D active shape models of human brain structures: application to patient-specific mesh generation

    Science.gov (United States)

    Ravikumar, Nishant; Castro-Mateos, Isaac; Pozo, Jose M.; Frangi, Alejandro F.; Taylor, Zeike A.

    2015-03-01

    The use of biomechanics-based numerical simulations has attracted growing interest in recent years for computer-aided diagnosis and treatment planning. With this in mind, a method for automatic mesh generation of brain structures of interest, using statistical models of shape (SSM) and appearance (SAM), for personalised computational modelling is presented. SSMs are constructed as point distribution models (PDMs) while SAMs are trained using intensity profiles sampled from a training set of T1-weighted magnetic resonance images. The brain structures of interest are, the cortical surface (cerebrum, cerebellum & brainstem), lateral ventricles and falx-cerebri membrane. Two methods for establishing correspondences across the training set of shapes are investigated and compared (based on SSM quality): the Coherent Point Drift (CPD) point-set registration method and B-spline mesh-to-mesh registration method. The MNI-305 (Montreal Neurological Institute) average brain atlas is used to generate the template mesh, which is deformed and registered to each training case, to establish correspondence over the training set of shapes. 18 healthy patients' T1-weightedMRimages form the training set used to generate the SSM and SAM. Both model-training and model-fitting are performed over multiple brain structures simultaneously. Compactness and generalisation errors of the BSpline-SSM and CPD-SSM are evaluated and used to quantitatively compare the SSMs. Leave-one-out cross validation is used to evaluate SSM quality in terms of these measures. The mesh-based SSM is found to generalise better and is more compact, relative to the CPD-based SSM. Quality of the best-fit model instance from the trained SSMs, to test cases are evaluated using the Hausdorff distance (HD) and mean absolute surface distance (MASD) metrics.

  5. Seasonal plasticity in the brain: the use of large animal models for neuroanatomical research.

    Science.gov (United States)

    Lehman, M N; Coolen, L M; Goodman, R L; Viguié, C; Billings, H J; Karsch, F J

    2002-01-01

    Seasonally breeding mammals display an annual cycle of fertility that is associated with both structural neuroplasticity and functional changes in the activity of the GnRH neurones in the brain. Sheep are valuable models for understanding the hormonal and environmental cues that regulate seasonal reproduction, as well as the brain circuitry that underlies this response. As a result of the large size of sheep, we can tightly correlate the anatomy of GnRH cells and their patterns of gene expression with direct measurements of their neurosecretory output. Tract tracing studies have begun to reveal the pathways by which seasonal changes in response to oestradiol negative feedback affect the function of the reproductive system. Electron microscopic studies have shown that synaptic inputs on to ovine GnRH cells undergo marked seasonal rearrangements that are independent of hormonal changes and may reflect the intrinsic seasonality of the brain. Recent work indicates that the polysialylated form of neural cell adhesion molecule (PSA-NCAM), a marker of neuroplasticity, is well positioned anatomically to contribute to seasonal structural and functional alterations. Applying state-of-the-art neuroanatomical techniques to this model has allowed us to delineate the neural pathways responsible for the seasonal shut down of reproduction in sheep, as well as to begin to uncover the cellular mechanisms underlying seasonal neuroplasticity in the adult mammalian brain.

  6. WONOEP APPRAISAL: NEW SYSTEMIC FUNCTIONAL IMAGING TECHNOLOGIES TO STUDY THE BRAIN IN EXPERIMENTAL MODELS OF EPILEPSY

    Science.gov (United States)

    Dedeurwaerdere, Stefanie; Shultz, Sandy R.; Federico, Paolo; Engel, Jerome

    2014-01-01

    Summary Objectives Modern functional neuroimaging provides opportunities to visualize activity of the entire brain, making it an indispensable diagnostic tool for epilepsy. Various forms of non-invasive functional neuroimaging are now also being performed as research tools in animal models of epilepsy and provide opportunities for parallel animal/human investigations into fundamental mechanisms of epilepsy and identification of epilepsy biomarkers. Methods Recent animal studies of epilepsy using positron emission tomography, tractography, and functional magnetic resonance imaging were reviewed. Results Epilepsy is an abnormal emergent property of disturbances in neuronal networks which, even for epilepsies characterized by focal seizures, involve widely distributed systems, often in both hemispheres. Functional neuroimaging in animal models now provides opportunities to examine neuronal disturbances in the whole brain that underlie generalized and focal seizure generation as well as various types of epileptogenesis. Significance Tremendous advances in understanding the contribution of specific properties of widely distributed neuronal networks to both normal and abnormal human behavior have been provided by current functional neuroimaging methodologies. Successful application of functional neuroimaging of the whole brain in the animal laboratory now permits investigations during epileptogenesis and correlation with deep brain EEG activity. With the continuing development of these techniques and analytical methods, the potential for future translational research on epilepsy is enormous. PMID:24836499

  7. Halofuginone Inhibits Angiogenesis and Growth in Implanted Metastatic Rat Brain Tumor Model-an MRI Study

    Directory of Open Access Journals (Sweden)

    Rinat Abramovitch

    2004-09-01

    Full Text Available Tumor growth and metastasis depend on angiogenesis; therefore, efforts are made to develop specific angiogenic inhibitors. Halofuginone (HF is a potent inhibitor of collagen type α1(I. In solid tumor models, HF has a potent antitumor and antiangiogenic effect in vivo, but its effect on brain tumors has not yet been evaluated. By employing magnetic resonance imaging (MRI, we monitored the effect of HF on tumor progression and vascularization by utilizing an implanted malignant fibrous histiocytoma metastatic rat brain tumor model. Here we demonstrate that treatment with HF effectively and dose-dependently reduced tumor growth and angiogenesis. On day 13, HF-treated tumors were fivefold smaller than control (P < .001. Treatment with HF significantly prolonged survival of treated animals (142%; P = .001. In HF-treated rats, tumor vascularization was inhibited by 30% on day 13 and by 37% on day 19 (P < .05. Additionally, HF treatment inhibited vessel maturation (P = .03. Finally, in HF-treated rats, we noticed the appearance of a few clusters of satellite tumors, which were distinct from the primary tumor and usually contained vessel cores. This phenomenon was relatively moderate when compared to previous reports of other antiangiogenic agents used to treat brain tumors. We therefore conclude that HF is effective for treatment of metastatic brain tumors.

  8. MALDI Mass Spectrometric Imaging of Lipids in Rat Brain Injury Models

    Science.gov (United States)

    Hankin, Joseph A.; Farias, Santiago; Barkley, Robert M.; Heidenreich, Kim; Frey, Lauren C.; Hamazaki, Kei; Kim, Hee-Yong; Murphy, Robert C.

    2015-01-01

    Matrix-assisted laser desorption ionization/imaging mass spectrometry (MALDI IMS) with a time-of-flight analyzer was used to characterize the distribution of lipid molecular species in the brain of rats in two injury models. Ischemia/reperfusion injury of the rat brain after bilateral occlusion of the carotid artery altered appearance of the phospholipids present in the hippocampal region, specifically the CA1 region. These brain regions also had a large increase in the ion abundance at m/z 548.5 and collisional activation supported identification of this ion as arising from ceramide (d18:1/18:0), a lipid known to be associated with cellular apoptosis. Traumatic brain injury model in the rat was examined by MALDI IMS and the area of damage also showed an increase in ceramide (d18:1/18:0) and a remarkable loss of signal for the potassium adduct of the most abundant phosphocholine molecular species 16:0/18:1 (PC) with a corresponding increase in the sodium adduct ion. This change in PC alkali attachment ion was suggested to be a result of edema and influx of extracellular fluid likely through a loss of Na/K-ATPase caused by the injury. These studies reveal the value of MALDI IMS to examine tissues for changes in lipid biochemistry and will provide data needed to eventually understand the biochemical mechanisms relevant to tissue injury. PMID:21953042

  9. Progressive brain damage, synaptic reorganization and NMDA activation in a model of epileptogenic cortical dysplasia.

    Directory of Open Access Journals (Sweden)

    Francesca Colciaghi

    Full Text Available Whether severe epilepsy could be a progressive disorder remains as yet unresolved. We previously demonstrated in a rat model of acquired focal cortical dysplasia, the methylazoxymethanol/pilocarpine - MAM/pilocarpine - rats, that the occurrence of status epilepticus (SE and subsequent seizures fostered a pathologic process capable of modifying the morphology of cortical pyramidal neurons and NMDA receptor expression/localization. We have here extended our analysis by evaluating neocortical and hippocampal changes in MAM/pilocarpine rats at different epilepsy stages, from few days after onset up to six months of chronic epilepsy. Our findings indicate that the process triggered by SE and subsequent seizures in the malformed brain i is steadily progressive, deeply altering neocortical and hippocampal morphology, with atrophy of neocortex and CA regions and progressive increase of granule cell layer dispersion; ii changes dramatically the fine morphology of neurons in neocortex and hippocampus, by increasing cell size and decreasing both dendrite arborization and spine density; iii induces reorganization of glutamatergic and GABAergic networks in both neocortex and hippocampus, favoring excitatory vs inhibitory input; iv activates NMDA regulatory subunits. Taken together, our data indicate that, at least in experimental models of brain malformations, severe seizure activity, i.e., SE plus recurrent seizures, may lead to a widespread, steadily progressive architectural, neuronal and synaptic reorganization in the brain. They also suggest the mechanistic relevance of glutamate/NMDA hyper-activation in the seizure-related brain pathologic plasticity.

  10. Progressive brain damage, synaptic reorganization and NMDA activation in a model of epileptogenic cortical dysplasia.

    Science.gov (United States)

    Colciaghi, Francesca; Finardi, Adele; Nobili, Paola; Locatelli, Denise; Spigolon, Giada; Battaglia, Giorgio Stefano

    2014-01-01

    Whether severe epilepsy could be a progressive disorder remains as yet unresolved. We previously demonstrated in a rat model of acquired focal cortical dysplasia, the methylazoxymethanol/pilocarpine - MAM/pilocarpine - rats, that the occurrence of status epilepticus (SE) and subsequent seizures fostered a pathologic process capable of modifying the morphology of cortical pyramidal neurons and NMDA receptor expression/localization. We have here extended our analysis by evaluating neocortical and hippocampal changes in MAM/pilocarpine rats at different epilepsy stages, from few days after onset up to six months of chronic epilepsy. Our findings indicate that the process triggered by SE and subsequent seizures in the malformed brain i) is steadily progressive, deeply altering neocortical and hippocampal morphology, with atrophy of neocortex and CA regions and progressive increase of granule cell layer dispersion; ii) changes dramatically the fine morphology of neurons in neocortex and hippocampus, by increasing cell size and decreasing both dendrite arborization and spine density; iii) induces reorganization of glutamatergic and GABAergic networks in both neocortex and hippocampus, favoring excitatory vs inhibitory input; iv) activates NMDA regulatory subunits. Taken together, our data indicate that, at least in experimental models of brain malformations, severe seizure activity, i.e., SE plus recurrent seizures, may lead to a widespread, steadily progressive architectural, neuronal and synaptic reorganization in the brain. They also suggest the mechanistic relevance of glutamate/NMDA hyper-activation in the seizure-related brain pathologic plasticity.

  11. Altered brain protein expression profiles are associated with molecular neurological dysfunction in the PKU mouse model.

    Science.gov (United States)

    Imperlini, Esther; Orrù, Stefania; Corbo, Claudia; Daniele, Aurora; Salvatore, Francesco

    2014-06-01

    Phenylketonuria (PKU), if not detected and treated in newborns, causes severe neurological dysfunction and cognitive and behavioral deficiencies. Despite the biochemical characterization of PKU, the molecular mechanisms underlying PKU-associated brain dysfunction remain poorly understood. The aim of this study was to gain insights into the pathogenesis of this neurological damage by analyzing protein expression profiles in brain tissue of Black and Tan BRachyury-PahEnu2 mice (a mouse model of PKU). We compared the cerebral protein expression of homozygous PKU mice with that of their heterozygous counterparts using two-dimensional difference gel electrophoresis analysis, and identified 21 differentially expressed proteins, four of which were over-expressed and 17 under-expressed. An in silico bioinformatic approach indicated that protein under-expression was related to neuronal differentiation and dendritic growth, and to such neurological disorders as progressive motor neuropathy and movement disorders. Moreover, functional annotation analyses showed that some identified proteins were involved in oxidative metabolism. To further investigate the proteins involved in the neurological damage, we validated two of the proteins that were most strikingly under-expressed, namely, Syn2 and Dpysl2, which are involved in synaptic function and neurotransmission. We found that Glu2/3 and NR1 receptor subunits were over-expressed in PKU mouse brain. Our results indicate that differential expression of these proteins may be associated with the processes underlying PKU brain dysfunction, namely, decreased synaptic plasticity and impaired neurotransmission. We identified a set of proteins whose expression is affected by hyperphenylalaninemia. We think that phenylketonuria (PKU) brain dysfunction also depends on reduced Syn2 and Dpysl2 levels, increased Glu2/3 and NR1 levels, and decreased Pkm, Ckb, Pgam1 and Eno1 levels. These findings finally confirm that alteration in synaptic

  12. Oral administration of sitagliptin activates CREB and is neuroprotective in murine model of brain trauma

    Directory of Open Access Journals (Sweden)

    Brian Dellavalle

    2016-12-01

    Full Text Available Introduction: Traumatic brain injury is a major cause of mortality and morbidity. We have previously shown that the injectable glucagon-like peptide-1 (GLP-1 analogue, liraglutide, significantly improved the outcome in mice after severe traumatic brain injury (TBI. In this study we are interested in the effects of oral treatment of a different class of GLP-1 based therapy, dipeptidyl peptidase IV (DPP-IV inhibition on mice after TBI. DPP-IV inhibitors reduce the degradation of endogenous GLP-1 and extend circulation of this protective peptide in the bloodstream. This class has yet to be investigated as a potential therapy for TBI. Methods: Mice were administrated once-daily 50 mg/kg of sitagliptin in a Nutella® ball or Nutella® alone throughout the study, beginning two days before severe trauma was induced with a stereotactic cryo-lesion. At two days post trauma, lesion size was determined. Brains were isolated for immunoblotting for assessment of selected biomarkers for pathology and protection.Results: Sitagliptin treatment reduced lesion size at day 2 post-injury by ~28% (p0.05. Conversely, apoptotic tone (alpha-spectrin fragmentation, Bcl-2 levels and the neuroinflammatory markers IL-6, and Iba-1 were not affected by treatment.Conclusions: This study shows, for the first time, that DPP-IV inhibition ameliorates both anatomical and biochemical consequences of TBI and activates CREB in the brain. Moreover, this work supports previous studies suggesting that the effect of GLP-1 analogues in models of brain damage relates to GLP-1 receptor stimulation in a dose-dependent manner.Keywords: GLP-1, Traumatic Brain Injury, TBI, sitagliptin, liraglutide, CREB, Oxidative Stress, GIP, DPP-IV, DPP-4

  13. Luria’s model of the functional units of the brain and the neuropsychology of dreaming

    Directory of Open Access Journals (Sweden)

    Téllez A.

    2016-12-01

    Full Text Available Traditionally, neuropsychology has focused on identifying the brain mechanisms of specific psychological processes, such as attention, motor skills, perception, memory, language, and consciousness, as well as their corresponding disorders. However, there are psychological processes that have received little attention in this field, such as dreaming. This study examined the clinical and experimental neuropsychological research relevant to dreaming, ranging from sleep disorders in patients with brain damage, to brain functioning during REM sleep, using different methods of brain imaging. These findings were analyzed within the framework of Luria’s Three Functional Unit Model of the Brain, and a proposal was made to explain certain of the essential characteristics of dreaming. This explanation describes how, during dreaming, an activation of the First Functional Unit occurs, comprising the reticular formation of the brainstem; this activates, in turn, the Second Functional Unit — which is formed by the parietal, occipital, and temporal lobes and Unit L, which is comprised of the limbic system, as well as simultaneous hypo-functioning of the Third Functional Unit (frontal lobe. This activity produces a perception of hallucinatory images of various sensory modes, as well as a lack of inhibition, a non-selfreflexive thought process, and a lack of planning and direction of such oneiric images. Dreaming is considered a type of natural confabulation, similar to the one that occurs in patients with frontal lobe damage or schizophrenia. The study also suggests that the confabulatory, bizarre, and impulsive nature of dreaming has a function in the cognitiveemotional homeostasis that aids proper brain function throughout the day.

  14. The application of a mathematical model linking structural and functional connectomes in severe brain injury

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    A. Kuceyeski

    2016-01-01

    Full Text Available Following severe injuries that result in disorders of consciousness, recovery can occur over many months or years post-injury. While post-injury synaptogenesis, axonal sprouting and functional reorganization are known to occur, the network-level processes underlying recovery are poorly understood. Here, we test a network-level functional rerouting hypothesis in recovery of patients with disorders of consciousness following severe brain injury. This hypothesis states that the brain recovers from injury by restoring normal functional connections via alternate structural pathways that circumvent impaired white matter connections. The so-called network diffusion model, which relates an individual's structural and functional connectomes by assuming that functional activation diffuses along structural pathways, is used here to capture this functional rerouting. We jointly examined functional and structural connectomes extracted from MRIs of 12 healthy and 16 brain-injured subjects. Connectome properties were quantified via graph theoretic measures and network diffusion model parameters. While a few graph metrics showed groupwise differences, they did not correlate with patients' level of consciousness as measured by the Coma Recovery Scale — Revised. There was, however, a strong and significant partial Pearson's correlation (accounting for age and years post-injury between level of consciousness and network diffusion model propagation time (r = 0.76, p < 0.05, corrected, i.e. the time functional activation spends traversing the structural network. We concluded that functional rerouting via alternate (and less efficient pathways leads to increases in network diffusion model propagation time. Simulations of injury and recovery in healthy connectomes confirmed these results. This work establishes the feasibility for using the network diffusion model to capture network-level mechanisms in recovery of consciousness after severe brain injury.

  15. Through the Immune Looking Glass: A Model for Brain Memory Strategies.

    Science.gov (United States)

    Sánchez-Ramón, Silvia; Faure, Florence

    2016-01-01

    The immune system (IS) and the central nervous system (CNS) are complex cognitive networks involved in defining the identity (self) of the individual through recognition and memory processes that enable one to anticipate responses to stimuli. Brain memory has traditionally been classified as either implicit or explicit on psychological and anatomical grounds, with reminiscences of the evolutionarily-based innate-adaptive IS responses. Beyond the multineuronal networks of the CNS, we propose a theoretical model of brain memory integrating the CNS as a whole. This is achieved by analogical reasoning between the operational rules of recognition and memory processes in both systems, coupled to an evolutionary analysis. In this new model, the hippocampus is no longer specifically ascribed to explicit memory but rather it both becomes part of the innate (implicit) memory system and tightly controls the explicit memory system. Alike the antigen presenting cells for the IS, the hippocampus would integrate transient and pseudo-specific (i.e., danger-fear) memories and would drive the formation of long-term and highly specific or explicit memories (i.e., the taste of the Proust's madeleine cake) by the more complex and recent, evolutionarily speaking, neocortex. Experimental and clinical evidence is provided to support the model. We believe that the singularity of this model's approximation could help to gain a better understanding of the mechanisms operating in brain memory strategies from a large-scale network perspective.

  16. An analytical model for nanoparticles concentration resulting from infusion into poroelastic brain tissue.

    Science.gov (United States)

    Pizzichelli, G; Di Michele, F; Sinibaldi, E

    2016-02-01

    We consider the infusion of a diluted suspension of nanoparticles (NPs) into poroelastic brain tissue, in view of relevant biomedical applications such as intratumoral thermotherapy. Indeed, the high impact of the related pathologies motivates the development of advanced therapeutic approaches, whose design also benefits from theoretical models. This study provides an analytical expression for the time-dependent NPs concentration during the infusion into poroelastic brain tissue, which also accounts for particle binding onto cells (by recalling relevant results from the colloid filtration theory). Our model is computationally inexpensive and, compared to fully numerical approaches, permits to explicitly elucidate the role of the involved physical aspects (tissue poroelasticity, infusion parameters, NPs physico-chemical properties, NP-tissue interactions underlying binding). We also present illustrative results based on parameters taken from the literature, by considering clinically relevant ranges for the infusion parameters. Moreover, we thoroughly assess the model working assumptions besides discussing its limitations. While not laying any claims of generality, our model can be used to support the development of more ambitious numerical approaches, towards the preliminary design of novel therapies based on NPs infusion into brain tissue. Copyright © 2015 Elsevier Inc. All rights reserved.

  17. A Generative Probabilistic Model and Discriminative Extensions for Brain Lesion Segmentation - With Application to Tumor and Stroke

    DEFF Research Database (Denmark)

    Menze, Bjoern H.; Van Leemput, Koen; Lashkari, Danial

    2016-01-01

    We introduce a generative probabilistic model for segmentation of brain lesions in multi-dimensional images that generalizes the EM segmenter, a common approach for modelling brain images using Gaussian mixtures and a probabilistic tissue atlas that employs expectation-maximization (EM...... jointly from the image data. It delineates lesion areas individually in each channel, allowing for differences in lesion appearance across modalities, an important feature of many brain tumor imaging sequences. We also propose discriminative model extensions to map the output of the generative model...... patient scans, and multimodal brain images of patients with acute and subacute ischemic stroke. We find the generative model that has been designed for tumor lesions to generalize well to stroke images, and the extended discriminative-discriminative model to be one of the top ranking methods in the BRATS...

  18. Brain Inspired Cognitive Model with Attention for Self-Driving Cars

    OpenAIRE

    Chen, Shitao; Zhang, Songyi; Shang, Jinghao; Chen, Badong; Zheng, Nanning

    2017-01-01

    Perception-driven approach and end-to-end system are two major vision-based frameworks for self-driving cars. However, it is difficult to introduce attention and historical information of autonomous driving process, which are the essential factors for achieving human-like driving into these two methods. In this paper, we propose a novel model for self-driving cars named brain-inspired cognitive model with attention (CMA). This model consists of three parts: a convolutional neural network for ...

  19. Group-ICA model order highlights patterns of functional brain connectivity

    Directory of Open Access Journals (Sweden)

    Ahmed eAbou Elseoud

    2011-06-01

    Full Text Available Resting-state networks (RSNs can be reliably and reproducibly detected using independent component analysis (ICA at both individual subject and group levels. Altering ICA dimensionality (model order estimation can have a significant impact on the spatial characteristics of the RSNs as well as their parcellation into sub-networks. Recent evidence from several neuroimaging studies suggests that the human brain has a modular hierarchical organization which resembles the hierarchy depicted by different ICA model orders. We hypothesized that functional connectivity between-group differences measured with ICA might be affected by model order selection. We investigated differences in functional connectivity using so-called dual-regression as a function of ICA model order in a group of unmedicated seasonal affective disorder (SAD patients compared to normal healthy controls. The results showed that the detected disease-related differences in functional connectivity alter as a function of ICA model order. The volume of between-group differences altered significantly as a function of ICA model order reaching maximum at model order 70 (which seems to be an optimal point that conveys the largest between-group difference then stabilized afterwards. Our results show that fine-grained RSNs enable better detection of detailed disease-related functional connectivity changes. However, high model orders show an increased risk of false positives that needs to be overcome. Our findings suggest that multilevel ICA exploration of functional connectivity enables optimization of sensitivity to brain disorders.

  20. Brain Serotonin Transporter Binding In a Minipig Model of Parkinson's Disease

    DEFF Research Database (Denmark)

    Lillethorup, Thea Pinholt; Glud, Andreas Nørgaard; Sørensen, Jens Christian Hedemann

    Objectives: Some of the debilitating non-motor aspects of Parkinson’s disease (PD) are related to the serotonin system1. To investigate the involvement of the brain serotonergic system in a PD animal model, we measured the in vivo binding of [11C]-DASB to the serotonin transporter (SERT......) as a marker of serotonergic neurons. In this study, we use the in vivo capabilities of PET imaging to study serotonin neurotransmission in a minipig model of PD induced by the intracerebroventricular injection of lactacystin, an inhibitor of the ubiquitin proteasome system. Methods: Five female Göttingen....... Results: Lactacystin administration induced behavioural symptoms including weakness of hindlimbs and decreased motor activity. SERT binding potential was decreased by 35-40% in striatal brain regions and by 20% in thalamic regions compared to the baseline scans. Conclusions: Our imaging data suggests...

  1. Long-term BPA infusions. Evaluation in the rat brain tumor and rat spinal cord models

    International Nuclear Information System (INIS)

    Coderre, J.A.; Micca, P.L.; Nawrocky, M.M.; Joel, D.D.; Morris, G.M.

    2000-01-01

    In the BPA-based dose escalation clinical trial, the observations of tumor recurrence in areas of extremely high calculated tumor doses suggest that the BPA distribution is non-uniform. Longer (6-hour) i.v. infusions of BPA are evaluated in the rat brain tumor and spinal cord models to address the questions of whether long-term infusions are more effective against the tumor and whether long-term infusions are detrimental in the central nervous system. In the rat spinal cord, the 50% effective doses (ED 50 ) for myeloparesis were not significantly different after a single i.p. injection of BPA-fructose or a 6 hour i.v. infusion. In the rat 9L gliosarcoma brain tumor model, BNCT following 2-hr or 6-hr infusions of BPA-F produced similar levels of long term survival. (author)

  2. Implantation of glioblastoma spheroids into organotypic brain slice cultures as a model for investigating effects of irradiation

    DEFF Research Database (Denmark)

    Petterson, Stine Asferg; Jakobsen, Ida Pind; Jensen, Stine Skov

    2016-01-01

    Glioblastoma is the most frequent malignant brain tumor with an overall survival of only 14.6 months. Novel in vitro models preserving both tumor tissue and the interface between tumor and brain tissue are highly needed in order to develop novel efficient therapeutic strategies. Additionally, mod...

  3. Validation of In Vitro Cell-Based Human Blood-Brain Barrier Model Using Clinical Positron Emission Tomography Radioligands To Predict In Vivo Human Brain Penetration

    International Nuclear Information System (INIS)

    Mabondzo, A.; Guyot, A.C.; Bottlaender, M.; Deverre, J.R.; Tsaouin, K.; Balimane, P.V.

    2010-01-01

    We have evaluated a novel in vitro cell-based human blood-brain barrier (BBB) model that could predict in vivo human brain penetration for compounds with different BBB permeabilities using the clinical positron emission tomography (PET) data. Comparison studies were also performed to demonstrate that the in vitro cell-based human BBB model resulted in better predictivity over the traditional permeability model in discovery organizations, Caco-2 cells. We evaluated the in vivo BBB permeability of [ 18 F] and [ 11 C]-compounds in humans by PET imaging. The in vivo plasma-brain exchange parameters used for comparison were determined in humans by PET using a kinetic analysis of the radiotracer binding. For each radiotracer, the parameters were determined by fitting the brain kinetics of the radiotracer using a two-tissue compartment model of the ligand-receptor interaction. Bidirectional transport studies with the same compounds as in in vivo studies were carried out using the in vitro cell-based human BBB model as well as Caco-2 cells. The in vitro cell-based human BBB model has important features of the BBB in vivo and is suitable for discriminating between CNS and non-CNS marketed drugs. A very good correlation (r 2 =0.90; P≤0.001) was demonstrated between in vitro BBB permeability and in vivo permeability coefficient. In contrast, a poor correlation (r 2 = 0.17) was obtained between Caco-2 data and in vivo human brain penetration. This study highlights the potential of this in vitro cell-based human BBB model in drug discovery and shows that it can be an extremely effective screening tool for CNS programs. (authors)

  4. A novel technique of serial biopsy in mouse brain tumour models.

    Directory of Open Access Journals (Sweden)

    Sasha Rogers

    Full Text Available Biopsy is often used to investigate brain tumour-specific abnormalities so that treatments can be appropriately tailored. Dacomitinib (PF-00299804 is a tyrosine kinase inhibitor (TKI, which is predicted to only be effective in cancers where the targets of this drug (EGFR, ERBB2, ERBB4 are abnormally active. Here we describe a method by which serial biopsy can be used to validate response to dacomitinib treatment in vivo using a mouse glioblastoma model. In order to determine the feasibility of conducting serial brain biopsies in mouse models with minimal morbidity, and if successful, investigate whether this can facilitate evaluation of chemotherapeutic response, an orthotopic model of glioblastoma was used. Immunodeficient mice received cortical implants of the human glioblastoma cell line, U87MG, modified to express the constitutively-active EGFR mutant, EGFRvIII, GFP and luciferase. Tumour growth was monitored using bioluminescence imaging. Upon attainment of a moderate tumour size, free-hand biopsy was performed on a subgroup of animals. Animal monitoring using a neurological severity score (NSS showed that all mice survived the procedure with minimal perioperative morbidity and recovered to similar levels as controls over a period of five days. The technique was used to evaluate dacomitinib-mediated inhibition of EGFRvIII two hours after drug administration. We show that serial tissue samples can be obtained, that the samples retain histological features of the tumour, and are of sufficient quality to determine response to treatment. This approach represents a significant advance in murine brain surgery that may be applicable to other brain tumour models. Importantly, the methodology has the potential to accelerate the preclinical in vivo drug screening process.

  5. Diffuse and Focal Brain Injury in a Large Animal Model of PTE: Mechanisms Underlying Epileptogenesis

    Science.gov (United States)

    2017-10-01

    Conclusions: A) Contusion injury validation and neuropathology B) Grid electrode development and testing C) Wireless Large Animal Custom Enclosure...In addition, we will test the NF-L and GFAP immunoassay to begin quantification of this biomarkers, as well as collecting serum from the animals pre...AWARD NUMBER: W81XWH-16-1-0675 TITLE: Diffuse and Focal Brain Injury in a Large Animal Model of PTE: Mechanisms Underlying Epileptogenesis

  6. Differential Temporal Evolution Patterns in Brain Temperature in Different Ischemic Tissues in a Monkey Model of Middle Cerebral Artery Occlusion

    Directory of Open Access Journals (Sweden)

    Zhihua Sun

    2012-01-01

    Full Text Available Brain temperature is elevated in acute ischemic stroke, especially in the ischemic penumbra (IP. We attempted to investigate the dynamic evolution of brain temperature in different ischemic regions in a monkey model of middle cerebral artery occlusion. The brain temperature of different ischemic regions was measured with proton magnetic resonance spectroscopy (1H MRS, and the evolution processes of brain temperature were compared among different ischemic regions. We found that the normal (baseline brain temperature of the monkey brain was 37.16°C. In the artery occlusion stage, the mean brain temperature of ischemic tissue was 1.16°C higher than the baseline; however, this increase was region dependent, with 1.72°C in the IP, 1.08°C in the infarct core, and 0.62°C in the oligemic region. After recanalization, the brain temperature of the infarct core showed a pattern of an initial decrease accompanied by a subsequent increase. However, the brain temperature of the IP and oligemic region showed a monotonously and slowly decreased pattern. Our study suggests that in vivo measurement of brain temperature could help to identify whether ischemic tissue survives.

  7. Computational modelling of traumatic brain injury predicts the location of chronic traumatic encephalopathy pathology.

    Science.gov (United States)

    Ghajari, Mazdak; Hellyer, Peter J; Sharp, David J

    2017-02-01

    Traumatic brain injury can lead to the neurodegenerative disease chronic traumatic encephalopathy. This condition has a clear neuropathological definition but the relationship between the initial head impact and the pattern of progressive brain pathology is poorly understood. We test the hypothesis that mechanical strain and strain rate are greatest in sulci, where neuropathology is prominently seen in chronic traumatic encephalopathy, and whether human neuroimaging observations converge with computational predictions. Three distinct types of injury were simulated. Chronic traumatic encephalopathy can occur after sporting injuries, so we studied a helmet-to-helmet impact in an American football game. In addition, we investigated an occipital head impact due to a fall from ground level and a helmeted head impact in a road traffic accident involving a motorcycle and a car. A high fidelity 3D computational model of brain injury biomechanics was developed and the contours of strain and strain rate at the grey matter-white matter boundary were mapped. Diffusion tensor imaging abnormalities in a cohort of 97 traumatic brain injury patients were also mapped at the grey matter-white matter boundary. Fifty-one healthy subjects served as controls. The computational models predicted large strain most prominent at the depths of sulci. The volume fraction of sulcal regions exceeding brain injury thresholds were significantly larger than that of gyral regions. Strain and strain rates were highest for the road traffic accident and sporting injury. Strain was greater in the sulci for all injury types, but strain rate was greater only in the road traffic and sporting injuries. Diffusion tensor imaging showed converging imaging abnormalities within sulcal regions with a significant decrease in fractional anisotropy in the patient group compared to controls within the sulci. Our results show that brain tissue deformation induced by head impact loading is greatest in sulcal locations

  8. Increased blood-brain barrier vulnerability to systemic inflammation in an Alzheimer disease mouse model.

    Science.gov (United States)

    Takeda, Shuko; Sato, Naoyuki; Ikimura, Kazuko; Nishino, Hirohito; Rakugi, Hiromi; Morishita, Ryuichi

    2013-08-01

    Behavioral and psychological problems are often observed in patients with dementia such as that associated with Alzheimer disease, and these noncognitive symptoms place an extremely heavy burden on the family and caregivers. Although it is well know that these symptoms often are triggered by infection of peripheral organs, the underlying mechanisms for these pathological conditions are still unclear. In this study, using an Alzheimer amyloid precursor protein (APP)-transgenic mouse, we analyzed behavioral changes and brain inflammatory response induced by peripheral administration of lipopolysaccharide. Application of a unique in vivo microdialysis system revealed that the increase in brain inflammatory cytokine (interleukin-6) level was significantly higher in APP-Tg than in wild-type mice after peripheral lipopolysaccharide injection, which was associated with more severe sickness behaviors. The blood-brain barrier became more permeable in APP-Tg mice during peripherally evoked inflammation, suggesting the increased vulnerability of the blood-brain barrier to inflammation in this animal model of Alzheimer's disease. These findings might provide insight into the pathogenesis of noncognitive symptoms in dementia and a basis to develop new therapeutic treatments for them. Copyright © 2013 Elsevier Inc. All rights reserved.

  9. Novel active contour model based on multi-variate local Gaussian distribution for local segmentation of MR brain images

    Science.gov (United States)

    Zheng, Qiang; Li, Honglun; Fan, Baode; Wu, Shuanhu; Xu, Jindong

    2017-12-01

    Active contour model (ACM) has been one of the most widely utilized methods in magnetic resonance (MR) brain image segmentation because of its ability of capturing topology changes. However, most of the existing ACMs only consider single-slice information in MR brain image data, i.e., the information used in ACMs based segmentation method is extracted only from one slice of MR brain image, which cannot take full advantage of the adjacent slice images' information, and cannot satisfy the local segmentation of MR brain images. In this paper, a novel ACM is proposed to solve the problem discussed above, which is based on multi-variate local Gaussian distribution and combines the adjacent slice images' information in MR brain image data to satisfy segmentation. The segmentation is finally achieved through maximizing the likelihood estimation. Experiments demonstrate the advantages of the proposed ACM over the single-slice ACM in local segmentation of MR brain image series.

  10. Measurement and Finite Element Model Validation of Immature Porcine Brain-Skull Displacement during Rapid Sagittal Head Rotations.

    Science.gov (United States)

    Pasquesi, Stephanie A; Margulies, Susan S

    2018-01-01

    Computational models are valuable tools for studying tissue-level mechanisms of traumatic brain injury, but to produce more accurate estimates of tissue deformation, these models must be validated against experimental data. In this study, we present in situ measurements of brain-skull displacement in the neonatal piglet head ( n  = 3) at the sagittal midline during six rapid non-impact rotations (two rotations per specimen) with peak angular velocities averaging 51.7 ± 1.4 rad/s. Marks on the sagittally cut brain and skull/rigid potting surfaces were tracked, and peak values of relative brain-skull displacement were extracted and found to be significantly less than values extracted from a previous axial plane model. In a finite element model of the sagittally transected neonatal porcine head, the brain-skull boundary condition was matched to the measured physical experiment data. Despite smaller sagittal plane displacements at the brain-skull boundary, the corresponding finite element boundary condition optimized for sagittal plane rotations is far less stiff than its axial counterpart, likely due to the prominent role of the boundary geometry in restricting interface movement. Finally, bridging veins were included in the finite element model. Varying the bridging vein mechanical behavior over a previously reported range had no influence on the brain-skull boundary displacements. This direction-specific sagittal plane boundary condition can be employed in finite element models of rapid sagittal head rotations.

  11. Using stochastic language models (SLM) to map lexical, syntactic, and phonological information processing in the brain.

    Science.gov (United States)

    Lopopolo, Alessandro; Frank, Stefan L; van den Bosch, Antal; Willems, Roel M

    2017-01-01

    Language comprehension involves the simultaneous processing of information at the phonological, syntactic, and lexical level. We track these three distinct streams of information in the brain by using stochastic measures derived from computational language models to detect neural correlates of phoneme, part-of-speech, and word processing in an fMRI experiment. Probabilistic language models have proven to be useful tools for studying how language is processed as a sequence of symbols unfolding in time. Conditional probabilities between sequences of words are at the basis of probabilistic measures such as surprisal and perplexity which have been successfully used as predictors of several behavioural and neural correlates of sentence processing. Here we computed perplexity from sequences of words and their parts of speech, and their phonemic transcriptions. Brain activity time-locked to each word is regressed on the three model-derived measures. We observe that the brain keeps track of the statistical structure of lexical, syntactic and phonological information in distinct areas.

  12. Through the Immune Looking Glass: A Model for Brain Memory Strategies.

    Directory of Open Access Journals (Sweden)

    Silvia eSánchez-Ramón

    2016-02-01

    Full Text Available The immune system (IS and the central nervous system (CNS are complex cognitive networks involved in defining the identity (self of the individual through recognition and memory processes that enable one to anticipate responses to stimuli. Brain memory has traditionally been classified as either implicit or explicit on psychological and anatomical grounds, with reminiscences of the evolutionarily-based innate-adaptive IS responses. Beyond the multineuronal networks of the CNS, we propose a theoretical model of brain memory integrating the CNS as a whole. This is achieved by analogical reasoning between the operational rules of recognition and memory processes in both systems, coupled to an evolutionary analysis. In this new model, the hippocampus is no longer specifically ascribed to explicit memory but rather it both becomes part of the innate (implicit memory system and tightly controls the explicit memory system. Alike the antigen presenting cells for the IS, the hippocampus would integrate transient and pseudo-specific (i.e. danger-fear memories and would drive the formation of long-term and highly specific or explicit memories (i.e. the taste of the Proust’s madeleine cake by the more complex and recent, evolutionarily speaking, neocortex. Experimental and clinical evidence is provided to support the model. We believe that the singularity of this model’s approximation could help to gain a better understanding of the mechanisms operating in brain memory strategies from a large-scale network perspective.

  13. The bovine brain: an in vitro translational model in developmental neuroscience and neurodegenerative research.

    Directory of Open Access Journals (Sweden)

    Antonella ePeruffo

    2014-07-01

    Full Text Available Animal models provide convenient and clinically relevant tools in the research on neurodegenerative diseases. Studies on developmental disorders extensively rely on the use of laboratory rodents. The present mini-review proposes an alternative translational model, based on the use of fetal bovine brain tissue. The bovine (Bos taurus possesses a large and highly gyrencephalic brain and the long gestation period (41 weeks is comparable to the human pregnancy (38-40 weeks. Primary cultures obtained from fetal bovine brain constitute a validated in vitro model that allows examinations of neurons and/or glial cells under controlled and reproducible conditions. Physiological processes can be also studied on cultured bovine neural cells incubated with specific substrates or by electrically coupled electrolyte-oxide-semiconductor capacitors that permit direct recording from neuronal cells. Bovine neural cells and specific in vitro cell culture could be an alternative in comparative neuroscience and in neurodegenerative research, useful for studying development of normal and altered circuitry in a long gestation mammalian species. Use of bovine tissues would promote a substantial reduction in the use of laboratory animals.

  14. Microfluidic modeling of the effects of nanoparticles on the blood-brain barrier in flow

    Science.gov (United States)

    Schwait, Craig; Hartman, Ryan; Bao, Yuping; Xu, Yaolin

    2011-11-01

    The difficulty of diffusing drugs across the blood-brain barrier (BBB) has caused an impasse for many brain treatments. Nanoparticles (NPs), to which drugs can adsorb, attach, or be entrapped, have the potential to deliver drugs past the BBB. Before nanoparticles can be used, their effects on the BBB and brain must be ascertained. Previous steady-state studies fall short for closely modeling in vivo conditions . Convection of nanoparticles is ignored, and endothelial cells' (ECs) morphology differs based on loading conditions; in vitro loading with continuous flow exhibit ECs indicating a more similar in vivo phenotype. NPs interact with monocytes prior to the BBB, and their toxicity effects were measured in flow conditions using both Trypan Blue cell counting and cell proliferation assays. The microfluidic device designed to model the BBB contained a concentric PES hollow fiber porous membrane in PFA tubing. Full use of the device will include ECs adhered on the inner surface and astrocytes adhered to the outer surface of the PES membrane to model cerebrovascular capillaries. Funded by NSF REU Site 1062611.

  15. BrainSignals Revisited: Simplifying a Computational Model of Cerebral Physiology.

    Directory of Open Access Journals (Sweden)

    Matthew Caldwell

    Full Text Available Multimodal monitoring of brain state is important both for the investigation of healthy cerebral physiology and to inform clinical decision making in conditions of injury and disease. Near-infrared spectroscopy is an instrument modality that allows non-invasive measurement of several physiological variables of clinical interest, notably haemoglobin oxygenation and the redox state of the metabolic enzyme cytochrome c oxidase. Interpreting such measurements requires the integration of multiple signals from different sources to try to understand the physiological states giving rise to them. We have previously published several computational models to assist with such interpretation. Like many models in the realm of Systems Biology, these are complex and dependent on many parameters that can be difficult or impossible to measure precisely. Taking one such model, BrainSignals, as a starting point, we have developed several variant models in which specific regions of complexity are substituted with much simpler linear approximations. We demonstrate that model behaviour can be maintained whilst achieving a significant reduction in complexity, provided that the linearity assumptions hold. The simplified models have been tested for applicability with simulated data and experimental data from healthy adults undergoing a hypercapnia challenge, but relevance to different physiological and pathophysiological conditions will require specific testing. In conditions where the simplified models are applicable, their greater efficiency has potential to allow their use at the bedside to help interpret clinical data in near real-time.

  16. Epidemiology of Mild Traumatic Brain Injury with Intracranial Hemorrhage: Focusing Predictive Models for Neurosurgical Intervention.

    Science.gov (United States)

    Orlando, Alessandro; Levy, A Stewart; Carrick, Matthew M; Tanner, Allen; Mains, Charles W; Bar-Or, David

    2017-11-01

    To outline differences in neurosurgical intervention (NI) rates between intracranial hemorrhage (ICH) types in mild traumatic brain injuries and help identify which ICH types are most likely to benefit from creation of predictive models for NI. A multicenter retrospective study of adult patients spanning 3 years at 4 U.S. trauma centers was performed. Patients were included if they presented with mild traumatic brain injury (Glasgow Coma Scale score 13-15) with head CT scan positive for ICH. Patients were excluded for skull fractures, "unspecified hemorrhage," or coagulopathy. Primary outcome was NI. Stepwise multivariable logistic regression models were built to analyze the independent association between ICH variables and outcome measures. The study comprised 1876 patients. NI rate was 6.7%. There was a significant difference in rate of NI by ICH type. Subdural hematomas had the highest rate of NI (15.5%) and accounted for 78% of all NIs. Isolated subarachnoid hemorrhages had the lowest, nonzero, NI rate (0.19%). Logistic regression models identified ICH type as the most influential independent variable when examining NI. A model predicting NI for isolated subarachnoid hemorrhages would require 26,928 patients, but a model predicting NI for isolated subdural hematomas would require only 328 patients. This study highlighted disparate NI rates among ICH types in patients with mild traumatic brain injury and identified mild, isolated subdural hematomas as most appropriate for construction of predictive NI models. Increased health care efficiency will be driven by accurate understanding of risk, which can come only from accurate predictive models. Copyright © 2017 Elsevier Inc. All rights reserved.

  17. Exercise modulates redox-sensitive small GTPase activity in the brain microvasculature in a model of brain metastasis formation.

    Directory of Open Access Journals (Sweden)

    Gretchen Wolff

    Full Text Available Tumor cell extravasation into the brain requires passage through the blood-brain barrier (BBB. There is evidence that exercise can alter the oxidation status of the brain microvasculature and protect against tumor cell invasion into the brain, although the mechanisms are not well understood. In the current study, we focused on the role of microenvironment generated by exercise and metastasizing tumor cells at the levels of brain microvessels, influencing oxidative stress-mediated responses and activation of redox-sensitive small GTPases. Mature male mice were exercised for four weeks using a running wheel with the average voluntary running distance 9.0 ± 0.3 km/day. Mice were then infused with 1.0 × 10(6 D122 (murine Lewis lung carcinoma cells into the brain microvasculature, and euthanized either 48 hours (in short-term studies or 2-3 weeks (in long-term studies post tumor cell administration. A significant increase in the level of reactive oxygen species was observed following 48 hours or 3 weeks of tumor cells growth, which was accompanied by a reduction in MnSOD expression in the exercised mice. Activation of the small GTPase Rho was negatively correlated with running distance in the tumor cell infused mice. Together, these data suggest that exercise may play a significant role during aggressive metastatic invasion, especially at higher intensities in pre-trained individuals.

  18. Material characterization and computer model simulation of low density polyurethane foam used in a rodent traumatic brain injury model.

    Science.gov (United States)

    Zhang, Liying; Gurao, Manish; Yang, King H; King, Albert I

    2011-05-15

    Computer models of the head can be used to simulate the events associated with traumatic brain injury (TBI) and quantify biomechanical response within the brain. Marmarou's impact acceleration rodent model is a widely used experimental model of TBI mirroring axonal pathology in humans. The mechanical properties of the low density polyurethane (PU) foam, an essential piece of energy management used in Marmarou's impact device, has not been fully characterized. The foam used in Marmarou's device was tested at seven strain rates ranging from quasi-static to dynamic (0.014-42.86 s⁻¹) to quantify the stress-strain relationships in compression. Recovery rate of the foam after cyclic compression was also determined through the periods of recovery up to three weeks. The experimentally determined stress-strain curves were incorporated into a material model in an explicit Finite Element (FE) solver to validate the strain rate dependency of the FE foam model. Compression test results have shown that the foam used in the rodent impact acceleration model is strain rate dependent. The foam has been found to be reusable for multiple impacts. However the stress resistance of used foam is reduced to 70% of the new foam. The FU_CHANG_FOAM material model in an FE solver has been found to be adequate to simulate this rate sensitive foam. Copyright © 2011 Elsevier B.V. All rights reserved.

  19. Breeding novel solutions in the brain: a model of Darwinian neurodynamics.

    Science.gov (United States)

    Szilágyi, András; Zachar, István; Fedor, Anna; de Vladar, Harold P; Szathmáry, Eörs

    2016-01-01

    Background : The fact that surplus connections and neurons are pruned during development is well established. We complement this selectionist picture by a proof-of-principle model of evolutionary search in the brain, that accounts for new variations in theory space. We present a model for Darwinian evolutionary search for candidate solutions in the brain. Methods : We combine known components of the brain - recurrent neural networks (acting as attractors), the action selection loop and implicit working memory - to provide the appropriate Darwinian architecture. We employ a population of attractor networks with palimpsest memory. The action selection loop is employed with winners-share-all dynamics to select for candidate solutions that are transiently stored in implicit working memory. Results : We document two processes: selection of stored solutions and evolutionary search for novel solutions. During the replication of candidate solutions attractor networks occasionally produce recombinant patterns, increasing variation on which selection can act. Combinatorial search acts on multiplying units (activity patterns) with hereditary variation and novel variants appear due to (i) noisy recall of patterns from the attractor networks, (ii) noise during transmission of candidate solutions as messages between networks, and, (iii) spontaneously generated, untrained patterns in spurious attractors. Conclusions : Attractor dynamics of recurrent neural networks can be used to model Darwinian search. The proposed architecture can be used for fast search among stored solutions (by selection) and for evolutionary search when novel candidate solutions are generated in successive iterations. Since all the suggested components are present in advanced nervous systems, we hypothesize that the brain could implement a truly evolutionary combinatorial search system, capable of generating novel variants.

  20. The ex-illiterate brain: The critical period, cognitive reserve and HAROLD model

    Directory of Open Access Journals (Sweden)

    Maria Vania Silva Nunes

    Full Text Available Abstract The lifelong acquisition of cognitive skills shapes the biology of the brain. However, there are critical periods for the best use of the brain to process the acquired information. Objectives: To discuss the critical period of cognitive acquisition, the concept of cognitive reserve and the HAROLD (Hemispheric Asymmetry Reduction in Older adults model. Methods: Seven women who learned how to read and to write after the age of 50 (ex-illiterates and five women with 10 years of regular schooling (controls were submitted to a language recognition test while brain activity was being recorded using magnetoencephalography. Spoken words were delivered binaurally via two plastic tubs terminating in ear inserts, and recordings were made with a whole head magnetometer consisting of 148 magnetometer coils. Results: Both groups performed similarly on the task of identifying target words. Analysis of the number of sources of activity in the left and right hemispheres revealed significant differences between the two groups, showing that ex-illiterate subjects exhibited less brain functional asymmetry during the language task. Conclusions: These results should be interpreted with caution because the groups were small. However, these findings reinforce the concept that poorly educated subjects tend to use the brain for information processing in a different way to subjects with a high educational level or who were schooled at the regular time. Finally, the recruiting of both hemispheres to tackle the language recognition test occurred to a greater degree in the ex-illiterate group where this can be interpreted as a sign of difficulty performing the task.

  1. Reference Tracts and Generative Models for Brain White Matter Tractography †

    Directory of Open Access Journals (Sweden)

    Susana Muñoz Maniega

    2017-12-01

    Full Text Available Background: Probabilistic neighborhood tractography aims to automatically segment brain white matter tracts from diffusion magnetic resonance imaging (dMRI data in different individuals. It uses reference tracts as priors for the shape and length of the tract, and matching models that describe typical deviations from these. We evaluated new reference tracts and matching models derived from dMRI data acquired from 80 healthy volunteers, aged 25–64 years. Methods: The new reference tracts and models were tested in 50 healthy older people, aged 71.8 ± 0.4 years. The matching models were further assessed by sampling and visualizing synthetic tracts derived from them. Results: We found that data-generated reference tracts improved the success rate of automatic white matter tract segmentations. We observed an increased rate of visually acceptable tracts, and decreased variation in quantitative parameters when using this approach. Sampling from the matching models demonstrated their quality, independently of the testing data. Conclusions: We have improved the automatic segmentation of brain white matter tracts, and demonstrated that matching models can be successfully transferred to novel data. In many cases, this will bypass the need for training data and make the use of probabilistic neighborhood tractography in small testing datasets newly practicable.

  2. Blind Source Separation for Unimodal and Multimodal Brain Networks: A Unifying Framework for Subspace Modeling.

    Science.gov (United States)

    Silva, Rogers F; Plis, Sergey M; Sui, Jing; Pattichis, Marios S; Adalı, Tülay; Calhoun, Vince D

    2016-10-01

    In the past decade, numerous advances in the study of the human brain were fostered by successful applications of blind source separation (BSS) methods to a wide range of imaging modalities. The main focus has been on extracting "networks" represented as the underlying latent sources. While the broad success in learning latent representations from multiple datasets has promoted the wide presence of BSS in modern neuroscience, it also introduced a wide variety of objective functions, underlying graphical structures, and parameter constraints for each method. Such diversity, combined with a host of datatype-specific know-how, can cause a sense of disorder and confusion, hampering a practitioner's judgment and impeding further development. We organize the diverse landscape of BSS models by exposing its key features and combining them to establish a novel unifying view of the area. In the process, we unveil important connections among models according to their properties and subspace structures. Consequently, a high-level descriptive structure is exposed, ultimately helping practitioners select the right model for their applications. Equipped with that knowledge, we review the current state of BSS applications to neuroimaging. The gained insight into model connections elicits a broader sense of generalization, highlighting several directions for model development. In light of that, we discuss emerging multi-dataset multidimensional (MDM) models and summarize their benefits for the study of the healthy brain and disease-related changes.

  3. Levels of detail analysis of microwave scattering from human head models for brain stroke detection

    Directory of Open Access Journals (Sweden)

    Awais Munawar Qureshi

    2017-11-01

    Full Text Available In this paper, we have presented a microwave scattering analysis from multiple human head models. This study incorporates different levels of detail in the human head models and its effect on microwave scattering phenomenon. Two levels of detail are taken into account; (i Simplified ellipse shaped head model (ii Anatomically realistic head model, implemented using 2-D geometry. In addition, heterogenic and frequency-dispersive behavior of the brain tissues has also been incorporated in our head models. It is identified during this study that the microwave scattering phenomenon changes significantly once the complexity of head model is increased by incorporating more details using magnetic resonance imaging database. It is also found out that the microwave scattering results match in both types of head model (i.e., geometrically simple and anatomically realistic, once the measurements are made in the structurally simplified regions. However, the results diverge considerably in the complex areas of brain due to the arbitrary shape interface of tissue layers in the anatomically realistic head model. After incorporating various levels of detail, the solution of subject microwave scattering problem and the measurement of transmitted and backscattered signals were obtained using finite element method. Mesh convergence analysis was also performed to achieve error free results with a minimum number of mesh elements and a lesser degree of freedom in the fast computational time. The results were promising and the E-Field values converged for both simple and complex geometrical models. However, the E-Field difference between both types of head model at the same reference point differentiated a lot in terms of magnitude. At complex location, a high difference value of 0.04236 V/m was measured compared to the simple location, where it turned out to be 0.00197 V/m. This study also contributes to provide a comparison analysis between the direct and iterative

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

    Science.gov (United States)

    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.

  5. Brain MR image segmentation based on an improved active contour model.

    Directory of Open Access Journals (Sweden)

    Xiangrui Meng

    Full Text Available It is often a difficult task to accurately segment brain magnetic resonance (MR images with intensity in-homogeneity and noise. This paper introduces a novel level set method for simultaneous brain MR image segmentation and intensity inhomogeneity correction. To reduce the effect of noise, novel anisotropic spatial information, which can preserve more details of edges and corners, is proposed by incorporating the inner relationships among the neighbor pixels. Then the proposed energy function uses the multivariate Student's t-distribution to fit the distribution of the intensities of each tissue. Furthermore, the proposed model utilizes Hidden Markov random fields to model the spatial correlation between neigh-boring pixels/voxels. The means of the multivariate Student's t-distribution can be adaptively estimated by multiplying a bias field to reduce the effect of intensity inhomogeneity. In the end, we reconstructed the energy function to be convex and calculated it by using the Split Bregman method, which allows our framework for random initialization, thereby allowing fully automated applications. Our method can obtain the final result in less than 1 second for 2D image with size 256 × 256 and less than 300 seconds for 3D image with size 256 × 256 × 171. The proposed method was compared to other state-of-the-art segmentation methods using both synthetic and clinical brain MR images and increased the accuracies of the results more than 3%.

  6. Melatonin alleviates brain and peripheral tissue edema in a neonatal rat model of hypoxic-ischemic brain damage: the involvement of edema related proteins.

    Science.gov (United States)

    Xu, Li-Xiao; Lv, Yuan; Li, Yan-Hong; Ding, Xin; Wang, Ying; Han, Xing; Liu, Ming-Hua; Sun, Bin; Feng, Xing

    2017-03-28

    Previous studies have indicated edema may be involved in the pathophysiology following hypoxic-ischemic encephalopathy (HIE), and melatonin may exhibit neuro-protection against brain insults. However, little is known regarding the mechanisms that involve the protective effects of melatonin in the brain and peripheral tissues after HIE. The present study aimed to examine the effects of melatonin on multiple organs, and the expression of edema related proteins in a neonatal rat model of hypoxic-ischemic brain damage (HIBD). One hundred ninety-two neonatal rats were randomly divided into three subgroups that underwent a sham surgery or HIBD. After the HIBD or sham-injury, the rats received an intraperitoneal injection of melatonin or an equal volume vehicle, respectively. We investigated the effects of melatonin on brain, kidney, and colon edema via histological examination and the expression of edema related proteins, including AQP-4, ZO-1 and occludin, via qPCR and western blot. Our data indicated (1) Melatonin reduced the histological injury in the brain and peripheral organs induced by HIBD as assessed via H-E staining and transmission electron microscopy. (2) Melatonin alleviated the HIBD-induced cerebral edema characterized by increased brain water content. (3) HIBD induced significant changes of edema related proteins, such as AQP-4, ZO-1 and occludin, and these changes were partially reversed by melatonin treatment. These findings provide substantial evidence that melatonin treatment has protective effects on the brain and peripheral organs after HIBD, and the edema related proteins, AQP4, ZO-1, and occludin, may indirectly contribute tothe mechanism of the edema protection by melatonin.

  7. Commonality of neural representations of sentences across languages: Predicting brain activation during Portuguese sentence comprehension using an English-based model of brain function.

    Science.gov (United States)

    Yang, Ying; Wang, Jing; Bailer, Cyntia; Cherkassky, Vladimir; Just, Marcel Adam

    2017-02-01

    The aim of the study was to test the cross-language generative capability of a model that predicts neural activation patterns evoked by sentence reading, based on a semantic characterization of the sentence. In a previous study on English monolingual speakers (Wang et al., submitted), a computational model performed a mapping from a set of 42 concept-level semantic features (Neurally Plausible Semantic Features, NPSFs) as well as 6 thematic role markers to neural activation patterns (assessed with fMRI), to predict activation levels in a network of brain locations. The model used two types of information gained from the English-based fMRI data to predict the activation for individual sentences in Portuguese. First, it used the mapping weights from NPSFs to voxel activation levels derived from the model for English reading. Second, the brain locations for which the activation levels were predicted were derived from a factor analysis of the brain activation patterns during English reading. These meta-language locations were defined by the clusters of voxels with high loadings on each of the four main dimensions (factors), namely people, places, actions and feelings, underlying the neural representations of the stimulus sentences. This cross-language model succeeded in predicting the brain activation patterns associated with the reading of 60 individual Portuguese sentences that were entirely new to the model, attaining accuracies reliably above chance level. The prediction accuracy was not affected by whether the Portuguese speaker was monolingual or Portuguese-English bilingual. The model's confusion errors indicated an accurate capture of the events or states described in the sentence at a conceptual level. Overall, the cross-language predictive capability of the model demonstrates the neural commonality between speakers of different languages in the representations of everyday events and states, and provides an initial characterization of the common meta

  8. A model to guide the rehabilitation of high-functioning employees after mild brain injury.

    Science.gov (United States)

    Dodson, Matthew B

    2010-01-01

    Impairment in executive functioning can occur after mild stroke, mild Traumatic Brain Injury, and neurodegenerative disease, and this can have deleterious effects on employment outcomes, occupational functioning, and general quality of life. What is not as well identified is the symbiotic relationship between executive functioning and other important psychosocial constructs inherent in successful employees ("Employee Performance Enablers"), and how various aspects of the employment environment can enable or inhibit the success of the employee with executive functioning deficits in meeting their essential job functions ("Workplace Ecology"). From an extensive review of the literature and the author's practice experience, a clinical model was developed to elucidate these two critical variables, as well as to provide guidance for organizing, planning, and implementing interventions that will address both employee enablers and workplace ecology to affect positive return to work outcomes for individuals with mild brain injury.

  9. An Actor-Partner Interdependence Model of Acquired Brain Injury Patient Impairments and Caregiver Psychosocial Functioning

    DEFF Research Database (Denmark)

    Perrin, Paul B; Norup, Anne; Caracuel, Alfonso

    2017-01-01

    . METHOD: A sample of 968 individuals with ABI and their caregivers (n = 1,936) from 4 countries completed the European Brain Injury Questionnaire, a measure of ABI impairments and caregiver psychosocial functioning in the context of providing care for the person with ABI. RESULTS: An APIM with all......OBJECTIVE: The purpose of this study was to use actor-partner interdependence modeling (APIM) to examine the simultaneous effects of both acquired brain injury (ABI) patient and caregiver ratings of patient impairments on both patient and caregiver ratings of caregiver psychosocial dysfunction...... adequate or good fit indices found that patient ratings of their own impairments in the domains of social disadaptation and depression were uniquely and positively associated with patient ratings of caregiver psychosocial dysfunction, yet none of the patient ratings of their own impairments were uniquely...

  10. Brain MRI Tumor Detection using Active Contour Model and Local Image Fitting Energy

    Science.gov (United States)

    Nabizadeh, Nooshin; John, Nigel

    2014-03-01

    Automatic abnormality detection in Magnetic Resonance Imaging (MRI) is an important issue in many diagnostic and therapeutic applications. Here an automatic brain tumor detection method is introduced that uses T1-weighted images and K. Zhang et. al.'s active contour model driven by local image fitting (LIF) energy. Local image fitting energy obtains the local image information, which enables the algorithm to segment images with intensity inhomogeneities. Advantage of this method is that the LIF energy functional has less computational complexity than the local binary fitting (LBF) energy functional; moreover, it maintains the sub-pixel accuracy and boundary regularization properties. In Zhang's algorithm, a new level set method based on Gaussian filtering is used to implement the variational formulation, which is not only vigorous to prevent the energy functional from being trapped into local minimum, but also effective in keeping the level set function regular. Experiments show that the proposed method achieves high accuracy brain tumor segmentation results.

  11. Maternal separation as a model of brain-gut axis dysfunction.

    LENUS (Irish Health Repository)

    O'Mahony, Siobhain M

    2011-03-01

    Early life stress has been implicated in many psychiatric disorders ranging from depression to anxiety. Maternal separation in rodents is a well-studied model of early life stress. However, stress during this critical period also induces alterations in many systems throughout the body. Thus, a variety of other disorders that are associated with adverse early life events are often comorbid with psychiatric illnesses, suggesting a common underlying aetiology. Irritable bowel syndrome (IBS) is a functional gastrointestinal disorder that is thought to involve a dysfunctional interaction between the brain and the gut. Essential aspects of the brain-gut axis include spinal pathways, the hypothalamic pituitary adrenal axis, the immune system, as well as the enteric microbiota. Accumulating evidence suggest that stress, especially in early life, is a predisposing factor to IBS.

  12. 3D Segmentation of Rodent Brain Structures Using Hierarchical Shape Priors and Deformable Models

    Science.gov (United States)

    Zhang, Shaoting; Huang, Junzhou; Uzunbas, Mustafa; Shen, Tian; Delis, Foteini; Huang, Xiaolei; Volkow, Nora; Thanos, Panayotis; Metaxas, Dimitris N.

    2016-01-01

    In this paper, we propose a method to segment multiple rodent brain structures simultaneously. This method combines deformable models and hierarchical shape priors within one framework. The deformation module employs both gradient and appearance information to generate image forces to deform the shape. The shape prior module uses Principal Component Analysis to hierarchically model the multiple structures at both global and local levels. At the global level, the statistics of relative positions among different structures are modeled. At the local level, the shape statistics within each structure is learned from training samples. Our segmentation method adaptively employs both priors to constrain the intermediate deformation result. This prior constraint improves the robustness of the model and benefits the segmentation accuracy. Another merit of our prior module is that the size of the training data can be small, because the shape prior module models each structure individually and combines them using global statistics. This scheme can preserve shape details better than directly applying PCA on all structures. We use this method to segment rodent brain structures, such as the cerebellum, the left and right striatum, and the left and right hippocampus. The experiments show that our method works effectively and this hierarchical prior improves the segmentation performance. PMID:22003750

  13. Computational modeling of blast wave interaction with a human body and assessment of traumatic brain injury

    Science.gov (United States)

    Tan, X. G.; Przekwas, A. J.; Gupta, R. K.

    2017-11-01

    The modeling of human body biomechanics resulting from blast exposure poses great challenges because of the complex geometry and the substantial material heterogeneity. We developed a detailed human body finite element model representing both the geometry and the materials realistically. The model includes the detailed head (face, skull, brain and spinal cord), the neck, the skeleton, air cavities (lungs) and the tissues. Hence, it can be used to properly model the stress wave propagation in the human body subjected to blast loading. The blast loading on the human was generated from a simulated C4 explosion. We used the highly scalable solvers in the multi-physics code CoBi for both the blast simulation and the human body biomechanics. The meshes generated for these simulations are of good quality so that relatively large time-step sizes can be used without resorting to artificial time scaling treatments. The coupled gas dynamics and biomechanics solutions were validated against the shock tube test data. The human body models were used to conduct parametric simulations to find the biomechanical response and the brain injury mechanism due to blasts impacting the human body. Under the same blast loading condition, we showed the importance of inclusion of the whole body.

  14. A Simplified Model for Intravoxel Incoherent Motion Perfusion Imaging of the Brain.

    Science.gov (United States)

    Conklin, J; Heyn, C; Roux, M; Cerny, M; Wintermark, M; Federau, C

    2016-12-01

    Despite a recent resurgence, intravoxel incoherent motion MRI faces practical challenges, including limited SNR and demanding acquisition and postprocessing requirements. A simplified approach using linear fitting of a subset of higher b-values has seen success in other organ systems. We sought to validate this method for evaluation of brain pathology by comparing perfusion measurements using simplified linear fitting to conventional biexponential fitting. Forty-nine patients with gliomas and 17 with acute strokes underwent 3T MRI, including DWI with 16 b-values (range, 0-900 s/mm 2 ). Conventional intravoxel incoherent motion was performed using nonlinear fitting of the standard biexponential equation. Simplified intravoxel incoherent motion was performed using linear fitting of the log-normalized signal curves for subsets of b-values >200 s/mm 2 . Comparisons between ROIs (tumors, strokes, contralateral brain) and between models (biexponential and simplified linear) were performed by using 2-way ANOVA. The root mean square error and coefficient of determination (R 2 ) were computed for the simplified model, with biexponential fitting as the reference standard. Perfusion maps using simplified linear fitting were qualitatively similar to conventional biexponential fitting. The perfusion fraction was elevated in high-grade (n = 33) compared to low-grade (n = 16) gliomas and was reduced in strokes compared to the contralateral brain (P the number of b-values used for linear fitting resulted in reduced accuracy (higher root mean square error and lower R 2 ) compared with full biexponential fitting. Intravoxel incoherent motion perfusion imaging of common brain pathology can be performed by using simplified linear fitting, with preservation of clinically relevant perfusion information. © 2016 by American Journal of Neuroradiology.

  15. Hidden Markov event sequence models: toward unsupervised functional MRI brain mapping.

    Science.gov (United States)

    Faisan, Sylvain; Thoraval, Laurent; Armspach, Jean-Paul; Foucher, Jack R; Metz-Lutz, Marie-Noëlle; Heitz, Fabrice

    2005-01-01

    Most methods used in functional MRI (fMRI) brain mapping require restrictive assumptions about the shape and timing of the fMRI signal in activated voxels. Consequently, fMRI data may be partially and misleadingly characterized, leading to suboptimal or invalid inference. To limit these assumptions and to capture the broad range of possible activation patterns, a novel statistical fMRI brain mapping method is proposed. It relies on hidden semi-Markov event sequence models (HSMESMs), a special class of hidden Markov models (HMMs) dedicated to the modeling and analysis of event-based random processes. Activation detection is formulated in terms of time coupling between (1) the observed sequence of hemodynamic response onset (HRO) events detected in the voxel's fMRI signal and (2) the "hidden" sequence of task-induced neural activation onset (NAO) events underlying the HROs. Both event sequences are modeled within a single HSMESM. The resulting brain activation model is trained to automatically detect neural activity embedded in the input fMRI data set under analysis. The data sets considered in this article are threefold: synthetic epoch-related, real epoch-related (auditory lexical processing task), and real event-related (oddball detection task) fMRI data sets. Synthetic data: Activation detection results demonstrate the superiority of the HSMESM mapping method with respect to a standard implementation of the statistical parametric mapping (SPM) approach. They are also very close, sometimes equivalent, to those obtained with an "ideal" implementation of SPM in which the activation patterns synthesized are reused for analysis. The HSMESM method appears clearly insensitive to timing variations of the hemodynamic response and exhibits low sensitivity to fluctuations of its shape (unsustained activation during task). Real epoch-related data: HSMESM activation detection results compete with those obtained with SPM, without requiring any prior definition of the expected

  16. Optical scatter imaging of cellular and mitochondrial swelling in brain tissue models of stroke

    Science.gov (United States)

    Johnson, Lee James

    2001-08-01

    The severity of brain edema resulting from a stroke can determine a patient's survival and the extent of their recovery. Cellular swelling is the microscopic source of a significant part of brain edema. Mitochondrial swelling also appears to be a determining event in the death or survival of the cells that are injured during a stroke. Therapies for reducing brain edema are not effective in many cases and current treatments of stroke do not address mitochondrial swelling at all. This dissertation is motivated by the lack of a complete understanding of cellular swelling resulting from stroke and the lack of a good method to begin to study mitochondrial swelling resulting from stroke in living brain tissue. In this dissertation, a novel method of detecting mitochondrial and cellular swelling in living hippocampal slices is developed and validated. The system is used to obtain spatial and temporal information about cellular and mitochondrial swelling resulting from various models of stroke. The effect of changes in water content on light scatter and absorption are examined in two models of brain edema. The results of this study demonstrate that optical techniques can be used to detect changes in water content. Mie scatter theory, the theoretical basis of the dual- angle scatter ratio imaging system, is presented. Computer simulations based on Mie scatter theory are used to determine the optimal angles for imaging. A detailed account of the early systems is presented to explain the motivations for the system design, especially polarization, wavelength and light path. Mitochondrial sized latex particles are used to determine the system response to changes in scattering particle size and concentration. The dual-angle scatter ratio imaging system is used to distinguish between osmotic and excitotoxic models of stroke injury. Such distinction cannot be achieved using the current techniques to study cellular swelling in hippocampal slices. The change in the scatter ratio is

  17. A high-capacity model for one shot association learning in the brain

    Directory of Open Access Journals (Sweden)

    Hafsteinn eEinarsson

    2014-11-01

    Full Text Available We present a high-capacity model for one-shot association learning(hetero-associative memory in sparse networks. We assume that basic patternsare pre-learned in networks and associations between two patterns are presentedonly once and have to be learned immediately. The model is a combination of anAmit-Fusi like network sparsely connected to a Willshaw type network. Thelearning procedure is palimpsest and comes from earlier work on one-shotpattern learning. However, in our setup we can enhance the capacity of thenetwork by iterative retrieval. This yields a model for sparse brain-likenetworks in which populations of a few thousand neurons are capable of learninghundreds of associations even if they are presented only once. The analysis ofthe model is based on a novel result by Janson et. al. on bootstrappercolation in random graphs.

  18. Altered brain functional connectivity and behaviour in a mouse model of maternal alcohol binge-drinking.

    Science.gov (United States)

    Cantacorps, Lídia; González-Pardo, Héctor; Arias, Jorge L; Valverde, Olga; Conejo, Nélida M

    2018-03-08

    Prenatal and perinatal alcohol exposure caused by maternal alcohol intake during gestation and lactation periods can have long-lasting detrimental effects on the brain development and behaviour of offspring. Children diagnosed with Foetal Alcohol Spectrum Disorders (FASD) display a wide range of cognitive, emotional and motor deficits, together with characteristic morphological abnormalities. Maternal alcohol binge drinking is particularly harmful for foetal and early postnatal brain development, as it involves exposure to high levels of alcohol over short periods of time. However, little is known about the long-term effects of maternal alcohol binge drinking on brain function and behaviour. To address this issue, we used pregnant C57BL/6 female mice with time-limited access to a 20% v/v alcohol solution as a procedure to model alcohol binge drinking during gestation and lactational periods. Male offspring were behaviourally tested during adolescence (30 days) and adulthood (60 days), and baseline neural metabolic capacity of brain regions sensitive to alcohol effects were also evaluated in adult animals from both groups. Our results show that prenatal and postnatal alcohol exposure caused age-dependent changes in spontaneous locomotor activity, increased anxiety-like behaviour and attenuated alcohol-induced conditioned place preference in adults. Also, significant changes in neural metabolic capacity using cytochrome c oxidase (CCO) quantitative histochemistry were found in the hippocampal dentate gyrus, the mammillary bodies, the ventral tegmental area, the lateral habenula and the central lobules of the cerebellum in adult mice with prenatal and postnatal alcohol exposure. In addition, the analysis of interregional CCO activity correlations in alcohol-exposed adult mice showed disrupted functional brain connectivity involving the limbic, brainstem, and cerebellar regions. Finally, increased neurogenesis was found in the dentate gyrus of the hippocampus of

  19. TU-G-210-01: Modeling for Breast and Brain HIFU Treatment Planning

    International Nuclear Information System (INIS)

    Christensen, D.

    2015-01-01

    Modeling can play a vital role in predicting, optimizing and analyzing the results of therapeutic ultrasound treatments. Simulating the propagating acoustic beam in various targeted regions of the body allows for the prediction of the resulting power deposition and temperature profiles. In this session we will apply various modeling approaches to breast, abdominal organ and brain treatments. Of particular interest is the effectiveness of procedures for correcting for phase aberrations caused by intervening irregular tissues, such as the skull in transcranial applications or inhomogeneous breast tissues. Also described are methods to compensate for motion in targeted abdominal organs such as the liver or kidney. Douglas Christensen – Modeling for Breast and Brain HIFU Treatment Planning Tobias Preusser – TRANS-FUSIMO – An Integrative Approach to Model-Based Treatment Planning of Liver FUS Tobias Preusser – TRANS-FUSIMO – An Integrative Approach to Model-Based Treatment Planning of Liver FUS Learning Objectives: Understand the role of acoustic beam modeling for predicting the effectiveness of therapeutic ultrasound treatments. Apply acoustic modeling to specific breast, liver, kidney and transcranial anatomies. Determine how to obtain appropriate acoustic modeling parameters from clinical images. Understand the separate role of absorption and scattering in energy delivery to tissues. See how organ motion can be compensated for in ultrasound therapies. Compare simulated data with clinical temperature measurements in transcranial applications. Supported by NIH R01 HL172787 and R01 EB013433 (DC); EU Seventh Framework Programme (FP7/2007-2013) under 270186 (FUSIMO) and 611889 (TRANS-FUSIMO)(TP); and P01 CA159992, GE, FUSF and InSightec (UV)

  20. TU-G-210-01: Modeling for Breast and Brain HIFU Treatment Planning

    Energy Technology Data Exchange (ETDEWEB)

    Christensen, D. [University of Utah (United States)

    2015-06-15

    Modeling can play a vital role in predicting, optimizing and analyzing the results of therapeutic ultrasound treatments. Simulating the propagating acoustic beam in various targeted regions of the body allows for the prediction of the resulting power deposition and temperature profiles. In this session we will apply various modeling approaches to breast, abdominal organ and brain treatments. Of particular interest is the effectiveness of procedures for correcting for phase aberrations caused by intervening irregular tissues, such as the skull in transcranial applications or inhomogeneous breast tissues. Also described are methods to compensate for motion in targeted abdominal organs such as the liver or kidney. Douglas Christensen – Modeling for Breast and Brain HIFU Treatment Planning Tobias Preusser – TRANS-FUSIMO – An Integrative Approach to Model-Based Treatment Planning of Liver FUS Tobias Preusser – TRANS-FUSIMO – An Integrative Approach to Model-Based Treatment Planning of Liver FUS Learning Objectives: Understand the role of acoustic beam modeling for predicting the effectiveness of therapeutic ultrasound treatments. Apply acoustic modeling to specific breast, liver, kidney and transcranial anatomies. Determine how to obtain appropriate acoustic modeling parameters from clinical images. Understand the separate role of absorption and scattering in energy delivery to tissues. See how organ motion can be compensated for in ultrasound therapies. Compare simulated data with clinical temperature measurements in transcranial applications. Supported by NIH R01 HL172787 and R01 EB013433 (DC); EU Seventh Framework Programme (FP7/2007-2013) under 270186 (FUSIMO) and 611889 (TRANS-FUSIMO)(TP); and P01 CA159992, GE, FUSF and InSightec (UV)

  1. Effects of early life adverse experiences on brain activity: Implications from maternal separation models in rodents

    Directory of Open Access Journals (Sweden)

    Mayumi eNishi

    2014-06-01

    Full Text Available During postnatal development, adverse early life experiences can affect the formation of neuronal circuits and exert long-lasting influences on neural function. Many studies have shown that daily repeated MS, an animal model of early life stress, can modulate the hypothalamic-pituitary-adrenal axis (HPA axis and can affect subsequent brain function and emotional behavior during adulthood. However, the molecular basis of the long-lasting effects of early life stress on brain function has not been completely elucidated. In this review, we introduce various cases of MS in rodents and illustrate the alterations in HPA axis activity by focusing on corticosterone (CORT, an end product of the HPA axis in rodents. We then present a characterization of the brain regions affected by various patterns of MS, including repeated MS and single time MS at various stages before weaning, by investigating c-Fos expression, a biological marker of neuronal activity. These CORT and c-Fos studies suggest that repeated early life stress may affect neuronal function in region- and temporal-specific manners, indicating a critical period for habituation to early life stress. Next, we discuss how early life stress can impact behavior, namely by inducing depression, anxiety or eating disorders. Furthermore, alterations in gene expression in adult mice exposed to MS, especially epigenetic changes of DNA methylation, are discussed.

  2. Pathological Deformations of Brain Vascular System Modelling Using Analogous Eletromagnetic Systems

    Directory of Open Access Journals (Sweden)

    Klara Capova

    2004-01-01

    Full Text Available The contribution deals with the modelling and simulation of human brain haemodynamics using analogous electromagnetic systems characteristic especially propagation properties of distributed parameters circuits. The cascade connection of analogical transmission line elements represents the vascular tree both from the point of the parameters and the topology as well. In the paper there are presented simulation examples of the healthy cerebral system mainly in the big arteries in comparing with the pathologically changed ones. The various degrees of stenosis are considered for the simulations of blood pressure and blood flow velocity and the results are compared with the healthy arteries. According to the last investigations the pathological deformations of brain arteries are th most frequently reasons of deaths in the world. The stenoses or aneurysms change the physical properties of arteries and they follow insufficient vascularisation of the brain. These computer-aided non-invasive methods together with the non-invasive experimental techniques represent a helpful tool both for the diagnostics and the treatment of vascular pathological deformations.

  3. Effects of early life stress on brain activity: implications from maternal separation model in rodents.

    Science.gov (United States)

    Nishi, Mayumi; Horii-Hayashi, Noriko; Sasagawa, Takayo; Matsunaga, Wataru

    2013-01-15

    Adverse experiences in early life can affect the formation of neuronal circuits during postnatal development and exert long-lasting influences on neural function. Many studies have shown that daily repeated maternal separation (RMS), an animal model of early life stress, can modulate the hypothalamic-pituitary-adrenal axis (HPA-axis) and can affect subsequent brain function and emotional behavior during adulthood. However, the molecular basis of the long-lasting effects of early life stress on brain function has not been completely elucidated. In this mini-review, we introduce various cases of maternal separation in rodents and illustrate the alterations in HPA-axis activity by focusing on corticosterone (CORT), an end-product of the HPA-axis in rodents. We then present the characterization of the brain regions affected by various patterns of MS, including RMS and single time maternal separation (SMS) at various stages before weaning, by investigating c-Fos expression, a biological marker of neuronal activity. These CORT and c-Fos studies suggest that repeated early life stress may affect neuronal function in region- and temporal-specific manners, indicating a critical period for habituation to early life stress. Furthermore, we introduce changes in behavioral aspects and gene expression in adult mice exposed to RMS. Copyright © 2012 Elsevier Inc. All rights reserved.

  4. Pattern Discovery in Brain Imaging Genetics via SCCA Modeling with a Generic Non-convex Penalty.

    Science.gov (United States)

    Du, Lei; Liu, Kefei; Yao, Xiaohui; Yan, Jingwen; Risacher, Shannon L; Han, Junwei; Guo, Lei; Saykin, Andrew J; Shen, Li

    2017-10-25

    Brain imaging genetics intends to uncover associations between genetic markers and neuroimaging quantitative traits. Sparse canonical correlation analysis (SCCA) can discover bi-multivariate associations and select relevant features, and is becoming popular in imaging genetic studies. The L1-norm function is not only convex, but also singular at the origin, which is a necessary condition for sparsity. Thus most SCCA methods impose [Formula: see text]-norm onto the individual feature or the structure level of features to pursuit corresponding sparsity. However, the [Formula: see text]-norm penalty over-penalizes large coefficients and may incurs estimation bias. A number of non-convex penalties are proposed to reduce the estimation bias in regression tasks. But using them in SCCA remains largely unexplored. In this paper, we design a unified non-convex SCCA model, based on seven non-convex functions, for unbiased estimation and stable feature selection simultaneously. We also propose an efficient optimization algorithm. The proposed method obtains both higher correlation coefficients and better canonical loading patterns. Specifically, these SCCA methods with non-convex penalties discover a strong association between the APOE e4 rs429358 SNP and the hippocampus region of the brain. They both are Alzheimer's disease related biomarkers, indicating the potential and power of the non-convex methods in brain imaging genetics.

  5. Gaussian mixture models and semantic gating improve reconstructions from human brain activity

    Directory of Open Access Journals (Sweden)

    Sanne eSchoenmakers

    2015-01-01

    Full Text Available Better acquisition protocols and analysis techniques are making it possible to use fMRI to obtain highly detailed visualizations of brain processes. In particular we focus on the reconstruction of natural images from BOLD responses in visual cortex. We expand our linear Gaussian framework for percept decoding with Gaussian mixture models to better represent the prior distribution of natural images. Reconstruction of such images then boils down to probabilistic inference in a hybrid Bayesian network. In our set-up, different mixture components correspond to different character categories. Our framework can automatically infer higher-order semantic categories from lower-level brain areas. Furthermore the framework can gate semantic information from higher-order brain areas to enforce the correct category during reconstruction. When categorical information is not available, we show that automatically learned clusters in the data give a similar improvement in reconstruction. The hybrid Bayesian network leads to highly accurate reconstructions in both supervised and unsupervised settings.

  6. Gut-brain and brain-gut axis in Parkinson's disease models : Effects of a uridine and fish oil diet

    NARCIS (Netherlands)

    Perez-Pardo, Paula; Dodiya, Hemraj B.; Broersen, Laus M; Douna, Hidde; van Wijk, Nick; Lopes da Silva, Sofia; Garssen, Johan; Keshavarzian, Ali; Kraneveld, Aletta D

    2017-01-01

    Recent investigations have focused on the potential role of gastrointestinal (GI) abnormalities in the pathogenesis of Parkinson's disease (PD). The 'dual-hit' hypothesis of PD speculates that a putative pathogen enters the brain via two routes: the olfactory system and the GI system. Here, we

  7. Consciousness, the brain, and spacetime geometry: an addendum. Some new developments on the Orch OR model for consciousness.

    Science.gov (United States)

    Penrose, R

    2001-04-01

    Brain action is both physically controlled and beyond computational simulation. Accordingly, there is a strong case for examining brain organization in a way that specifically seeks out structures in the brain that might plausibly support such putative non-computational action at the ill-understood borderline between quantum and classical physics. Thus, we must seek out structures in the brain where the actual physics that operates at this level could plausibly have important influence on brain action. This is the basis of the Orch-OR model that Stuart Hameroff and I have been proposing, and which he describes in the foregoing article. The case is strongly put forward that the neuronal microtubules play a key role in the required quantum/classical borderline activities which might have an essential relevance to the phenomenon of consciousness. The exploration of such deeper level of neuronal structure and function is very much a continuation of the line of work so wonderfully initiated by Cajal.

  8. How Anatomy Shapes Dynamics: A Semi-Analytical Study of the Brain at Rest by a Simple Spin Model

    Directory of Open Access Journals (Sweden)

    Gustavo eDeco

    2012-09-01

    Full Text Available Resting state networks show a surprisingly coherent and robust spatiotemporal organization. Previous theoretical studies demonstrated that these patterns can be understood as emergent on the basis of the underlying neuroanatomical connectivity skeleton. Integrating the biologically realistic DTI/DSI based neuroanatomical connectivity into a brain model of Ising spin dynamics, we found the presence of latent ghost multi-stable attractors, which can be studied analytically. The multistable attractor landscape defines a functionally meaningful dynamic repertoire of the brain network that is inherently present in the neuroanatomical connectivity. We demonstrate that the more entropy of attractors exists, the richer is the dynamical repertoire and consequently the brain network displays more capabilities of computation. We hypothesize therefore that human brain connectivity developed a scale free type of architecture in order to be able to store a large number of different and flexibly accessible brain functions

  9. How anatomy shapes dynamics: a semi-analytical study of the brain at rest by a simple spin model.

    Science.gov (United States)

    Deco, Gustavo; Senden, Mario; Jirsa, Viktor

    2012-01-01

    Resting state networks (RSNs) show a surprisingly coherent and robust spatiotemporal organization. Previous theoretical studies demonstrated that these patterns can be understood as emergent on the basis of the underlying neuroanatomical connectivity skeleton. Integrating the biologically realistic DTI/DSI-(Diffusion Tensor Imaging/Diffusion Spectrum Imaging)based neuroanatomical connectivity into a brain model of Ising spin dynamics, we found a system with multiple attractors, which can be studied analytically. The multistable attractor landscape thus defines a functionally meaningful dynamic repertoire of the brain network that is inherently present in the neuroanatomical connectivity. We demonstrate that the more entropy of attractors exists, the richer is the dynamical repertoire and consequently the brain network displays more capabilities of computation. We hypothesize therefore that human brain connectivity developed a scale free type of architecture in order to be able to store a large number of different and flexibly accessible brain functions.

  10. Chronic Hypopituitarism Associated with Increased Postconcussive Symptoms Is Prevalent after Blast-Induced Mild Traumatic Brain Injury

    Directory of Open Access Journals (Sweden)

    Arundhati Undurti

    2018-02-01

    Full Text Available The most frequent injury sustained by US service members deployed to Iraq or Afghanistan is mild traumatic brain injuries (mTBI, or concussion, by far most often caused by blast waves from improvised explosive devices or other explosive ordnance. TBI from all causes gives rise to chronic neuroendocrine disorders with an estimated prevalence of 25–50%. The current study expands upon our earlier finding that chronic pituitary gland dysfunction occurs with a similarly high frequency after blast-related concussions. We measured circulating hormone levels and accessed demographic and testing data from two groups of male veterans with hazardous duty experience in Iraq or Afghanistan. Veterans in the mTBI group had experienced one or more blast-related concussion. Members of the deployment control (DC group encountered similar deployment conditions but had no history of blast-related mTBI. 12 of 39 (31% of the mTBI participants and 3 of 20 (15% veterans in the DC group screened positive for one or more neuroendocrine disorders. Positive screens for growth hormone deficiency occurred most often. Analysis of responses on self-report questionnaires revealed main effects of both mTBI and hypopituitarism on postconcussive and posttraumatic stress disorder (PTSD symptoms. Symptoms associated with pituitary dysfunction overlap considerably with those of PTSD. They include cognitive deficiencies, mood and anxiety disorders, sleep problems, diminished quality of life, deleterious changes in metabolism and body composition, and increased cardiovascular mortality. When such symptoms are due to hypopituitarism, they may be alleviated by hormone replacement. These findings suggest consideration of routine post-deployment neuroendocrine screening of service members and veterans who have experienced blast-related mTBI and are reporting postconcussive symptoms.

  11. Region-specific tauopathy and synucleinopathy in brain of the alpha-synuclein overexpressing mouse model of Parkinson's disease

    Directory of Open Access Journals (Sweden)

    Masliah Eliezer

    2011-08-01

    Full Text Available Abstract Background α-synuclein [α-Syn]-mediated activation of GSK-3β leading to increases in hyperphosphorylated Tau has been shown by us to occur in striata of Parkinson's diseased [PD] patients and in animal models of PD. In Alzheimer's disease, tauopathy exists in several brain regions; however, the pattern of distribution of tauopathy in other brain regions of PD or in animal models of PD is not known. The current studies were undertaken to analyze the distribution of tauopathy in different brain regions in a widely used mouse model of PD, the α-Syn overexpressing mouse. Results High levels of α-Syn levels were seen in the brain stem, with a much smaller increase in the frontal cortex; neither cerebellum nor hippocampus showed any overexpression of α-Syn. Elevated levels of p-Tau, hyperphosphorylated at Ser202, Ser262 and Ser396/404, were seen in brain stem, with lower levels seen in hippocampus. In both frontal cortex and cerebellum, increases were seen only in p-Ser396/404 Tau, but not in p-Ser202 and p-Ser262. p-GSK-3β levels were not elevated in any of the brain regions, although total GSK-3β was elevated in brain stem. p-p38MAPK levels were unchanged in all brain regions examined, while p-ERK levels were elevated in brain stem, hippocampus and cerebellum, but not the frontal cortex. p-JNK levels were increased in brain stem and cerebellum but not in the frontal cortex or hippocampus. Elevated levels of free tubulin, indicating microtubule destabilization, were seen only in the brain stem. Conclusion Our combined data suggest that in this animal model of PD, tauopathy, along with microtubule destabilization, exists primarily in the brain stem and striatum, which are also the two major brain regions known to express high levels of α-Syn and undergo the highest levels of degeneration in human PD. Thus, tauopathy in PD may have a very restricted pattern of distribution.

  12. Theoretical Compartment Modeling of DCE-MRI Data Based on the Transport across Physiological Barriers in the Brain

    Directory of Open Access Journals (Sweden)

    Laura Fanea

    2012-01-01

    Full Text Available Neurological disorders represent major causes of lost years of healthy life and mortality worldwide. Development of their quantitative interdisciplinary in vivo evaluation is required. Compartment modeling (CM of brain data acquired in vivo using magnetic resonance imaging techniques with clinically available contrast agents can be performed to quantitatively assess brain perfusion. Transport of 1H spins in water molecules across physiological compartmental brain barriers in three different pools was mathematically modeled and theoretically evaluated in this paper and the corresponding theoretical compartment modeling of dynamic contrast enhanced magnetic resonance imaging (DCE-MRI data was analyzed. The pools considered were blood, tissue, and cerebrospinal fluid (CSF. The blood and CSF data were mathematically modeled assuming continuous flow of the 1H spins in these pools. Tissue data was modeled using three CMs. Results in this paper show that transport across physiological brain barriers such as the blood to brain barrier, the extracellular space to the intracellular space barrier, or the blood to CSF barrier can be evaluated quantitatively. Statistical evaluations of this quantitative information may be performed to assess tissue perfusion, barriers' integrity, and CSF flow in vivo in the normal or disease-affected brain or to assess response to therapy.

  13. Modeling the effects of age and gender on normal pediatric brain metabolism using F18-FDG PET/CT.

    Science.gov (United States)

    Turpin, Sophie; Martineau, Patrick J; Levasseur, Marc-André; Lambert, Raymond

    2017-12-28

    Normal databases of pediatric brain metabolism are uncommon, as local brain metabolism evolves significantly with age throughout childhood, limiting their clinical applicability. The aim of this study was to develop mathematical models of regional relative brain metabolism (RRBM) using pediatric F18-FluoroDeoxyGlucose (FDG) Positron Emission Tomography (PET) with Computed Tomography (CT) data of normal pediatric brains, accounting for gender and age. Methods: PET/CT brain acquisitions were obtained from 88 neurologically-normal subjects, aged 6 months to 18 years. Subjects were assigned to either development ( n = 59) or validation groups ( n = 29). For each subject, commercially available software (NeuroQTM) was used to quantify the relative metabolism of 47 separate brain regions using whole-brain normalized (WBN) and pons normalized (PN) activity. The effects of age on RRBM were modeled using multiple linear and non-linear mathematical equations and the significance of gender was assessed using the Student t-test. Optimal models were selected using the Akaike Information Criterion. Mean predicted values and 95% prediction intervals were derived for all regions. Model predictions were compared to the validation data set and mean predicted error was calculated for all regions using both WBN and PN models. Results: As a function of age, optimal models of RRBM were linear for 7 regions, quadratic for 13, cubic for 6, logarithmic for 12, power for 7, and modified power laws for 4regions using WBN data; linearfor 9 regions, quadratic for 27, cubic for 2, logarithmic for 5 and power for 2 using PN data. Gender differences were found to be statistically significant only in the posterior cingulate cortex for the WBN data. Comparing our models to the validation group resulted in 94.3% of regions falling within the 95% prediction interval for WBN and 94.1% for PN. For all the brain regions in the validation group, the percentage of error in prediction was 3 ± 0.96% using

  14. Cognitive-motivational interactions: beyond boxes-and-arrows models of the mind-brain.

    Science.gov (United States)

    Pessoa, Luiz

    2017-09-01

    How do motivation and cognitive control interact in brain and behavior? The past decade has witnessed a steady growth in studies investigating both the behavioral and the brain basis of these interactions. In this paper, I describe such interactions in the context of the dual completion model, which proposes that motivational significance influences both perceptual and executive competition. Embracing a research agenda that attempts to understand cognition-motivation interactions highlights considerable challenges faced by investigators. For example, even the standard language utilized, with terms such as "perception," "attention," "cognition," and "motivation," encourages a modular-like conceptualization of the underlying processes and mechanisms. I propose that large-scale interactions involving both task-related and valuation-related networks help understand how motivation shapes executive function. I argue that, ultimately, the mind and brain sciences need to move beyond "boxes and arrows" and fully embrace the richness and complexity of the interactions between motivation and cognition. In the last 10 years, the study in humans of the interactions of motivation with perception and cognition has grown at a fast pace. The growth has included behavioral studies characterizing the processes involved, and neuroimaging studies investigating the regions and circuits underlying the behaviors in question. This literature acknowledges the fact that perception and cognition do not happen in a vacuum but are, instead, situated in contexts that feature value . Although this assertion is uncontroversial, the mind and brain sciences have studied perception and cognition for many decades by largely extricating value from them. Fortunately, this state of affairs has now changed and the field has a newfound vigor in attempting to understand the impact of motivation on these mental functions.

  15. Developing Enhanced Blood–Brain Barrier Permeability Models: Integrating External Bio-Assay Data in QSAR Modeling

    Science.gov (United States)

    Wang, Wenyi; Kim, Marlene T.; Sedykh, Alexander

    2015-01-01

    Purpose Experimental Blood–Brain Barrier (BBB) permeability models for drug molecules are expensive and time-consuming. As alternative methods, several traditional Quantitative Structure-Activity Relationship (QSAR) models have been developed previously. In this study, we aimed to improve the predictivity of traditional QSAR BBB permeability models by employing relevant public bio-assay data in the modeling process. Methods We compiled a BBB permeability database consisting of 439 unique compounds from various resources. The database was split into a modeling set of 341 compounds and a validation set of 98 compounds. Consensus QSAR modeling workflow was employed on the modeling set to develop various QSAR models. A five-fold cross-validation approach was used to validate the developed models, and the resulting models were used to predict the external validation set compounds. Furthermore, we used previously published membrane transporter models to generate relevant transporter profiles for target compounds. The transporter profiles were used as additional biological descriptors to develop hybrid QSAR BBB models. Results The consensus QSAR models have R2=0.638 for fivefold cross-validation and R2=0.504 for external validation. The consensus model developed by pooling chemical and transporter descriptors showed better predictivity (R2=0.646 for five-fold cross-validation and R2=0.526 for external validation). Moreover, several external bio-assays that correlate with BBB permeability were identified using our automatic profiling tool. Conclusions The BBB permeability models developed in this study can be useful for early evaluation of new compounds (e.g., new drug candidates). The combination of chemical and biological descriptors shows a promising direction to improve the current traditional QSAR models. PMID:25862462

  16. Zebrafish as a Screening Model for Testing the Permeability of Blood-Brain Barrier to Small Molecules.

    Science.gov (United States)

    Kim, Seong Soon; Im, So Hee; Yang, Jung Yoon; Lee, Yu-Ri; Kim, Geum Ran; Chae, Jin Sil; Shin, Dae-Seop; Song, Jin Sook; Ahn, Sunjoo; Lee, Byung Hoi; Woo, Jae Chun; Ahn, Jin Hee; Yun, Chang Soo; Kim, Phiho; Kim, Hyoung Rae; Lee, Kyeong-Ryoon; Bae, Myung Ae

    2017-08-01

    The objective of this study was to evaluate the permeability of small molecules into the brain via the blood-brain barrier in zebrafish and to investigate the possibility of using this animal model as a screening tool during the early stages of drug discovery. Fifteen compounds were used to understand the permeation into the brain in zebrafish and mice. The ratio of brain-to-plasma concentration was compared between the two animal models. The partition coefficient (K p,brain ), estimated using the concentration ratio at designated times (0.167, 0.25, 0.5, or 2 h) after oral administrations (per os, p.o), ranged from 0.099 to 5.68 in zebrafish and from 0.080 to 11.8 in mice. A correlation was observed between the K p,brain values obtained from the zebrafish and mice, suggesting that zebrafish can be used to estimate K p,brain to predict drug penetration in humans. Furthermore, in vivo transport experiments to understand the permeability glycoprotein (P-gp) transporter-mediated behavior of loperamide (LPM) in zebrafish were performed. The zebrafish, K p,brain,30min of LPM was determined to be 0.099 ± 0.069 after dosing with LPM alone, which increased to 0.180 ± 0.115 after dosing with LPM and tariquidar (TRQ, an inhibitor of P-gp). In mouse, the K p,brain,30min of LPM was determined to be 0.080 ± 0.004 after dosing with LPM alone and 0.237 ± 0.013 after dosing with LPM and TRQ. These findings indicate that the zebrafish could be used as an effective screening tool during the discovery stages of new drugs to estimate their distribution in the brain.

  17. Inborn and experience-dependent models of categorical brain organization. A position paper.

    Directory of Open Access Journals (Sweden)

    Guido eGainotti

    2015-01-01

    Full Text Available The present review aims to summarize the debate in contemporary neuroscience between inborn and experience-dependent models of conceptual representations that goes back to the description of category-specific semantic disorders for biological and artefact categories. Experience-dependent models suggest that categorical disorders are the by-product of the differential weighting of different sources of knowledge in the representation of biological and artefact categories. These models maintain that semantic disorders are not really category-specific, because they do not respect the boundaries between different categories. They also argue that the brain structures disrupted in a given type of category-specific semantic disorder should correspond to the areas of convergence of the sensory-motor information which play a major role in the construction of that category. Furthermore, they provide a simple interpretation of gender-related categorical effects and are supported by studies that have assessed the importance of prior experience in the cortical representation of objects On the other hand, inborn models maintain that category-specific semantic disorders reflect the disruption of innate brain networks, which are shaped by natural selection to allow rapid identification of objects that are very relevant for survival. From the empirical point of view, these models are mainly supported by observations made in blind subjects, which suggest that visual experience is not necessary for the emergence of category-specificity in the ventral stream of visual processing. The weight of data supporting experience-dependent and inborn models are thoroughly discussed, stressing the fact observations made in blind subjects are still the subject of intense debate, but concluding that at the present state of knowledge it is not possible to choose between experience-dependent and inborn models of conceptual representations.

  18. Robust brain ROI segmentation by deformation regression and deformable shape model.

    Science.gov (United States)

    Wu, Zhengwang; Guo, Yanrong; Park, Sang Hyun; Gao, Yaozong; Dong, Pei; Lee, Seong-Whan; Shen, Dinggang

    2018-01-01

    We propose a robust and efficient learning-based deformable model for segmenting regions of interest (ROIs) from structural MR brain images. Different from the conventional deformable-model-based methods that deform a shape model locally around the initialization location, we learn an image-based regressor to guide the deformable model to fit for the target ROI. Specifically, given any voxel in a new image, the image-based regressor can predict the displacement vector from this voxel towards the boundary of target ROI, which can be used to guide the deformable segmentation. By predicting the displacement vector maps for the whole image, our deformable model is able to use multiple non-boundary predictions to jointly determine and iteratively converge the initial shape model to the target ROI boundary, which is more robust to the local prediction error and initialization. In addition, by introducing the prior shape model, our segmentation avoids the isolated segmentations as often occurred in the previous multi-atlas-based methods. In order to learn an image-based regressor for displacement vector prediction, we adopt the following novel strategies in the learning procedure: (1) a joint classification and regression random forest is proposed to learn an image-based regressor together with an ROI classifier in a multi-task manner; (2) high-level context features are extracted from intermediate (estimated) displacement vector and classification maps to enforce the relationship between predicted displacement vectors at neighboring voxels. To validate our method, we compare it with the state-of-the-art multi-atlas-based methods and other learning-based methods on three public brain MR datasets. The results consistently show that our method is better in terms of both segmentation accuracy and computational efficiency. Copyright © 2017 Elsevier B.V. All rights reserved.

  19. Cinnamon extract improves insulin sensitivity in the brain and lowers liver fat in mouse models of obesity.

    Science.gov (United States)

    Sartorius, Tina; Peter, Andreas; Schulz, Nadja; Drescher, Andrea; Bergheim, Ina; Machann, Jürgen; Schick, Fritz; Siegel-Axel, Dorothea; Schürmann, Annette; Weigert, Cora; Häring, Hans-Ulrich; Hennige, Anita M

    2014-01-01

    Treatment of diabetic subjects with cinnamon demonstrated an improvement in blood glucose concentrations and insulin sensitivity but the underlying mechanisms remained unclear. This work intends to elucidate the impact of cinnamon effects on the brain by using isolated astrocytes, and an obese and diabetic mouse model. Cinnamon components (eugenol, cinnamaldehyde) were added to astrocytes and liver cells to measure insulin signaling and glycogen synthesis. Ob/ob mice were supplemented with extract from cinnamomum zeylanicum for 6 weeks and cortical brain activity, locomotion and energy expenditure were evaluated. Insulin action was determined in brain and liver tissues. Treatment of primary astrocytes with eugenol promoted glycogen synthesis, whereas the effect of cinnamaldehyde was attenuated. In terms of brain function in vivo, cinnamon extract improved insulin sensitivity and brain activity in ob/ob mice, and the insulin-stimulated locomotor activity was improved. In addition, fasting blood glucose levels and glucose tolerance were greatly improved in ob/ob mice due to cinnamon extracts, while insulin secretion was unaltered. This corresponded with lower triglyceride and increased liver glycogen content and improved insulin action in liver tissues. In vitro, Fao cells exposed to cinnamon exhibited no change in insulin action. Together, cinnamon extract improved insulin action in the brain as well as brain activity and locomotion. This specific effect may represent an important central feature of cinnamon in improving insulin action in the brain, and mediates metabolic alterations in the periphery to decrease liver fat and improve glucose homeostasis.

  20. Cinnamon extract improves insulin sensitivity in the brain and lowers liver fat in mouse models of obesity.

    Directory of Open Access Journals (Sweden)

    Tina Sartorius

    Full Text Available OBJECTIVES: Treatment of diabetic subjects with cinnamon demonstrated an improvement in blood glucose concentrations and insulin sensitivity but the underlying mechanisms remained unclear. This work intends to elucidate the impact of cinnamon effects on the brain by using isolated astrocytes, and an obese and diabetic mouse model. METHODS: Cinnamon components (eugenol, cinnamaldehyde were added to astrocytes and liver cells to measure insulin signaling and glycogen synthesis. Ob/ob mice were supplemented with extract from cinnamomum zeylanicum for 6 weeks and cortical brain activity, locomotion and energy expenditure were evaluated. Insulin action was determined in brain and liver tissues. RESULTS: Treatment of primary astrocytes with eugenol promoted glycogen synthesis, whereas the effect of cinnamaldehyde was attenuated. In terms of brain function in vivo, cinnamon extract improved insulin sensitivity and brain activity in ob/ob mice, and the insulin-stimulated locomotor activity was improved. In addition, fasting blood glucose levels and glucose tolerance were greatly improved in ob/ob mice due to cinnamon extracts, while insulin secretion was unaltered. This corresponded with lower triglyceride and increased liver glycogen content and improved insulin action in liver tissues. In vitro, Fao cells exposed to cinnamon exhibited no change in insulin action. CONCLUSIONS: Together, cinnamon extract improved insulin action in the brain as well as brain activity and locomotion. This specific effect may represent an important central feature of cinnamon in improving insulin action in the brain, and mediates metabolic alterations in the periphery to decrease liver fat and improve glucose homeostasis.

  1. A multimodal RAGE-specific inhibitor reduces amyloid β-mediated brain disorder in a mouse model of Alzheimer disease.

    Science.gov (United States)

    Deane, Rashid; Singh, Itender; Sagare, Abhay P; Bell, Robert D; Ross, Nathan T; LaRue, Barbra; Love, Rachal; Perry, Sheldon; Paquette, Nicole; Deane, Richard J; Thiyagarajan, Meenakshisundaram; Zarcone, Troy; Fritz, Gunter; Friedman, Alan E; Miller, Benjamin L; Zlokovic, Berislav V

    2012-04-01

    In Alzheimer disease (AD), amyloid β peptide (Aβ) accumulates in plaques in the brain. Receptor for advanced glycation end products (RAGE) mediates Aβ-induced perturbations in cerebral vessels, neurons, and microglia in AD. Here, we identified a high-affinity RAGE-specific inhibitor (FPS-ZM1) that blocked Aβ binding to the V domain of RAGE and inhibited Aβ40- and Aβ42-induced cellular stress in RAGE-expressing cells in vitro and in the mouse brain in vivo. FPS-ZM1 was nontoxic to mice and readily crossed the blood-brain barrier (BBB). In aged APPsw/0 mice overexpressing human Aβ-precursor protein, a transgenic mouse model of AD with established Aβ pathology, FPS-ZM1 inhibited RAGE-mediated influx of circulating Aβ40 and Aβ42 into the brain. In brain, FPS-ZM1 bound exclusively to RAGE, which inhibited β-secretase activity and Aβ production and suppressed microglia activation and the neuroinflammatory response. Blockade of RAGE actions at the BBB and in the brain reduced Aβ40 and Aβ42 levels in brain markedly and normalized cognitive performance and cerebral blood flow responses in aged APPsw/0 mice. Our data suggest that FPS-ZM1 is a potent multimodal RAGE blocker that effectively controls progression of Aβ-mediated brain disorder and that it may have the potential to be a disease-modifying agent for AD.

  2. New Insights Offered by a Computational Model of Deep Brain Stimulation

    DEFF Research Database (Denmark)

    Modolo, J.; Mosekilde, Erik; Beuter, A.

    2007-01-01

    Deep brain stimulation (DBS) is a standard neurosurgical procedure used to treat motor symptoms in about 5% of patients with Parkinson's disease (PD). Despite the indisputable success of this procedure, the biological mechanisms underlying the clinical benefits of DBS have not yet been fully...... and exploring the physiological mechanisms which respond to this treatment strategy (i.e., DBS). Finally, we present new insights into the ways this computational model may help to elucidate the dynamic network effects produced in a cerebral structure when DBS is applied. (C) 2007 Elsevier Ltd. All rights...

  3. Transport rankings of non-steroidal antiinflammatory drugs across blood-brain barrier in vitro models.

    Directory of Open Access Journals (Sweden)

    Iveta Novakova

    Full Text Available The aim of this work was to conduct a comprehensive study about the transport properties of NSAIDs across the blood-brain barrier (BBB in vitro. Transport studies with celecoxib, diclofenac, ibuprofen, meloxicam, piroxicam and tenoxicam were accomplished across Transwell models based on cell line PBMEC/C1-2, ECV304 or primary rat brain endothelial cells. Single as well as group substance studies were carried out. In group studies substance group compositions, transport medium and serum content were varied, transport inhibitors verapamil and probenecid were added. Resulted permeability coefficients were compared and normalized to internal standards diazepam and carboxyfluorescein. Transport rankings of NSAIDs across each model were obtained. Single substance studies showed similar rankings as corresponding group studies across PBMEC/C1-2 or ECV304 cell layers. Serum content, glioma conditioned medium and inhibitors probenecid and verapamil influenced resulted permeability significantly. Basic differences of transport properties of the investigated NSAIDs were similar comparing all three in vitro BBB models. Different substance combinations in the group studies and addition of probenecid and verapamil suggested that transporter proteins are involved in the transport of every tested NSAID. Results especially underlined the importance of same experimental conditions (transport medium, serum content, species origin, cell line for proper data comparison.

  4. Electric field distribution in a finite-volume head model of deep brain stimulation.

    Science.gov (United States)

    Grant, Peadar F; Lowery, Madeleine M

    2009-11-01

    This study presents a whole-head finite element model of deep brain stimulation to examine the effect of electrical grounding, the finite conducting volume of the head, and scalp, skull and cerebrospinal fluid layers. The impedance between the stimulating and reference electrodes in the whole-head model was found to lie within clinically reported values when the reference electrode was incorporated on a localized surface in the model. Incorporation of the finite volume of the head and inclusion of surrounding outer tissue layers reduced the magnitude of the electric field and activating function by approximately 20% in the region surrounding the electrode. Localized distortions of the electric field were also observed when the electrode was placed close to the skull. Under bipolar conditions the effect of the finite conducting volume was shown to be negligible. The results indicate that, for monopolar stimulation, incorporation of the finite volume and outer tissue layers can alter the magnitude of the electric field and activating function when the electrode is deep within the brain, and may further affect the shape if the electrode is close to the skull.

  5. Task decomposition: a framework for comparing diverse training models in human brain plasticity studies

    Directory of Open Access Journals (Sweden)

    Emily B. J. Coffey

    2013-10-01

    Full Text Available Training studies, in which the structural or functional neurophysiology is compared before and after expertise is acquired, are increasingly being used as models for understanding the human brain’s potential for reorganization. It is proving difficult to use these results to answer basic and important questions like how task training leads to both specific and general changes in behaviour and how these changes correspond with modifications in the brain. The main culprit is the diversity of paradigms used as complex task models. An assortment of activities ranging from juggling to deciphering Morse code has been reported. Even when working in the same general domain, few researchers use similar training models. New ways to meaningfully compare complex tasks are needed. We propose a method for characterizing and deconstructing the task requirements of complex training paradigms, which is suitable for application to both structural and functional neuroimaging studies. We believe this approach will aid brain plasticity research by making it easier to compare training paradigms, identify ‘missing puzzle pieces’, and encourage researchers to design training protocols to bridge these gaps.

  6. Transport rankings of non-steroidal antiinflammatory drugs across blood-brain barrier in vitro models.

    Science.gov (United States)

    Novakova, Iveta; Subileau, Eva-Anne; Toegel, Stefan; Gruber, Daniela; Lachmann, Bodo; Urban, Ernst; Chesne, Christophe; Noe, Christian R; Neuhaus, Winfried

    2014-01-01

    The aim of this work was to conduct a comprehensive study about the transport properties of NSAIDs across the blood-brain barrier (BBB) in vitro. Transport studies with celecoxib, diclofenac, ibuprofen, meloxicam, piroxicam and tenoxicam were accomplished across Transwell models based on cell line PBMEC/C1-2, ECV304 or primary rat brain endothelial cells. Single as well as group substance studies were carried out. In group studies substance group compositions, transport medium and serum content were varied, transport inhibitors verapamil and probenecid were added. Resulted permeability coefficients were compared and normalized to internal standards diazepam and carboxyfluorescein. Transport rankings of NSAIDs across each model were obtained. Single substance studies showed similar rankings as corresponding group studies across PBMEC/C1-2 or ECV304 cell layers. Serum content, glioma conditioned medium and inhibitors probenecid and verapamil influenced resulted permeability significantly. Basic differences of transport properties of the investigated NSAIDs were similar comparing all three in vitro BBB models. Different substance combinations in the group studies and addition of probenecid and verapamil suggested that transporter proteins are involved in the transport of every tested NSAID. Results especially underlined the importance of same experimental conditions (transport medium, serum content, species origin, cell line) for proper data comparison.

  7. In vitro models of the blood-brain barrier

    DEFF Research Database (Denmark)

    Helms, Hans Christian Cederberg; Abbott, N Joan; Burek, Malgorzata

    2016-01-01

    The endothelial cells lining the brain capillaries separate the blood from the brain parenchyma. The endothelial monolayer of the brain capillaries serves both as a crucial interface for exchange of nutrients, gases, and metabolites between blood and brain, and as a barrier for neurotoxic compone...

  8. High-Resolution Longitudinal Screening with Magnetic Resonance Imaging in a Murine Brain Cancer Model

    Directory of Open Access Journals (Sweden)

    Nicholas A. Bock

    2003-11-01

    Full Text Available One of the main limitations of intracranial models of diseases is our present inability to monitor and evaluate the intracranial compartment noninvasively over time. Therefore, there is a growing need for imaging modalities that provide thorough neuropathological evaluations of xenograft and transgenic models of intracranial pathology. In this study, we have established protocols for multiple-mouse magnetic resonance imaging (MRI to follow the growth and behavior of intracranial xenografts of gliomas longitudinally. We successfully obtained weekly images on 16 mice for a total of 5 weeks on a 7-T multiple-mouse MRI. T2- and Ti-weighted imaging with gadolinium enhancement of vascularity was used to detect tumor margins, tumor size, and growth. These experiments, using 3D whole brain images obtained in four mice at once, demonstrate the feasibility of obtaining repeat radiological images in intracranial tumor models and suggest that MRI should be incorporated as a research modality for the investigation of intracranial pathobiology.

  9. Contribution of thrombin-reactive brain pericytes to blood-brain barrier dysfunction in an in vivo mouse model of obesity-associated diabetes and an in vitro rat model.

    Directory of Open Access Journals (Sweden)

    Takashi Machida

    Full Text Available Diabetic complications are characterized by the dysfunction of pericytes located around microvascular endothelial cells. The blood-brain barrier (BBB exhibits hyperpermeability with progression of diabetes. Therefore, brain pericytes at the BBB may be involved in diabetic complications of the central nervous system (CNS. We hypothesized that brain pericytes respond to increased brain thrombin levels in diabetes, leading to BBB dysfunction and diabetic CNS complications. Mice were fed a high-fat diet (HFD for 2 or 8 weeks to induce obesity. Transport of i.v.-administered sodium fluorescein and 125I-thrombin across the BBB were measured. We evaluated brain endothelial permeability and expression of tight junction proteins in the presence of thrombin-treated brain pericytes using a BBB model of co-cultured rat brain endothelial cells and pericytes. Mice fed a HFD for 8 weeks showed both increased weight gain and impaired glucose tolerance. In parallel, the brain influx rate of sodium fluorescein was significantly greater than that in mice fed a normal diet. HFD feeding inhibited the decline in brain thrombin levels occurring during 6 weeks of feeding. In the HFD fed mice, plasma thrombin levels were significantly increased, by up to 22%. 125I-thrombin was transported across the BBB in normal mice after i.v. injection, with uptake further enhanced by co-injection of unlabeled thrombin. Thrombin-treated brain pericytes increased brain endothelial permeability and caused decreased expression of zona occludens-1 (ZO-1 and occludin and morphological disorganization of ZO-1. Thrombin also increased mRNA expression of interleukin-1β and 6 and tumor necrosis factor-α in brain pericytes. Thrombin can be transported from circulating blood through the BBB, maintaining constant levels in the brain, where it can stimulate pericytes to induce BBB dysfunction. Thus, the brain pericyte-thrombin interaction may play a key role in causing BBB dysfunction in

  10. How do parcellation size and short-range connectivity affect dynamics in large-scale brain network models?

    Science.gov (United States)

    Proix, Timothée; Spiegler, Andreas; Schirner, Michael; Rothmeier, Simon; Ritter, Petra; Jirsa, Viktor K

    2016-11-15

    Recent efforts to model human brain activity on the scale of the whole brain rest on connectivity estimates of large-scale networks derived from diffusion magnetic resonance imaging (dMRI). This type of connectivity describes white matter fiber tracts. The number of short-range cortico-cortical white-matter connections is, however, underrepresented in such large-scale brain models. It is still unclear on the one hand, which scale of representation of white matter fibers is optimal to describe brain activity on a large-scale such as recorded with magneto- or electroencephalography (M/EEG) or functional magnetic resonance imaging (fMRI), and on the other hand, to which extent short-range connections that are typically local should be taken into account. In this article we quantified the effect of connectivity upon large-scale brain network dynamics by (i) systematically varying the number of brain regions before computing the connectivity matrix, and by (ii) adding generic short-range connections. We used dMRI data from the Human Connectome Project. We developed a suite of preprocessing modules called SCRIPTS to prepare these imaging data for The Virtual Brain, a neuroinformatics platform for large-scale brain modeling and simulations. We performed simulations under different connectivity conditions and quantified the spatiotemporal dynamics in terms of Shannon Entropy, dwell time and Principal Component Analysis. For the reconstructed connectivity, our results show that the major white matter fiber bundles play an important role in shaping slow dynamics in large-scale brain networks (e.g. in fMRI). Faster dynamics such as gamma oscillations (around 40 Hz) are sensitive to the short-range connectivity if transmission delays are considered. Copyright © 2016 Elsevier Inc. All rights reserved.

  11. A comparative study of two prediction models for brain tumor progression

    Science.gov (United States)

    Zhou, Deqi; Tran, Loc; Wang, Jihong; Li, Jiang

    2015-03-01

    MR diffusion tensor imaging (DTI) technique together with traditional T1 or T2 weighted MRI scans supplies rich information sources for brain cancer diagnoses. These images form large-scale, high-dimensional data sets. Due to the fact that significant correlations exist among these images, we assume low-dimensional geometry data structures (manifolds) are embedded in the high-dimensional space. Those manifolds might be hidden from radiologists because it is challenging for human experts to interpret high-dimensional data. Identification of the manifold is a critical step for successfully analyzing multimodal MR images. We have developed various manifold learning algorithms (Tran et al. 2011; Tran et al. 2013) for medical image analysis. This paper presents a comparative study of an incremental manifold learning scheme (Tran. et al. 2013) versus the deep learning model (Hinton et al. 2006) in the application of brain tumor progression prediction. The incremental manifold learning is a variant of manifold learning algorithm to handle large-scale datasets in which a representative subset of original data is sampled first to construct a manifold skeleton and remaining data points are then inserted into the skeleton by following their local geometry. The incremental manifold learning algorithm aims at mitigating the computational burden associated with traditional manifold learning methods for large-scale datasets. Deep learning is a recently developed multilayer perceptron model that has achieved start-of-the-art performances in many applications. A recent technique named "Dropout" can further boost the deep model by preventing weight coadaptation to avoid over-fitting (Hinton et al. 2012). We applied the two models on multiple MRI scans from four brain tumor patients to predict tumor progression and compared the performances of the two models in terms of average prediction accuracy, sensitivity, specificity and precision. The quantitative performance metrics were

  12. Tracer kinetic modelling for DCE-MRI quantification of subtle blood-brain barrier permeability.

    Science.gov (United States)

    Heye, Anna K; Thrippleton, Michael J; Armitage, Paul A; Valdés Hernández, Maria Del C; Makin, Stephen D; Glatz, Andreas; Sakka, Eleni; Wardlaw, Joanna M

    2016-01-15

    There is evidence that subtle breakdown of the blood-brain barrier (BBB) is a pathophysiological component of several diseases, including cerebral small vessel disease and some dementias. Dynamic contrast-enhanced MRI (DCE-MRI) combined with tracer kinetic modelling is widely used for assessing permeability and perfusion in brain tumours and body tissues where contrast agents readily accumulate in the extracellular space. However, in diseases where leakage is subtle, the optimal approach for measuring BBB integrity is likely to differ since the magnitude and rate of enhancement caused by leakage are extremely low; several methods have been reported in the literature, yielding a wide range of parameters even in healthy subjects. We hypothesised that the Patlak model is a suitable approach for measuring low-level BBB permeability with low temporal resolution and high spatial resolution and brain coverage, and that normal levels of scanner instability would influence permeability measurements. DCE-MRI was performed in a cohort of mild stroke patients (n=201) with a range of cerebral small vessel disease severity. We fitted these data to a set of nested tracer kinetic models, ranking their performance according to the Akaike information criterion. To assess the influence of scanner drift, we scanned 15 healthy volunteers that underwent a "sham" DCE-MRI procedure without administration of contrast agent. Numerical simulations were performed to investigate model validity and the effect of scanner drift. The Patlak model was found to be most appropriate for fitting low-permeability data, and the simulations showed vp and K(Trans) estimates to be reasonably robust to the model assumptions. However, signal drift (measured at approximately 0.1% per minute and comparable to literature reports in other settings) led to systematic errors in calculated tracer kinetic parameters, particularly at low permeabilities. Our findings justify the growing use of the Patlak model in low

  13. Mechanics of blast loading on the head models in the study of traumatic brain injury using experimental and computational approaches.

    Science.gov (United States)

    Ganpule, S; Alai, A; Plougonven, E; Chandra, N

    2013-06-01

    Blast waves generated by improvised explosive devices can cause mild, moderate to severe traumatic brain injury in soldiers and civilians. To understand the interactions of blast waves on the head and brain and to identify the mechanisms of injury, compression-driven air shock tubes are extensively used in laboratory settings to simulate the field conditions. The overall goal of this effort is to understand the mechanics of blast wave-head interactions as the blast wave traverses the head/brain continuum. Toward this goal, surrogate head model is subjected to well-controlled blast wave profile in the shock tube environment, and the results are analyzed using combined experimental and numerical approaches. The validated numerical models are then used to investigate the spatiotemporal distribution of stresses and pressure in the human skull and brain. By detailing the results from a series of careful experiments and numerical simulations, this paper demonstrates that: (1) Geometry of the head governs the flow dynamics around the head which in turn determines the net mechanical load on the head. (2) Biomechanical loading of the brain is governed by direct wave transmission, structural deformations, and wave reflections from tissue-material interfaces. (3) Deformation and stress analysis of the skull and brain show that skull flexure and tissue cavitation are possible mechanisms of blast-induced traumatic brain injury.

  14. Down-regulation of selected Blood-brain Barrier Specific Genes from Capillaries to Bovine In Vitro Models

    DEFF Research Database (Denmark)

    Goldeman, Charlotte; Saaby, Lasse; Brodin, Birger

    Cultures of primary bovine brain endothelial cells (BECs) grown, often together with astrocytes, on permeable supports in two-compartment culture systems are commonly used as an in vitro model of the blood-brain barrier (BBB). While trans-endothelial electrical resistance, restriction...... the in vivo gene expression of brain capillary endothelial cells. Primary bovine endothelial cells and rat astrocytes were cultured in different culture configurations and the mRNA expression of selected genes (vWF, Glut-1, P-gp, claudin-1,-5, occludin, JAM-1, LAT-1, SLC16A1, MRP-1,-4, BCRP, ZO-1, AP, TPA...

  15. Noninvasive monitoring of treatment response in a rabbit cyanide toxicity model reveals differences in brain and muscle metabolism

    Science.gov (United States)

    Kim, Jae G.; Lee, Jangwoen; Mahon, Sari B.; Mukai, David; Patterson, Steven E.; Boss, Gerry R.; Tromberg, Bruce J.; Brenner, Matthew

    2012-10-01

    Noninvasive near infrared spectroscopy measurements were performed to monitor cyanide (CN) poisoning and recovery in the brain region and in foreleg muscle simultaneously, and the effects of a novel CN antidote, sulfanegen sodium, on tissue hemoglobin oxygenation changes were compared using a sub-lethal rabbit model. The results demonstrated that the brain region is more susceptible to CN poisoning and slower in endogenous CN detoxification following exposure than peripheral muscles. However, sulfanegen sodium rapidly reversed CN toxicity, with brain region effects reversing more quickly than muscle. In vivo monitoring of multiple organs may provide important clinical information regarding the extent of CN toxicity and subsequent recovery, and facilitate antidote drug development.

  16. Prevention of Blast-Related Injuries

    Science.gov (United States)

    2015-07-14

    2699-2710. 32. Finnigan SP, Walsh M, Rose SE, Chalk JB. Quantitative EEG indices of sub- acute ischaemic stroke correlate with clinical outcomes...as intensely stained regions in and around cell bodies are reminiscent of Amyloid β reactive staining in Alzheimer’s disease (AD). Immunoreactive...motility and phagocytic activity were impaired in mice with Alzheimer’s disease -like pathology (AD-like) with their impairment being temporally and

  17. Prevention of Blast-Related Injuries

    Science.gov (United States)

    2016-07-01

    cell bodies that may be related to impaired axoplasmic transport and its ultimate release into the surrounding extracellular matrix , which in turn...the expression of phosphorylated neurofilament heavy chain (pNF-H Elisa Kit, Encor Biotechnology , Gainesville, FL), glial fibrillary acidic protein...samples were assessed for temporal changes in the expression of phosphorylated neurofilament heavy chain (pNF-H Elisa Kit, Encor Biotechnology

  18. Advanced MRI in Blast-related TBI

    Science.gov (United States)

    2012-07-01

    this study possible; the staff at the LRMC MRI clinic, including Don Al- brant, Kenny Caywood, Kelly McKay, Tim McKay, Tim Roberts, Kris Robertson...erans with persistent post-concussive symp- toms . Neuroimage 2011;54:Suppl 1:S76- S82. 12. Warden DL, French LM, Shupenko L, et al. Case report of a...Luethcke CA, Bryan CJ, Morrow CE, Isler WC. Comparison of concussive symp- toms , cognitive performance, and psycho- logical symptoms between acute blast

  19. Testing a dual-systems model of adolescent brain development using resting-state connectivity analyses.

    Science.gov (United States)

    van Duijvenvoorde, A C K; Achterberg, M; Braams, B R; Peters, S; Crone, E A

    2016-01-01

    The current study aimed to test a dual-systems model of adolescent brain development by studying changes in intrinsic functional connectivity within and across networks typically associated with cognitive-control and affective-motivational processes. To this end, resting-state and task-related fMRI data were collected of 269 participants (ages 8-25). Resting-state analyses focused on seeds derived from task-related neural activation in the same participants: the dorsal lateral prefrontal cortex (dlPFC) from a cognitive rule-learning paradigm and the nucleus accumbens (NAcc) from a reward-paradigm. Whole-brain seed-based resting-state analyses showed an age-related increase in dlPFC connectivity with the caudate and thalamus, and an age-related decrease in connectivity with the (pre)motor cortex. nAcc connectivity showed a strengthening of connectivity with the dorsal anterior cingulate cortex (ACC) and subcortical structures such as the hippocampus, and a specific age-related decrease in connectivity with the ventral medial PFC (vmPFC). Behavioral measures from both functional paradigms correlated with resting-state connectivity strength with their respective seed. That is, age-related change in learning performance was mediated by connectivity between the dlPFC and thalamus, and age-related change in winning pleasure was mediated by connectivity between the nAcc and vmPFC. These patterns indicate (i) strengthening of connectivity between regions that support control and learning, (ii) more independent functioning of regions that support motor and control networks, and (iii) more independent functioning of regions that support motivation and valuation networks with age. These results are interpreted vis-à-vis a dual-systems model of adolescent brain development. Copyright © 2015. Published by Elsevier Inc.

  20. A novel transgenic zebrafish model for blood-brain and blood-retinal barrier development

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    Sugimoto Masahiko

    2010-07-01

    Full Text Available Abstract Background Development and maintenance of the blood-brain and blood-retinal barrier is critical for the homeostasis of brain and retinal tissue. Despite decades of research our knowledge of the formation and maintenance of the blood-brain (BBB and blood-retinal (BRB barrier is very limited. We have established an in vivo model to study the development and maintenance of these barriers by generating a transgenic zebrafish line that expresses a vitamin D-binding protein fused with enhanced green fluorescent protein (DBP-EGFP in blood plasma, as an endogenous tracer. Results The temporal establishment of the BBB and BRB was examined using this transgenic line and the results were compared with that obtained by injection of fluorescent dyes into the sinus venosus of embryos at various stages of development. We also examined the expression of claudin-5, a component of tight junctions during the first 4 days of development. We observed that the BBB of zebrafish starts to develop by 3 dpf, with expression of claudin-5 in the central arteries preceding it at 2 dpf. The hyaloid vasculature in the zebrafish retina develops a barrier function at 3 dpf, which endows the zebrafish with unique advantages for studying the BRB. Conclusion Zebrafish embryos develop BBB and BRB function simultaneously by 3 dpf, which is regulated by tight junction proteins. The Tg(l-fabp:DBP-EGFP zebrafish will have great advantages in studying development and maintenance of the blood-neural barrier, which is a new application for the widely used vertebrate model.

  1. Relationship of mechanical impact magnitude to neurologic dysfunction severity in a rat traumatic brain injury model.

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    Tsung-Hsun Hsieh

    Full Text Available Traumatic brain injury (TBI is a major brain injury type commonly caused by traffic accidents, falls, violence, or sports injuries. To obtain mechanistic insights about TBI, experimental animal models such as weight-drop-induced TBI in rats have been developed to mimic closed-head injury in humans. However, the relationship between the mechanical impact level and neurological severity following weight-drop-induced TBI remains uncertain. In this study, we comprehensively investigated the relationship between physical impact and graded severity at various weight-drop heights.The acceleration, impact force, and displacement during the impact were accurately measured using an accelerometer, a pressure sensor, and a high-speed camera, respectively. In addition, the longitudinal changes in neurological deficits and balance function were investigated at 1, 4, and 7 days post TBI lesion. The inflammatory expression markers tested by Western blot analysis, including glial fibrillary acidic protein, beta-amyloid precursor protein, and bone marrow tyrosine kinase gene in chromosome X, in the frontal cortex, hippocampus, and corpus callosum were investigated at 1 and 7 days post-lesion.Gradations in impact pressure produced progressive degrees of injury severity in the neurological score and balance function. Western blot analysis demonstrated that all inflammatory expression markers were increased at 1 and 7 days post-impact injury when compared to the sham control rats. The severity of neurologic dysfunction and induction in inflammatory markers strongly correlated with the graded mechanical impact levels.We conclude that the weight-drop-induced TBI model can produce graded brain injury and induction of neurobehavioral deficits and may have translational relevance to developing therapeutic strategies for TBI.

  2. Changes in oxygen partial pressure of brain tissue in an animal model of obstructive apnea

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    Torres Marta

    2010-01-01

    Full Text Available Abstract Background Cognitive impairment is one of the main consequences of obstructive sleep apnea (OSA and is usually attributed in part to the oxidative stress caused by intermittent hypoxia in cerebral tissues. The presence of oxygen-reactive species in the brain tissue should be produced by the deoxygenation-reoxygenation cycles which occur at tissue level during recurrent apneic events. However, how changes in arterial blood oxygen saturation (SpO2 during repetitive apneas translate into oxygen partial pressure (PtO2 in brain tissue has not been studied. The objective of this study was to assess whether brain tissue is partially protected from intermittently occurring interruption of O2 supply during recurrent swings in arterial SpO2 in an animal model of OSA. Methods Twenty-four male Sprague-Dawley rats (300-350 g were used. Sixteen rats were anesthetized and non-invasively subjected to recurrent obstructive apneas: 60 apneas/h, 15 s each, for 1 h. A control group of 8 rats was instrumented but not subjected to obstructive apneas. PtO2 in the cerebral cortex was measured using a fast-response oxygen microelectrode. SpO2 was measured by pulse oximetry. The time dependence of arterial SpO2 and brain tissue PtO2 was carried out by Friedman repeated measures ANOVA. Results Arterial SpO2 showed a stable periodic pattern (no significant changes in maximum [95.5 ± 0.5%; m ± SE] and minimum values [83.9 ± 1.3%]. By contrast, brain tissue PtO2 exhibited a different pattern from that of arterial SpO2. The minimum cerebral cortex PtO2 computed during the first apnea (29.6 ± 2.4 mmHg was significantly lower than baseline PtO2 (39.7 ± 2.9 mmHg; p = 0.011. In contrast to SpO2, the minimum and maximum values of PtO2 gradually increased (p 2 were significantly greater relative to baseline and the first apnea dip, respectively. Conclusions These data suggest that the cerebral cortex is partially protected from intermittently occurring interruption of

  3. The effect of ultrasound on thromboembolic model of brain stroke in rat

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    Shabanzadeh A

    2007-08-01

    Full Text Available Background: Ultrasound (US has been used in neuroprotection after cerebral ischemia; however, its use is controversial. Application of US in combination with fibrinolytic agents may improve fibrinolytic effects. In this study the effects of US, alone or in combination with tissue plasminogen activator (tPA, on brain ischemic injury were examined and we studied whether US is protective in the brain injured by ischemia under normothermic conditions. Methods: We performed two studies. In the first study, rectal and brain temperatures were compared. In the second study, we studied whether US alone or in combination with tPA is neuroprotective in thromboembolic stroke. To induce focal cerebral ischemia, a clot was formed in a catheter. Once the clot had formed, the catheter was advanced 17 mm in the internal carotid artery until its tip was 1-2 mm away from the origin of the middle cerebral artery (MCA. The preformed clot in the catheter was then injected, and the catheter was removed. The wound was then closed and the infarction volume, edema and neurological deficits were measured after MCA occlusion. Results: The temperature in the brain was approximately 0.50 ºC lower than the rectal temperature. In the control, US+low tPA, low tPA, US+high tPA and, high tPA groups, the infarct volume (% was 34.56±4.16, 17.09±6.72, 21.25±7.8, 13.5±10.72 and 20.61±6.17 (mean ±SD at 48 h after MCA occlusion, respectively. The results indicate that US alone reduces the infarct volume by 30% compared to that of the control group (P<0.05. US improved neurological deficits and reduced brain edema significantly (p<0.05. Conclusions: This study indicate that US appears to have a protective effect, alone and in combination with tPA, in an embolic model of stroke.

  4. Effects of Ecballium elaterium on brain in a rat model of sepsis-associated encephalopathy

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    Arslan, Demet; Ekinci, Aysun; Arici, Akgul; Bozdemir, Eda; Akil, Esref; Ozdemir, Hasan Huseyin

    2017-01-01

    ABSTRACT Despite recent advances in antibiotic therapy, sepsis remains a major clinical challenge in intensive care units. Here we examined the anti-inflammatory and antioxidant effects of Ecballium elaterium (EE) on brain, and explored its therapeutic potential in an animal model of sepsis-associated encephalopathy (SAE) [induced by cecal ligation and puncture (CLP)]. Thirty rats were divided into three groups of 10 each: control, sepsis, and treatment. Rats were subjected to CLP except for the control group, which underwent laparatomy only. The treatment group received 2.5 mg/kg EE while the sepsis group was administered by saline. Twenty-four hours after laparotomy, animals were sacrificied and the brains were removed. Brain homogenates were prepared to assess interleukin 1beta (IL-1β), interleukin 6 (IL-6), tumor necrosis factor alpha (TNF-α), total antioxidant capacity (TAC), and total oxidant status (TOS). Brain tissue sections were stained by hematoxylin and eosin (H&E) to semi-quantitatively examine the histopathologic changes such as neuron degeneration, pericellular/perivascular edema and inflammatory cell infiltration in the cerebral cortex. We found a statistically significant reduction in brain tissue homogenate levels of TNF-α 59.5 ± 8.4/50.2 ± 6.2 (p = 0.007) and TOS 99.3 ± 16.9/82.3 ± 7.8 (p = 0.01) in rats treated with EE; although interleukin 6 levels were increased in the treatment group compared to the sepsis group, this was not statistically significant. Neuronal damage (p = 0.00), pericellular/perivascular edema and inflammatory cell infiltration (p = 0.001) were also significantly lower in the treatment group compared to those in the sepsis group. These data suggest that Ecballium elaterium contains some components that exert protective effects against SAE in part by attenuating accumulation of proinflammatory cytokines, which may be important contributors to its anti-inflammatory effects during sepsis. PMID:28859554

  5. Pathogenetic and therapeutic perspectives on neurocognitive models in psychiatry: A synthesis of behavioral, brain imaging, and biological studies

    OpenAIRE

    Rao, Naren P.

    2012-01-01

    Neurocognitive assessments are useful to determine the locus of insult as well as functional capacities of patients on treatment. In psychiatry, neurocognitive assessment is useful in the identification of brain lesions, evaluation of cognitive deterioration over time, and advancement of theories regarding the neuroanatomical localization of symptoms. Neurocognitive models provide a bridging link between brain pathology and phenomenology. They provide a useful framework to understand the path...

  6. Patient-specific 3D printed model in delineating brain glioma and surrounding structures in a pediatric patient

    OpenAIRE

    Ivan Lau; Andrew Squelch; Yung Liang Wan; Alex Mun-Chung Wong; Werner Ducke; Zhonghua Sun

    2017-01-01

    Background and Objectives: Three-dimensional (3D) printing has been increasingly used in medicine with applications in the diagnostic assessment of disease extent, medical education and training, preoperative planning, and surgical simulation. The use of 3D printing in brain tumors is very limited. In this study, we presented our preliminary experience of creating patient-specific 3D printed model of a brain tumor in a pediatric patient and demonstrated the feasibility of using 3D printing in...

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

    International Nuclear Information System (INIS)

    Liu, Eva Sau Fan; Wu, Vincent Wing Cheung; Harris, Benjamin; Foote, Matthew; Lehman, Margot; Chan, Lawrence Wing Chi

    2017-01-01

    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, following 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.

  8. Deep ensemble learning of sparse regression models for brain disease diagnosis.

    Science.gov (United States)

    Suk, Heung-Il; Lee, Seong-Whan; Shen, Dinggang

    2017-04-01

    Recent studies on brain imaging analysis witnessed the core roles of machine learning techniques in computer-assisted intervention for brain disease diagnosis. Of various machine-learning techniques, sparse regression models have proved their effectiveness in handling high-dimensional data but with a small number of training samples, especially in medical problems. In the meantime, deep learning methods have been making great successes by outperforming the state-of-the-art performances in various applications. In this paper, we propose a novel framework that combines the two conceptually different methods of sparse regression and deep learning for Alzheimer's disease/mild cognitive impairment diagnosis and prognosis. Specifically, we first train multiple sparse regression models, each of which is trained with different values of a regularization control parameter. Thus, our multiple sparse regression models potentially select different feature subsets from the original feature set; thereby they have different powers to predict the response values, i.e., clinical label and clinical scores in our work. By regarding the response values from our sparse regression models as target-level representations, we then build a deep convolutional neural network for clinical decision making, which thus we call 'Deep Ensemble Sparse Regression Network.' To our best knowledge, this is the first work that combines sparse regression models with deep neural network. In our experiments with the ADNI cohort, we validated the effectiveness of the proposed method by achieving the highest diagnostic accuracies in three classification tasks. We also rigorously analyzed our results and compared with the previous studies on the ADNI cohort in the literature. Copyright © 2017 Elsevier B.V. All rights reserved.

  9. Progesterone treatment shows benefit in a pediatric model of moderate to severe bilateral brain injury.

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    Rastafa I Geddes

    Full Text Available Controlled cortical impact (CCI models in adult and aged Sprague-Dawley (SD rats have been used extensively to study medial prefrontal cortex (mPFC injury and the effects of post-injury progesterone treatment, but the hormone's effects after traumatic brain injury (TBI in juvenile animals have not been determined. In the present proof-of-concept study we investigated whether progesterone had neuroprotective effects in a pediatric model of moderate to severe bilateral brain injury.Twenty-eight-day old (PND 28 male Sprague Dawley rats received sham (n = 24 or CCI (n = 47 injury and were given progesterone (4, 8, or 16 mg/kg per 100 g body weight or vehicle injections on post-injury days (PID 1-7, subjected to behavioral testing from PID 9-27, and analyzed for lesion size at PID 28.The 8 and 16 mg/kg doses of progesterone were observed to be most beneficial in reducing the effect of CCI on lesion size and behavior in PND 28 male SD rats.Our findings suggest that a midline CCI injury to the frontal cortex will reliably produce a moderate TBI comparable to what is seen in the adult male rat and that progesterone can ameliorate the injury-induced deficits.

  10. Cellular model studies of brain-mediated phototherapy on Alzheimer's disease

    Science.gov (United States)

    Zhu, Ling; Liu, Timon Cheng-Yi; Hu, Bina; Li, Xiao-Yun; Wang, Yong-Qing

    2008-12-01

    Alzheimer's disease (AD) is now the most common neurodegenerative disease. Despite approval of several drugs for AD, the disease continues to rob millions of their memories and their lives. We have studied the cellular models of brain-mediated phototherapy on AD, and the studies will be reviewed in this paper. Genetic studies have shown that dysfunction of amyloid β-protein (Aβ) or tau is sufficient to cause AD. Aβ or Aβ induced redox stress induced neuron apoptosis might be as a cellular model of AD. We found red light at 640+/-15 nm from light emitting diode array (RLED640) might inhibit Aβ 25-35 induced PC12 cell apoptosis, which is mediated by cyclic adenosine monophosphate, and it might inhibit hydrogen peroxide (H2O2) induced differentiated PC12 cell (dPC12) apoptosis, which is mediated by tyrosine hydroxylase. There is rhythm dysfunction in AD. We found low intensity 810 nm laser irradiation might rehabilitate TNF-alpha induced inhibition of clock gen expression of NIH 3T3 fibroblasts. Our studies provide a foundation for photobiomodulation on brain to rehabilitate AD.

  11. Deconvolution-Based CT and MR Brain Perfusion Measurement: Theoretical Model Revisited and Practical Implementation Details

    Science.gov (United States)

    Fieselmann, Andreas; Kowarschik, Markus; Ganguly, Arundhuti; Hornegger, Joachim; Fahrig, Rebecca

    2011-01-01

    Deconvolution-based analysis of CT and MR brain perfusion data is widely used in clinical practice and it is still a topic of ongoing research activities. In this paper, we present a comprehensive derivation and explanation of the underlying physiological model for intravascular tracer systems. We also discuss practical details that are needed to properly implement algorithms for perfusion analysis. Our description of the practical computer implementation is focused on the most frequently employed algebraic deconvolution methods based on the singular value decomposition. In particular, we further discuss the need for regularization in order to obtain physiologically reasonable results. We include an overview of relevant preprocessing steps and provide numerous references to the literature. We cover both CT and MR brain perfusion imaging in this paper because they share many common aspects. The combination of both the theoretical as well as the practical aspects of perfusion analysis explicitly emphasizes the simplifications to the underlying physiological model that are necessary in order to apply it to measured data acquired with current CT and MR scanners. PMID:21904538

  12. Computational Modeling and Neuroimaging Techniques for Targeting during Deep Brain Stimulation

    Science.gov (United States)

    Sweet, Jennifer A.; Pace, Jonathan; Girgis, Fady; Miller, Jonathan P.

    2016-01-01

    Accurate surgical localization of the varied targets for deep brain stimulation (DBS) is a process undergoing constant evolution, with increasingly sophisticated techniques to allow for highly precise targeting. However, despite the fastidious placement of electrodes into specific structures within the brain, there is increasing evidence to suggest that the clinical effects of DBS are likely due to the activation of widespread neuronal networks directly and indirectly influenced by the stimulation of a given target. Selective activation of these complex and inter-connected pathways may further improve the outcomes of currently treated diseases by targeting specific fiber tracts responsible for a particular symptom in a patient-specific manner. Moreover, the delivery of such focused stimulation may aid in the discovery of new targets for electrical stimulation to treat additional neurological, psychiatric, and even cognitive disorders. As such, advancements in surgical targeting, computational modeling, engineering designs, and neuroimaging techniques play a critical role in this process. This article reviews the progress of these applications, discussing the importance of target localization for DBS, and the role of computational modeling and novel neuroimaging in improving our understanding of the pathophysiology of diseases, and thus paving the way for improved selective target localization using DBS. PMID:27445709

  13. A multi-channel magnetic induction tomography measurement system for human brain model imaging

    International Nuclear Information System (INIS)

    Xu, Zheng; Luo, Haijun; He, Wei; He, Chuanhong; Song, Xiaodong; Zahng, Zhanglong

    2009-01-01

    This paper proposes a multi-channel magnetic induction tomography measurement system for biological conductivity imaging in a human brain model. A hemispherical glass bowl filled with a salt solution is used as the human brain model; meanwhile, agar blocks of different conductivity are placed in the solution to simulate the intracerebral hemorrhage. The excitation and detection coils are fixed co-axially, and the axial gradiometer is used as the detection coil in order to cancel the primary field. On the outer surface of the glass bowl, 15 sensor units are arrayed in two circles as measurement parts, and a single sensor unit for canceling the phase drift is placed beside the glass bowl. The phase sensitivity of our system is 0.204°/S m −1 with the excitation frequency of 120 kHz and the phase noise is in the range of −0.03° to +0.05°. Only the coaxial detection coil is available for each excitation coil; therefore, 15 phase data are collected in each measurement turn. Finally, the two-dimensional images of conductivity distribution are obtained using an interpolation algorithm. The frequency-varying experiment indicates that the imaging quality becomes better as the excitation frequency is increased

  14. Deconvolution-Based CT and MR Brain Perfusion Measurement: Theoretical Model Revisited and Practical Implementation Details.

    Science.gov (United States)

    Fieselmann, Andreas; Kowarschik, Markus; Ganguly, Arundhuti; Hornegger, Joachim; Fahrig, Rebecca

    2011-01-01

    Deconvolution-based analysis of CT and MR brain perfusion data is widely used in clinical practice and it is still a topic of ongoing research activities. In this paper, we present a comprehensive derivation and explanation of the underlying physiological model for intravascular tracer systems. We also discuss practical details that are needed to properly implement algorithms for perfusion analysis. Our description of the practical computer implementation is focused on the most frequently employed algebraic deconvolution methods based on the singular value decomposition. In particular, we further discuss the need for regularization in order to obtain physiologically reasonable results. We include an overview of relevant preprocessing steps and provide numerous references to the literature. We cover both CT and MR brain perfusion imaging in this paper because they share many common aspects. The combination of both the theoretical as well as the practical aspects of perfusion analysis explicitly emphasizes the simplifications to the underlying physiological model that are necessary in order to apply it to measured data acquired with current CT and MR scanners.

  15. Mouse model of diffuse brain damage following anoxia, evaluated by a new assay of generalized arousal.

    Science.gov (United States)

    Arrieta-Cruz, Isabel; Pfaff, Donald W; Shelley, Deborah N

    2007-06-01

    Diffuse brain damage following anoxia due to cardiac failure, drowning, carbon monoxide exposure or other accidents constitutes a major medical problem. We have created a novel mouse model using the breathing of pure nitrogen, followed by a recently developed assay that reflects an operational definition of generalized arousal. The operational definition is precise, complete, and leads to quantitative, physical measures in a genetically tractable animal. Exposure to pure nitrogen for controlled periods had a surprising bifurcate effect: about half the mice survived with neurological measures that were virtually normal while the other half died. The new assay detected behavioral deficits unrevealed by neurological screening. Two important features of the results were that (i) deficits were not equal across the circadian cycle, and (ii) deficits were not equal across all the measures within the operational definition of arousal. Specific voluntary motor measurements were decreased in a manner that depended on the phase of the circadian cycle. Sensory responses were also decreased, with an emphasis on vertical movement responses; but, interestingly, fear learning was not damaged. This study establishes the first useful approach to diffuse brain damage in a genetically tractable animal. The model and its outcome measurements will be useful during future attempts at amelioration of acquired neurological disabilities following hypoxic-ischemic injuries.

  16. Three-dimensional brain arteriovenous malformation models for clinical use and resident training.

    Science.gov (United States)

    Dong, Mengqi; Chen, Guangzhong; Li, Jianyi; Qin, Kun; Ding, Xiaowen; Peng, Chao; Zhou, Dong; Lin, Xiaofeng

    2018-01-01

    To fabricate three-dimensional (3D) models of brain arteriovenous malformation (bAVM) and report our experience with customized 3D printed models of patients with bAVM as an educational and clinical tool for patients, doctors, and surgical residents. Using computerized tomography angiography (CTA) or digital subtraction angiography (DSA) images, the rapid prototyping process was completed with specialized software and "in-house" 3D printing service. Intraoperative validation of model fidelity was performed by comparing to DSA images of the same patient during the endovascular treatment process. 3D bAVM models were used for preoperative patient education and consultation, surgical planning, and resident training. 3D printed bAVM models were successful made. By neurosurgeons' evaluation, the printed models precisely replicated the actual bAVM structure of the same patients (n = 7, 97% concordance, range 95%-99% with average of 3D models was associated shorter time for preoperative patient education and consultation, higher acceptable of the procedure for patients and relatives, shorter time between obtaining intraoperative DSA data and the start of endovascular treatment. Thirty surgical residents from residency programs tested the bAVM models and provided feedback on their resemblance to real bAVM structures and the usefulness of printed solid model as an educational tool. Patient-specific 3D printed models of bAVM can be constructed with high fidelity. 3D printed bAVM models were proven to be helpful in preoperative patient consultation, surgical planning, and resident training. Copyright © 2017 The Authors. Published by Wolters Kluwer Health, Inc. All rights reserved.

  17. Brain and Behavioral Pathology in an Animal Model of Wernicke’s Encephalopathy and Wernicke-Korsakoff Syndrome

    Science.gov (United States)

    Vetreno, Ryan P.; Ramos, Raddy L.; Anzalone, Steven; Savage, Lisa M.

    2012-01-01

    Animal models provide the opportunity for in-depth and experimental investigation into the anatomical and physiological underpinnings of human neurological disorders. Rodent models of thiamine deficiency have yielded significant insight into the structural, neurochemical and cognitive deficits associated with thiamine deficiency as well as proven useful toward greater understanding of memory function in the intact brain. In this review, we discuss the anatomical, neurochemical and behavioral changes that occur during the acute and chronic phases of thiamine deficiency and describe how rodent models of Wernicke-Korsakoff Syndrome aid in developing a more detailed picture of brain structures involved in learning and memory. PMID:22192411

  18. Cell-based in vitro blood-brain barrier model can rapidly evaluate nanoparticles' brain permeability in association with particle size and surface modification.

    Science.gov (United States)

    Hanada, Sanshiro; Fujioka, Kouki; Inoue, Yuriko; Kanaya, Fumihide; Manome, Yoshinobu; Yamamoto, Kenji

    2014-01-24

    The possibility of nanoparticle (NP) uptake to the human central nervous system is a major concern. Recent reports showed that in animal models, nanoparticles (NPs) passed through the blood-brain barrier (BBB). For the safe use of NPs, it is imperative to evaluate the permeability of NPs through the BBB. Here we used a commercially available in vitro BBB model to evaluate the permeability of NPs for a rapid, easy and reproducible assay. The model is reconstructed by culturing both primary rat brain endothelial cells and pericytes to support the tight junctions of endothelial cells. We used the permeability coefficient (P(app)) to determine the permeability of NPs. The size dependency results, using fluorescent silica NPs (30, 100, and 400 nm), revealed that the Papp for the 30 nm NPs was higher than those of the larger silica. The surface charge dependency results using Qdots® (amino-, carboxyl-, and PEGylated-Qdots), showed that more amino-Qdots passed through the model than the other Qdots. Usage of serum-containing buffer in the model resulted in an overall reduction of permeability. In conclusion, although additional developments are desired to elucidate the NPs transportation, we showed that the BBB model could be useful as a tool to test the permeability of nanoparticles.

  19. Modeling learning in brain stem and cerebellar sites responsible for VOR plasticity

    Science.gov (United States)

    Quinn, K. J.; Didier, A. J.; Baker, J. F.; Peterson, B. W.

    1998-01-01

    A simple model of vestibuloocular reflex (VOR) function was used to analyze several hypotheses currently held concerning the characteristics of VOR plasticity. The network included a direct vestibular pathway and an indirect path via the cerebellum. An optimization analysis of this model suggests that regulation of brain stem sites is critical for the proper modification of VOR gain. A more physiologically plausible learning rule was also applied to this network. Analysis of these simulation results suggests that the preferred error correction signal controlling gain modification of the VOR is the direct output of the accessory optic system (AOS) to the vestibular nuclei vs. a signal relayed through the cerebellum via floccular Purkinje cells. The potential anatomical and physiological basis for this conclusion is discussed, in relation to our current understanding of the latency of the adapted VOR response.

  20. A network of networks model to study phase synchronization using structural connection matrix of human brain

    Science.gov (United States)

    Ferrari, F. A. S.; Viana, R. L.; Reis, A. S.; Iarosz, K. C.; Caldas, I. L.; Batista, A. M.

    2018-04-01

    The cerebral cortex plays a key role in complex cortical functions. It can be divided into areas according to their function (motor, sensory and association areas). In this paper, the cerebral cortex is described as a network of networks (cortex network), we consider that each cortical area is composed of a network with small-world property (cortical network). The neurons are assumed to have bursting properties with the dynamics described by the Rulkov model. We study the phase synchronization of the cortex network and the cortical networks. In our simulations, we verify that synchronization in cortex network is not homogeneous. Besides, we focus on the suppression of neural phase synchronization. Synchronization can be related to undesired and pathological abnormal rhythms in the brain. For this reason, we consider the delayed feedback control to suppress the synchronization. We show that delayed feedback control is efficient to suppress synchronous behavior in our network model when an appropriate signal intensity and time delay are defined.

  1. Three-Dimensional Blood-Brain Barrier Model for in vitro Studies of Neurovascular Pathology

    Science.gov (United States)

    Cho, Hansang; Seo, Ji Hae; Wong, Keith H. K.; Terasaki, Yasukazu; Park, Joseph; Bong, Kiwan; Arai, Ken; Lo, Eng H.; Irimia, Daniel

    2015-10-01

    Blood-brain barrier (BBB) pathology leads to neurovascular disorders and is an important target for therapies. However, the study of BBB pathology is difficult in the absence of models that are simple and relevant. In vivo animal models are highly relevant, however they are hampered by complex, multi-cellular interactions that are difficult to decouple. In vitro models of BBB are simpler, however they have limited functionality and relevance to disease processes. To address these limitations, we developed a 3-dimensional (3D) model of BBB on a microfluidic platform. We verified the tightness of the BBB by showing its ability to reduce the leakage of dyes and to block the transmigration of immune cells towards chemoattractants. Moreover, we verified the localization at endothelial cell boundaries of ZO-1 and VE-Cadherin, two components of tight and adherens junctions. To validate the functionality of the BBB model, we probed its disruption by neuro-inflammation mediators and ischemic conditions and measured the protective function of antioxidant and ROCK-inhibitor treatments. Overall, our 3D BBB model provides a robust platform, adequate for detailed functional studies of BBB and for the screening of BBB-targeting drugs in neurological diseases.

  2. Memory as the "whole brain work": a large-scale model based on "oscillations in super-synergy".

    Science.gov (United States)

    Başar, Erol

    2005-01-01

    According to recent trends, memory depends on several brain structures working in concert across many levels of neural organization; "memory is a constant work-in progress." The proposition of a brain theory based on super-synergy in neural populations is most pertinent for the understanding of this constant work in progress. This report introduces a new model on memory basing on the processes of EEG oscillations and Brain Dynamics. This model is shaped by the following conceptual and experimental steps: 1. The machineries of super-synergy in the whole brain are responsible for formation of sensory-cognitive percepts. 2. The expression "dynamic memory" is used for memory processes that evoke relevant changes in alpha, gamma, theta and delta activities. The concerted action of distributed multiple oscillatory processes provides a major key for understanding of distributed memory. It comprehends also the phyletic memory and reflexes. 3. The evolving memory, which incorporates reciprocal actions or reverberations in the APLR alliance and during working memory processes, is especially emphasized. 4. A new model related to "hierarchy of memories as a continuum" is introduced. 5. The notions of "longer activated memory" and "persistent memory" are proposed instead of long-term memory. 6. The new analysis to recognize faces emphasizes the importance of EEG oscillations in neurophysiology and Gestalt analysis. 7. The proposed basic framework called "Memory in the Whole Brain Work" emphasizes that memory and all brain functions are inseparable and are acting as a "whole" in the whole brain. 8. The role of genetic factors is fundamental in living system settings and oscillations and accordingly in memory, according to recent publications. 9. A link from the "whole brain" to "whole body," and incorporation of vegetative and neurological system, is proposed, EEG oscillations and ultraslow oscillations being a control parameter.

  3. A Computational Model for the Automatic Diagnosis of Attention Deficit Hyperactivity Disorder Based on Functional Brain Volume

    Directory of Open Access Journals (Sweden)

    Lirong Tan

    2017-09-01

    Full Text Available In this paper, we investigated the problem of computer-aided diagnosis of Attention Deficit Hyperactivity Disorder (ADHD using machine learning techniques. With the ADHD-200 dataset, we developed a Support Vector Machine (SVM model to classify ADHD patients from typically developing controls (TDCs, using the regional brain volumes as predictors. Conventionally, the volume of a brain region was considered to be an anatomical feature and quantified using structural magnetic resonance images. One major contribution of the present study was that we had initially proposed to measure the regional brain volumes using fMRI images. Brain volumes measured from fMRI images were denoted as functional volumes, which quantified the volumes of brain regions that were actually functioning during fMRI imaging. We compared the predictive power of functional volumes with that of regional brain volumes measured from anatomical images, which were denoted as anatomical volumes. The former demonstrated higher discriminative power than the latter for the classification of ADHD patients vs. TDCs. Combined with our two-step feature selection approach which integrated prior knowledge with the recursive feature elimination (RFE algorithm, our SVM classification model combining functional volumes and demographic characteristics achieved a balanced accuracy of 67.7%, which was 16.1% higher than that of a relevant model published previously in the work of Sato et al. Furthermore, our classifier highlighted 10 brain regions that were most discriminative in distinguishing between ADHD patients and TDCs. These 10 regions were mainly located in occipital lobe, cerebellum posterior lobe, parietal lobe, frontal lobe, and temporal lobe. Our present study using functional images will likely provide new perspectives about the brain regions affected by ADHD.

  4. Maternal pravastatin prevents altered fetal brain development in a preeclamptic CD-1 mouse model.

    Directory of Open Access Journals (Sweden)

    Alissa R Carver

    Full Text Available Using an animal model, we have previously shown that preeclampsia results in long-term adverse neuromotor outcomes in the offspring, and this phenotype was prevented by antenatal treatment with pravastatin. This study aims to localize the altered neuromotor programming in this animal model and to evaluate the role of pravastatin in its prevention.For the preeclampsia model, pregnant CD-1 mice were randomly allocated to injection of adenovirus carrying sFlt-1 or its control virus carrying mFc into the tail vein. Thereafter they received pravastatin (sFlt-1-pra "experimental group" or water (sFlt-1 "positive control" until weaning. The mFc group ("negative control" received water. Offspring at 6 months of age were sacrificed, and whole brains underwent magnetic resonance imaging (MRI. MRIs were performed using an 11.7 Tesla vertical bore MRI scanner. T2 weighted images were acquired to evaluate the volumes of 28 regions of interest, including areas involved in adaptation and motor, spatial and sensory function. Cytochemistry and cell quantification was performed using neuron-specific Nissl stain. One-way ANOVA with multiple comparison testing was used for statistical analysis.Compared with control offspring, male sFlt-1 offspring have decreased volumes in the fimbria, periaquaductal gray, stria medullaris, and ventricles and increased volumes in the lateral globus pallidus and neocortex; however, female sFlt-1 offspring showed increased volumes in the ventricles, stria medullaris, and fasciculus retroflexus and decreased volumes in the inferior colliculus, thalamus, and lateral globus pallidus. Neuronal quantification via Nissl staining exhibited decreased cell counts in sFlt-1 offspring neocortex, more pronounced in males. Prenatal pravastatin treatment prevented these changes.Preeclampsia alters brain development in sex-specific patterns, and prenatal pravastatin therapy prevents altered neuroanatomic programming in this animal model.

  5. Assessment of the Blood-Brain Barrier Permeability of Potential Neuroprotective Aurones in Parallel Artificial Membrane Permeability Assay and Porcine Brain Endothelial Cell Models.

    Science.gov (United States)

    Liew, Kok-Fui; Hanapi, Nur Aziah; Chan, Kit-Lam; Yusof, Siti R; Lee, Chong-Yew

    2017-02-01

    Previously, several aurone derivatives were identified with promising neuroprotective activities. In developing these compounds to target the central nervous system (CNS), an assessment of their blood-brain barrier (BBB) permeability was performed using in vitro BBB models: parallel artificial membrane permeability assay-BBB which measures passive permeability and primary porcine brain endothelial cell model which enables determination of the involvement of active transport mechanism. Parallel artificial membrane permeability assay-BBB identified most compounds with high passive permeability, with 3 aurones having exceptional P e values highlighting the importance of basic amine moieties and optimal lipophilicity for good passive permeability. Bidirectional permeability assays with porcine brain endothelial cell showed a significant net influx permeation of the aurones indicating a facilitated uptake mechanism in contrast to donepezil, a CNS drug included in the evaluation which only displayed passive permeation. From pH-dependent permeability assay coupled with data analysis using pCEL-X software, intrinsic transcellular permeability (P o ) of a representative aurone 4-3 was determined, considering factors such as the aqueous boundary layer that may hinder accurate in vitro to in vivo correlation. The P o  value determined supported the in vivo feasibility of the aurone as a CNS-active compound. Copyright © 2017 American Pharmacists Association®. Published by Elsevier Inc. All rights reserved.

  6. Does brain slices from pentylenetetrazole-kindled mice provide a more predictive screening model for antiepileptic drugs?

    DEFF Research Database (Denmark)

    Hansen, Suzanne L.; Sterjev, Zoran; Werngreen, Marie

    2012-01-01

    screening model for AEDs. To this end, we compared the in vitro and in vivo pharmacological profile of several selected AEDs (phenobarbital, phenytoin, tiagabine, fosphenytoin, valproate, and carbamazepine) along with citalopram using the PTZ-kindled model and brain slices from naïve, saline...

  7. A Model for Predicting Cognitive and Emotional Health from Structural and Functional Neurocircuitry Following Traumatic Brain Injury

    Science.gov (United States)

    2013-10-01

    International Journal of Obesity 2009 Reviewer, European Journal of Neuroscience 2009-2013 Reviewer, International Journal of Eating Disorders...A Model for Predicting Cognitive and Emotional Health from Structural and Functional Neurocircuitry Following Traumatic Brain Injury...TITLE AND SUBTITLE 5a. CONTRACT NUMBER W81XWH-12-1-0386 A Model for Predicting Cognitive and Emotional Health from Structural and Functional

  8. A generative probabilistic model and discriminative extensions for brain lesion segmentation – with application to tumor and stroke

    Science.gov (United States)

    Menze, Bjoern H.; Van Leemput, Koen; Lashkari, Danial; Riklin-Raviv, Tammy; Geremia, Ezequiel; Alberts, Esther; Gruber, Philipp; Wegener, Susanne; Weber, Marc-André; Székely, Gabor; Ayache, Nicholas; Golland, Polina

    2016-01-01

    We introduce a generative probabilistic model for segmentation of brain lesions in multi-dimensional images that generalizes the EM segmenter, a common approach for modelling brain images using Gaussian mixtures and a probabilistic tissue atlas that employs expectation-maximization (EM) to estimate the label map for a new image. Our model augments the probabilistic atlas of the healthy tissues with a latent atlas of the lesion. We derive an estimation algorithm with closed-form EM update equations. The method extracts a latent atlas prior distribution and the lesion posterior distributions jointly from the image data. It delineates lesion areas individually in each channel, allowing for differences in lesion appearance across modalities, an important feature of many brain tumor imaging sequences. We also propose discriminative model extensions to map the output of the generative model to arbitrary labels with semantic and biological meaning, such as “tumor core” or “fluid-filled structure”, but without a one-to-one correspondence to the hypo-or hyper-intense lesion areas identified by the generative model. We test the approach in two image sets: the publicly available BRATS set of glioma patient scans, and multimodal brain images of patients with acute and subacute ischemic stroke. We find the generative model that has been designed for tumor lesions to generalize well to stroke images, and the generative-discriminative model to be one of the top ranking methods in the BRATS evaluation. PMID:26599702

  9. How much detail is needed in modeling a transcranial magnetic stimulation figure-8 coil: Measurements and brain simulations

    OpenAIRE

    Petrov, Petar I.; Mandija, Stefano; Sommer, Iris E. C.; van den Berg, Cornelis A. T.; Neggers, Sebastiaan F. W.

    2017-01-01

    Background: Despite TMS wide adoption, its spatial and temporal patterns of neuronal effects are not well understood. Although progress has been made in predicting induced currents in the brain using realistic finite element models (FEM), there is little consensus on how a magnetic field of a typical TMS coil should be modeled. Empirical validation of such models is limited and subject to several limitations. Methods: We evaluate and empirically validate models of a figure-of-eight TMS coil t...

  10. A rat model of smoke inhalation injury: Influence of combustion smoke on gene expression in the brain

    International Nuclear Information System (INIS)

    Lee, Heung M.; Greeley, George H.; Herndon, David N.; Sinha, Mala; Luxon, Bruce A.; Englander, Ella W.

    2005-01-01

    Acute smoke inhalation causes death and injury in victims of home and industrial fires as well as victims of combat situations. The lethal factors in combustion smoke inhalation are toxic gases and oxygen deficiency, with carbon monoxide (CO) as a primary cause of death. In survivors, inhalation of smoke can result in severe immediate and delayed neuropathologies. To gain insight into the progression of molecular events contributing to smoke inhalation sequelae in the brain, we developed a smoke inhalation rat model and conducted a genome-wide analysis of gene expression. Microarray analysis revealed a modified brain transcriptome with changes peaking at 24 h and subsiding within 7 days post-smoke. Overall, smoke inhalation downregulated genes associated with synaptic function, neurotransmission, and neurotrophic support, and upregulated genes associated with stress responses, including nitric oxide synthesis, antioxidant defenses, proteolysis, inflammatory response, and glial activation. Notably, among the affected genes, many have been previously implicated in other types of brain injury, demonstrating the usefulness of microarrays for analysis of changes in gene expression in complex insults. In accord with previously described modulations of nitric oxide homeostasis in CO poisoning, microarray analysis revealed increased brain expression of nitric oxide synthase (NOS) and NOS ligand after inhalation of smoke. Furthermore, immunostaining showed significant elevations in perivascular NOS and in protein nitration, corroborating the involvement of nitric oxide perturbations in post-smoke sequelae in the brain. Thus, the new rat model, in combination with microarray analyses, affords insight into the complex molecular pathophysiology of smoke inhalation in the brain

  11. Evolutionary modeling and correcting for observation error support a 3/5 brain-body allometry for primates.

    Science.gov (United States)

    Grabowski, Mark; Voje, Kjetil L; Hansen, Thomas F

    2016-05-01

    The tight brain-body allometry across mammals and primates has motivated and informed many hypotheses about brain evolution in humans and other taxa. While a 2/3 or a 3/4 scaling is often at the core of such research, such exponents are derived from estimates based on particular statistical and evolutionary assumptions without careful consideration of how either may influence findings. Here we quantify primate brain-body allometry using phylogenetic comparative methods based on models of both adaptive and constrained evolution, and estimate and account for observational error in both response and predictor variables. Our results supported an evolutionary model in which brain size is directly constrained to evolve in unison with body size, rather than adapting to changes in the latter. The effects of controlling for phylogeny and observation error were substantial, and our analysis yielded a novel 3/5 scaling exponent for primate brain-body evolutionary allometry. Using this exponent with the latest brain- and body-size estimates to calculate new encephalization quotients for apes, humans, and fossil hominins, we found early hominins were substantially more encephalized than previously thought. Copyright © 2016 Elsevier Ltd. All rights reserved.

  12. Pathogenesis, Experimental Models and Contemporary Pharmacotherapy of Irritable Bowel Syndrome: Story About the Brain-Gut Axis.

    Science.gov (United States)

    Tsang, S W; Auyeung, K K W; Bian, Z X; Ko, J K S

    2016-01-01

    Although the precise pathophysiology of irritable bowel syndrome (IBS) remains unknown, it is generally considered to be a disorder of the brain-gut axis, representing the disruption of communication between the brain and the digestive system. The present review describes advances in understanding the pathophysiology and experimental approaches in studying IBS, as well as providing an update of the therapies targeting brain-gut axis in the treatment of the disease. Causal factors of IBS are reviewed. Following this, the preclinical experimental models of IBS will be introduced. Besides, both current and future therapeutic approaches of IBS will be discussed. When signal of the brain-gut axis becomes misinterpreted, it may lead to dysregulation of both central and enteric nervous systems, altered intestinal motility, increased visceral sensitivity and consequently contributing to the development of IBS. Interference of the brain-gut axis can be modulated by various psychological and environmental factors. Although there is no existing animal experiment that can represent this complex multifactorial disease, these in vivo models are clinically relevant readouts of gastrointestinal functions being essential to the identification of effective treatments of IBS symptoms as well as their molecular targets. Understanding the brain-gut axis is essential in developing the effective therapy for IBS. Therapies include improvement of GI motor functions, relief of visceral hypersensitivity and pain, attenuation of autonomic dysfunctions and suppression of mucosal immune activation. Target-oriented therapies that provide symptomatic, psychological and physiological benefits could surely help to improve the quality of life of IBS patients.

  13. Neurobiology of the basal platyhelminth Macrostomum lignano: map and digital 3D model of the juvenile brain neuropile.

    Science.gov (United States)

    Morris, Joshua; Cardona, Albert; De Miguel-Bonet, Maria Del Mar; Hartenstein, Volker

    2007-08-01

    We have analyzed brain structure in Macrostomum lignano, a representative of the basal platyhelminth taxon Macrostomida. Using confocal microscopy and digital 3D modeling software on specimens labeled with general markers for neurons (tyrTub), muscles (phalloidin), and nuclei (Sytox), an atlas and digital model of the juvenile Macrostomum brain was generated. The brain forms a ganglion with a central neuropile surrounded by a cortex of neuronal cell bodies. The neuropile contains a stereotypical array of compact axon bundles, as well as branched terminal axons and dendrites. Muscle fibers penetrate the flatworm brain horizontally and vertically at invariant positions. Beside the invariant pattern of neurite bundles, these "cerebral muscles" represent a convenient system of landmarks that help define discrete compartments in the juvenile brain. Commissural axon bundles define a dorsal and ventro-medial neuropile compartment, respectively. Longitudinal axons that enter the neuropile through an invariant set of anterior and posterior nerve roots define a ventro-basal and a central medial compartment in the neuropile. Flanking these "fibrous" compartments are neuropile domains that lack thick axon bundles and are composed of short collaterals and terminal arborizations of neurites. Two populations of neurons, visualized by antibodies against FMRFamide and serotonin, respectively, were mapped relative to compartment boundaries. This study will aid in the documentation and interpretation of patterns of gene expression, as well as functional studies, in the developing Macrostomum brain.

  14. The effects of voluntary, involuntary, and forced exercises on brain-derived neurotrophic factor and motor function recovery: a rat brain ischemia model.

    Directory of Open Access Journals (Sweden)

    Zheng Ke

    Full Text Available BACKGROUND: Stroke rehabilitation with different exercise paradigms has been investigated, but which one is more effective in facilitating motor recovery and up-regulating brain neurotrophic factor (BDNF after brain ischemia would be interesting to clinicians and patients. Voluntary exercise, forced exercise, and involuntary muscle movement caused by functional electrical stimulation (FES have been individually demonstrated effective as stroke rehabilitation intervention. The aim of this study was to investigate the effects of these three common interventions on brain BDNF changes and motor recovery levels using a rat ischemic stroke model. METHODOLOGY/PRINCIPAL FINDINGS: One hundred and seventeen Sprague-Dawley rats were randomly distributed into four groups: Control (Con, Voluntary exercise of wheel running (V-Ex, Forced exercise of treadmill running (F-Ex, and Involuntary exercise of FES (I-Ex with implanted electrodes placed in two hind limb muscles on the affected side to mimic gait-like walking pattern during stimulation. Ischemic stroke was induced in all rats with the middle cerebral artery occlusion/reperfusion model and fifty-seven rats had motor deficits after stroke. Twenty-four hours after reperfusion, rats were arranged to their intervention programs. De Ryck's behavioral test was conducted daily during the 7-day intervention as an evaluation tool of motor recovery. Serum corticosterone concentration and BDNF levels in the hippocampus, striatum, and cortex were measured after the rats were sacrificed. V-Ex had significantly better motor recovery in the behavioral test. V-Ex also had significantly higher hippocampal BDNF concentration than F-Ex and Con. F-Ex had significantly higher serum corticosterone level than other groups. CONCLUSION/SIGNIFICANCE: Voluntary exercise is the most effective intervention in upregulating the hippocampal BDNF level, and facilitating motor recovery. Rats that exercised voluntarily also showed less

  15. In vitro blood-brain barrier models for drug research: state-of-the-art and new perspectives on reconstituting these models on artificial basement membrane platforms.

    Science.gov (United States)

    Banerjee, Jayati; Shi, Yejiao; Azevedo, Helena S

    2016-09-01

    In vitro blood-brain barrier (BBB) models are indispensable screening tools for obtaining early information about the brain-penetrating behaviour of promising drug candidates. Until now, in vitro BBB models have focused on investigating the interplay among cellular components of neurovascular units and the effect of fluidic sheer stress in sustaining normal BBB phenotype and functions. However, an area that has received less recognition is the role of the noncellular basement membrane (BM) in modulating BBB physiology. This review describes the state-of-the-art on in vitro BBB models relevant in drug discovery research and highlights their strengths, weaknesses and the utility potential of some of these models in testing the permeability of nanocarriers as vectors for delivering therapeutics to the brain. Importantly, our review also introduces a new concept of engineering artificial BM platforms for reconstituting BBB models in vitro. Copyright © 2016 Elsevier Ltd. All rights reserved.

  16. Developing a multiscale, multi-resolution agent-based brain tumor model by graphics processing units

    Directory of Open Access Journals (Sweden)

    Zhang Le

    2011-12-01

    Full Text Available Abstract Multiscale agent-based modeling (MABM has been widely used to simulate Glioblastoma Multiforme (GBM and its progression. At the intracellular level, the MABM approach employs a system of ordinary differential equations to describe quantitatively specific intracellular molecular pathways that determine phenotypic switches among cells (e.g. from migration to proliferation and vice versa. At the intercellular level, MABM describes cell-cell interactions by a discrete module. At the tissue level, partial differential equations are employed to model the diffusion of chemoattractants, which are the input factors of the intracellular molecular pathway. Moreover, multiscale analysis makes it possible to explore the molecules that play important roles in determining the cellular phenotypic switches that in turn drive the whole GBM expansion. However, owing to limited computational resources, MABM is currently a theoretical biological model that uses relatively coarse grids to simulate a few cancer cells in a small slice of brain cancer tissue. In order to improve this theoretical model to simulate and predict actual GBM cancer progression in real time, a graphics processing unit (GPU-based parallel computing algorithm was developed and combined with the multi-resolution design to speed up the MABM. The simulated results demonstrated that the GPU-based, multi-resolution and multiscale approach can accelerate the previous MABM around 30-fold with relatively fine grids in a large extracellular matrix. Therefore, the new model has great potential for simulating and predicting real-time GBM progression, if real experimental data are incorporated.

  17. Brain-computer interface with language model-electroencephalography fusion for locked-in syndrome.

    Science.gov (United States)

    Oken, Barry S; Orhan, Umut; Roark, Brian; Erdogmus, Deniz; Fowler, Andrew; Mooney, Aimee; Peters, Betts; Miller, Meghan; Fried-Oken, Melanie B

    2014-05-01

    Some noninvasive brain-computer interface (BCI) systems are currently available for locked-in syndrome (LIS) but none have incorporated a statistical language model during text generation. To begin to address the communication needs of individuals with LIS using a noninvasive BCI that involves rapid serial visual presentation (RSVP) of symbols and a unique classifier with electroencephalography (EEG) and language model fusion. The RSVP Keyboard was developed with several unique features. Individual letters are presented at 2.5 per second. Computer classification of letters as targets or nontargets based on EEG is performed using machine learning that incorporates a language model for letter prediction via Bayesian fusion enabling targets to be presented only 1 to 4 times. Nine participants with LIS and 9 healthy controls were enrolled. After screening, subjects first calibrated the system, and then completed a series of balanced word generation mastery tasks that were designed with 5 incremental levels of difficulty, which increased by selecting phrases for which the utility of the language model decreased naturally. Six participants with LIS and 9 controls completed the experiment. All LIS participants successfully mastered spelling at level 1 and one subject achieved level 5. Six of 9 control participants achieved level 5. Individuals who have incomplete LIS may benefit from an EEG-based BCI system, which relies on EEG classification and a statistical language model. Steps to further improve the system are discussed.

  18. Development of NMR imaging using CEST agents: application to brain tumor in a rodent model

    International Nuclear Information System (INIS)

    Flament, J.

    2012-01-01

    The study aimed at developing saturation transfer imaging of lipoCEST contrast agents for the detection of angiogenesis in a U87 mouse brain tumor model. A lipoCEST with a sensitivity threshold of 100 pM in vitro was optimized in order to make it compatible with CEST imaging in vivo. Thanks to the development of an experimental setup dedicated to CEST imaging, we evaluated lipoCEST to detect specifically tumor angiogenesis. We demonstrated for the first time that lipoCEST visualization was feasible in vivo in a mouse brain after intravenous injection. Moreover, the integrin α v β 3 over expressed during tumor angiogenesis can be specifically targeted using a functionalized lipoCEST with RGD peptide. The specific association between the RGD-lipoCEST and its target α v β 3 was confirmed by immunohistochemical data and fluorescence microscopy. Finally, in order to tend to a molecular imaging protocol by CEST-MRI, we developed a quantification tool of lipoCEST contrast agents. This tool is based on modeling of proton exchange processes in vivo. By taking into account both B0 and B1 fields inhomogeneities which can dramatically alter CEST contrast, we showed that the accuracy of our quantification tool was 300 pM in vitro. The tool was applied on in vivo data acquired on the U87 mouse model and the maximum concentration of RGD-lipoCEST linked to their molecular targets was evaluated to 1.8 nM. (author) [fr

  19. Hypothalamic deep brain stimulation reduces weight gain in an obesity-animal model.

    Directory of Open Access Journals (Sweden)

    William P Melega

    Full Text Available Prior studies of appetite regulatory networks, primarily in rodents, have established that targeted electrical stimulation of ventromedial hypothalamus (VMH can alter food intake patterns and metabolic homeostasis. Consideration of this method for weight modulation in humans with severe overeating disorders and morbid obesity can be further advanced by modeling procedures and assessing endpoints that can provide preclinical data on efficacy and safety. In this study we adapted human deep brain stimulation (DBS stereotactic methods and instrumentation to demonstrate in a large animal model the modulation of weight gain with VMH-DBS. Female Göttingen minipigs were used because of their dietary habits, physiologic characteristics, and brain structures that resemble those of primates. Further, these animals become obese on extra-feeding regimens. DBS electrodes were first bilaterally implanted into the VMH of the animals (n = 8 which were then maintained on a restricted food regimen for 1 mo following the surgery. The daily amount of food was then doubled for the next 2 mo in all animals to produce obesity associated with extra calorie intake, with half of the animals (n = 4 concurrently receiving continuous low frequency (50 Hz VMH-DBS. Adverse motoric or behavioral effects were not observed subsequent to the surgical procedure or during the DBS period. Throughout this 2 mo DBS period, all animals consumed the doubled amount of daily food. However, the animals that had received VMH-DBS showed a cumulative weight gain (6.1±0.4 kg; mean ± SEM that was lower than the nonstimulated VMH-DBS animals (9.4±1.3 kg; p<0.05, suggestive of a DBS-associated increase in metabolic rate. These results in a porcine obesity model demonstrate the efficacy and behavioral safety of a low frequency VMH-DBS application as a potential clinical strategy for modulation of body weight.

  20. Functional Characterization of IPSC-Derived Brain Cells as a Model for X-Linked Adrenoleukodystrophy.

    Directory of Open Access Journals (Sweden)

    Mauhamad Baarine

    Full Text Available X-ALD is an inherited neurodegenerative disorder where mutations in the ABCD1 gene result in clinically diverse phenotypes: the fatal disorder of cerebral childhood ALD (cALD or a milder disorder of adrenomyeloneuropathy (AMN. The various models used to study the pathobiology of X-ALD disease lack the appropriate presentation for different phenotypes of cALD vs AMN. This study demonstrates that induced pluripotent stem cells (IPSC derived brain cells astrocytes (Ast, neurons and oligodendrocytes (OLs express morphological and functional activities of the respective brain cell types. The excessive accumulation of saturated VLCFA, a "hallmark" of X-ALD, was observed in both AMN OLs and cALD OLs with higher levels observed in cALD OLs than AMN OLs. The levels of ELOVL1 (ELOVL Fatty Acid Elongase 1 mRNA parallel the VLCFA load in AMN and cALD OLs. Furthermore, cALD Ast expressed higher levels of proinflammatory cytokines than AMN Ast and control Ast with or without stimulation with lipopolysaccharide. These results document that IPSC-derived Ast and OLs from cALD and AMN fibroblasts mimic the respective biochemical disease phenotypes and thus provide an ideal platform to investigate the mechanism of VLCFA load in cALD OLs and VLCFA-induced inflammatory disease mechanisms of cALD Ast and thus for testing of new therapeutics for AMN and cALD disease of X-ALD.

  1. Mesoscopic segregation of excitation and inhibition in a brain network model.

    Directory of Open Access Journals (Sweden)

    Daniel Malagarriga

    2015-02-01

    Full Text Available Neurons in the brain are known to operate under a careful balance of excitation and inhibition, which maintains neural microcircuits within the proper operational range. How this balance is played out at the mesoscopic level of neuronal populations is, however, less clear. In order to address this issue, here we use a coupled neural mass model to study computationally the dynamics of a network of cortical macrocolumns operating in a partially synchronized, irregular regime. The topology of the network is heterogeneous, with a few of the nodes acting as connector hubs while the rest are relatively poorly connected. Our results show that in this type of mesoscopic network excitation and inhibition spontaneously segregate, with some columns acting mainly in an excitatory manner while some others have predominantly an inhibitory effect on their neighbors. We characterize the conditions under which this segregation arises, and relate the character of the different columns with their topological role within the network. In particular, we show that the connector hubs are preferentially inhibitory, the more so the larger the node's connectivity. These results suggest a potential mesoscale organization of the excitation-inhibition balance in brain networks.

  2. Pencilbeam irradiation technique for whole brain radiotherapy: technical and biological challenges in a small animal model.

    Science.gov (United States)

    Schültke, Elisabeth; Trippel, Michael; Bräuer-Krisch, Elke; Renier, Michel; Bartzsch, Stefan; Requardt, Herwig; Döbrössy, Máté D; Nikkhah, Guido

    2013-01-01

    We have conducted the first in-vivo experiments in pencilbeam irradiation, a new synchrotron radiation technique based on the principle of microbeam irradiation, a concept of spatially fractionated high-dose irradiation. In an animal model of adult C57 BL/6J mice we have determined technical and physiological limitations with the present technical setup of the technique. Fifty-eight animals were distributed in eleven experimental groups, ten groups receiving whole brain radiotherapy with arrays of 50 µm wide beams. We have tested peak doses ranging between 172 Gy and 2,298 Gy at 3 mm depth. Animals in five groups received whole brain radiotherapy with a center-to-center (ctc) distance of 200 µm and a peak-to-valley ratio (PVDR) of ∼ 100, in the other five groups the ctc was 400 µm (PVDR ∼ 400). Motor and memory abilities were assessed during a six months observation period following irradiation. The lower dose limit, determined by the technical equipment, was at 172 Gy. The LD50 was about 1,164 Gy for a ctc of 200 µm and higher than 2,298 Gy for a ctc of 400 µm. Age-dependent loss in motor and memory performance was seen in all groups. Better overall performance (close to that of healthy controls) was seen in the groups irradiated with a ctc of 400 µm.

  3. Quantitative profiling of brain lipid raft proteome in a mouse model of fragile X syndrome.

    Science.gov (United States)

    Kalinowska, Magdalena; Castillo, Catherine; Francesconi, Anna

    2015-01-01

    Fragile X Syndrome, a leading cause of inherited intellectual disability and autism, arises from transcriptional silencing of the FMR1 gene encoding an RNA-binding protein, Fragile X Mental Retardation Protein (FMRP). FMRP can regulate the expression of approximately 4% of brain transcripts through its role in regulation of mRNA transport, stability and translation, thus providing a molecular rationale for its potential pleiotropic effects on neuronal and brain circuitry function. Several intracellular signaling pathways are dysregulated in the absence of FMRP suggesting that cellular deficits may be broad and could result in homeostatic changes. Lipid rafts are specialized regions of the plasma membrane, enriched in cholesterol and glycosphingolipids, involved in regulation of intracellular signaling. Among transcripts targeted by FMRP, a subset encodes proteins involved in lipid biosynthesis and homeostasis, dysregulation of which could affect the integrity and function of lipid rafts. Using a quantitative mass spectrometry-based approach we analyzed the lipid raft proteome of Fmr1 knockout mice, an animal model of Fragile X syndrome, and identified candidate proteins that are differentially represented in Fmr1 knockout mice lipid rafts. Furthermore, network analysis of these candidate proteins reveals connectivity between them and predicts functional connectivity with genes encoding components of myelin sheath, axonal processes and growth cones. Our findings provide insight to aid identification of molecular and cellular dysfunctions arising from Fmr1 silencing and for uncovering shared pathologies between Fragile X syndrome and other autism spectrum disorders.

  4. A diagnosis model for early Tourette syndrome children based on brain structural network characteristics

    Science.gov (United States)

    Wen, Hongwei; Liu, Yue; Wang, Jieqiong; Zhang, Jishui; Peng, Yun; He, Huiguang

    2016-03-01

    Tourette syndrome (TS) is a childhood-onset neurobehavioral disorder characterized by the presence of multiple motor and vocal tics. Tic generation has been linked to disturbed networks of brain areas involved in planning, controlling and execution of action. The aim of our work is to select topological characteristics of structural network which were most efficient for estimating the classification models to identify early TS children. Here we employed the diffusion tensor imaging (DTI) and deterministic tractography to construct the structural networks of 44 TS children and 48 age and gender matched healthy children. We calculated four different connection matrices (fiber number, mean FA, averaged fiber length weighted and binary matrices) and then applied graph theoretical methods to extract the regional nodal characteristics of structural network. For each weighted or binary network, nodal degree, nodal efficiency and nodal betweenness were selected as features. Support Vector Machine Recursive Feature Extraction (SVM-RFE) algorithm was used to estimate the best feature subset for classification. The accuracy of 88.26% evaluated by a nested cross validation was achieved on combing best feature subset of each network characteristic. The identified discriminative brain nodes mostly located in the basal ganglia and frontal cortico-cortical networks involved in TS children which was associated with tic severity. Our study holds promise for early identification and predicting prognosis of TS children.

  5. A scalable multi-resolution spatio-temporal model for brain activation and connectivity in fMRI data.

    Science.gov (United States)

    Castruccio, Stefano; Ombao, Hernando; Genton, Marc G

    2018-01-22

    Functional Magnetic Resonance Imaging (fMRI) is a primary modality for studying brain activity. Modeling spatial dependence of imaging data at different spatial scales is one of the main challenges of contemporary neuroimaging, and it could allow for accurate testing for significance in neural activity. The high dimensionality of this type of data (on the order of hundreds of thousands of voxels) poses serious modeling challenges and considerable computational constraints. For the sake of feasibility, standard models typically reduce dimensionality by modeling covariance among regions of interest (ROIs)-coarser or larger spatial units-rather than among voxels. However, ignoring spatial dependence at different scales could drastically reduce our ability to detect activation patterns in the brain and hence produce misleading results. We introduce a multi-resolution spatio-temporal model and a computationally efficient methodology to estimate cognitive control related activation and whole-brain connectivity. The proposed model allows for testing voxel-specific activation while accounting for non-stationary local spatial dependence within anatomically defined ROIs, as well as regional dependence (between-ROIs). The model is used in a motor-task fMRI study to investigate brain activation and connectivity patterns aimed at identifying associations between these patterns and regaining motor functionality following a stroke. © 2018, The International Biometric Society.

  6. A scalable multi-resolution spatio-temporal model for brain activation and connectivity in fMRI data

    KAUST Repository

    Castruccio, Stefano

    2018-01-23

    Functional Magnetic Resonance Imaging (fMRI) is a primary modality for studying brain activity. Modeling spatial dependence of imaging data at different spatial scales is one of the main challenges of contemporary neuroimaging, and it could allow for accurate testing for significance in neural activity. The high dimensionality of this type of data (on the order of hundreds of thousands of voxels) poses serious modeling challenges and considerable computational constraints. For the sake of feasibility, standard models typically reduce dimensionality by modeling covariance among regions of interest (ROIs)—coarser or larger spatial units—rather than among voxels. However, ignoring spatial dependence at different scales could drastically reduce our ability to detect activation patterns in the brain and hence produce misleading results. We introduce a multi-resolution spatio-temporal model and a computationally efficient methodology to estimate cognitive control related activation and whole-brain connectivity. The proposed model allows for testing voxel-specific activation while accounting for non-stationary local spatial dependence within anatomically defined ROIs, as well as regional dependence (between-ROIs). The model is used in a motor-task fMRI study to investigate brain activation and connectivity patterns aimed at identifying associations between these patterns and regaining motor functionality following a stroke.

  7. Oxidative Stress and Protein Quality Control Systems in the Aged Canine Brain as a Model for Human Neurodegenerative Disorders

    Directory of Open Access Journals (Sweden)

    Mariarita Romanucci

    2015-01-01

    Full Text Available Aged dogs are considered the most suitable spontaneous animal model for studying normal aging and neurodegenerative diseases. Elderly canines naturally develop cognitive dysfunction and neuropathological hallmarks similar to those seen in humans, especially Alzheimer’s disease-like pathology. Pet dogs also share similar living conditions and diets to humans. Oxidative damage accumulates in the canine brain during aging, making dogs a valid model for translational antioxidant treatment/prevention studies. Evidence suggests the presence of detective protein quality control systems, involving ubiquitin-proteasome system (UPS and Heat Shock Proteins (HSPs, in the aged canine brain. Further studies on the canine model are needed to clarify the role of age-related changes in UPS activity and HSP expression in neurodegeneration in order to design novel treatment strategies, such as HSP-based therapies, aimed at improving chaperone defences against proteotoxic stress affecting brain during aging.

  8. Oxidative Stress and Protein Quality Control Systems in the Aged Canine Brain as a Model for Human Neurodegenerative Disorders.

    Science.gov (United States)

    Romanucci, Mariarita; Della Salda, Leonardo

    2015-01-01

    Aged dogs are considered the most suitable spontaneous animal model for studying normal aging and neurodegenerative diseases. Elderly canines naturally develop cognitive dysfunction and neuropathological hallmarks similar to those seen in humans, especially Alzheimer's disease-like pathology. Pet dogs also share similar living conditions and diets to humans. Oxidative damage accumulates in the canine brain during aging, making dogs a valid model for translational antioxidant treatment/prevention studies. Evidence suggests the presence of detective protein quality control systems, involving ubiquitin-proteasome system (UPS) and Heat Shock Proteins (HSPs), in the aged canine brain. Further studies on the canine model are needed to clarify the role of age-related changes in UPS activity and HSP expression in neurodegeneration in order to design novel treatment strategies, such as HSP-based therapies, aimed at improving chaperone defences against proteotoxic stress affecting brain during aging.

  9. Kalman estimator- and general linear model-based on-line brain activation mapping by near-infrared spectroscopy

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    Ge Shuzhi S

    2010-12-01

    Full Text Available Abstract Background Near-infrared spectroscopy (NIRS is a non-invasive neuroimaging technique that recently has been developed to measure the changes of cerebral blood oxygenation associated with brain activities. To date, for functional brain mapping applications, there is no standard on-line method for analysing NIRS data. Methods In this paper, a novel on-line NIRS data analysis framework taking advantages of both the general linear model (GLM and the Kalman estimator is devised. The Kalman estimator is used to update the GLM coefficients recursively, and one critical coefficient regarding brain activities is then passed to a t-statistical test. The t-statistical test result is used to update a topographic brain activation map. Meanwhile, a set of high-pass filters is plugged into the GLM to prevent very low-frequency noises, and an autoregressive (AR model is used to prevent the temporal correlation caused by physiological noises in NIRS time series. A set of data recorded in finger tapping experiments is studied using the proposed framework. Results The obtained results suggest that the method can effectively track the task related brain activation areas, and prevent the noise distortion in the estimation while the experiment is running. Thereby, the potential of the proposed method for real-time NIRS-based brain imaging was demonstrated. Conclusions This paper presents a novel on-line approach for analysing NIRS data for functional brain mapping applications. This approach demonstrates the potential of a real-time-updating topographic brain activation map.

  10. Establishment of 9L/F344 rat intracerebral glioma model of brain tumor stem cells

    Directory of Open Access Journals (Sweden)

    Zong-yu XIAO

    2015-04-01

    Full Text Available Objective To establish the 9L/F344 rat intracerebral glioma model of brain tumor stem cells.  Methods Rat 9L gliosarcoma stem-like cells were cultured in serum-free suspension. The expression of CD133 and nestin were tested by immunohistochemistry. A total of 48 inbredline male F344 rats were randomly divided into 2 groups, and 9L tumor sphere cells and 9L monolayer cells were respectively implanted into the right caudate nucleus of F344 rats in 2 groups. Survival time was observed and determined using the method of Kaplan-Meier survival analysis. Fourteen days after implantation or when the rats were dying, their brains were perfused and sectioned for HE staining, and CD133 and nestin were detected by immunohistochemistry.  Results Rat 9L tumor spheres were formed with suspension culture in serum-free medium. The gliomas formed in both groups were invasive without obvious capsule. More new vessels, bleeding and necrosis could be detected in 9L tumor spheres group. The tumor cells in both groups were positive for CD133 and nestin. There was no significant difference in the expression of CD133 and nestin between 2 groups (P > 0.05, for all. According to the expression of nestin, the tumors formed by 9L tumor sphere cells were more invasive. The median survival time of the rats bearing 9L tumor sphere cells was 15 d (95%CI: 15.219-15.781, and the median survival time of the rats bearing 9L monolayer cells was 21 d (95%CI: 20.395-21.605. There was significant difference between 2 groups (χ2 = 12.800, P = 0.000.  Conclusions 9L/F344 rat intracerebral glioma model of brain tumor stem cells is successfully established, which provides a glioma model for the future research. DOI: 10.3969/j.issn.1672-6731.2015.04.012

  11. Introducing the model of cognitive-communication competence: A model to guide evidence-based communication interventions after brain injury.

    Science.gov (United States)

    MacDonald, Sheila

    2017-01-01

    Communication impairments associated with acquired brain injury (ABI) are devastating in their impact on family, community, social, academic, and vocational participation. Despite international evidence-based guidelines for communication interventions, evidence practice gaps include under identification of communication deficits, infrequent referrals, and inadequate treatment to realize functional communication outcomes. Evidence-informed communication intervention requires synthesis of abundant interdisciplinary research. This study describes the development of the model of cognitive-communication competence, a new model that summarizes a complex array of influences on communication to provide a holistic view of communication competence after ABI. A knowledge synthesis approach was employed to integrate interdisciplinary evidence relevant to communication competence. Development of the model included review of the incidence of communication impairments, practice guidelines, and factors relevant to communication competence guided by three key questions. This was followed by expert consultation with researchers, clinicians, and individuals with ABI. The resulting model comprises 7 domains, 7 competencies, and 47 factors related to communication functioning and intervention. This model could bridge evidence to practice by promoting a comprehensive and consistent view of communication competence for evidence synthesis, clinical decision-making, outcome measurement, and interprofessional collaboration.

  12. Three-compartment modeling of C-11 N-Methyl spiperone kinetics in the human brain

    International Nuclear Information System (INIS)

    Brooks, R.A.; Wong, D.F.; Di Chiro, G.; Wayner, R.T.; Douglass, K.H.; Frost, J.J.; Larson, S.M.; Wagner, H.N. Jr.

    1984-01-01

    N-Methyl spiperone, as well as spiperone, has been used to study the dopamine receptor system in the brain. The authors have applied a 3-compartment model consisting of vascular, extravascular unbound, and receptor-bound activity to two normal volunteers and one patient with Parkinson's disease. The model differs from that proposed by another study, in that, as in the Sokoloff model for deoxyglucose, there is no explicit term for blood flow. Furthermore, the authors used a 3-compartment model for the cerebellum as well as the caudate/putamen. Serial scans were obtained by PET for up to 2 hrs after injection of the tracer. Time-activity curves were generated over the caudate, putamen and cerebellum. The results indicate a close fit of the observed data to the 3-compatment model. In the model, K1 represents the rate constant of delivery of the tracer in the tissue from the vascular compartment. K2 is the reverse rate constant. K1 was approximately equal to K2 for the cerebellum. In the basal ganglia, K2 was less than K1 due to nonspecific binding in compartment 2. K3 represents the rate constant of binding of the tracer to the receptor binding sites in the cerebral cortex and basal ganglia and to nonspecific binding sites in the cerebellum which contains essentially no dopamine receptors. K4 represents the rate constant for dissociation of the tracer from the receptors. For N-methyl spiperone K4 is very low in the caudate/putamen. The 3-compartment model seemed to fit the data better than the 2-compartment model for both the caudate/putamen and cerebellar activity

  13. Social Competence in Pediatric Brain Tumor Survivors: Application of a Model from Social Neuroscience and Developmental Psychology

    Science.gov (United States)

    Hocking, Matthew C.; McCurdy, Mark; Turner, Elise; Kazak, Anne E.; Noll, Robert B.; Phillips, Peter; Barakat, Lamia P.

    2014-01-01

    Pediatric brain tumor (BT) survivors are at risk for psychosocial late effects across many domains of functioning, including neurocognitive and social. The literature on the social competence of pediatric BT survivors is still developing and future research is needed that integrates developmental and cognitive neuroscience research methodologies to identify predictors of survivor social adjustment and interventions to ameliorate problems. This review discusses the current literature on survivor social functioning through a model of social competence in childhood brain disorder and suggests future directions based on this model. Interventions pursuing change in survivor social adjustment should consider targeting social ecological factors. PMID:25382825

  14. Social competence in pediatric brain tumor survivors: application of a model from social neuroscience and developmental psychology.

    Science.gov (United States)

    Hocking, Matthew C; McCurdy, Mark; Turner, Elise; Kazak, Anne E; Noll, Robert B; Phillips, Peter; Barakat, Lamia P

    2015-03-01

    Pediatric brain tumor (BT) survivors are at risk for psychosocial late effects across many domains of functioning, including neurocognitive and social. The literature on the social competence of pediatric BT survivors is still developing and future research is needed that integrates developmental and cognitive neuroscience research methodologies to identify predictors of survivor social adjustment and interventions to ameliorate problems. This review discusses the current literature on survivor social functioning through a model of social competence in childhood brain disorder and suggests future directions based on this model. Interventions pursuing change in survivor social adjustment should consider targeting social ecological factors. © 2014 Wiley Periodicals, Inc.

  15. Reward optimization in the primate brain: a probabilistic model of decision making under uncertainty.

    Directory of Open Access Journals (Sweden)

    Yanping Huang

    Full Text Available A key problem in neuroscience is understanding how the brain makes decisions under uncertainty. Important insights have been gained using tasks such as the random dots motion discrimination task in which the subject makes decisions based on noisy stimuli. A descriptive model known as the drift diffusion model has previously been used to explain psychometric and reaction time data from such tasks but to fully explain the data, one is forced to make ad-hoc assumptions such as a time-dependent collapsing decision boundary. We show that such assumptions are unnecessary when decision making is viewed within the framework of partially observable Markov decision processes (POMDPs. We propose an alternative model for decision making based on POMDPs. We show that the motion discrimination task reduces to the problems of (1 computing beliefs (posterior distributions over the unknown direction and motion strength from noisy observations in a bayesian manner, and (2 selecting actions based on these beliefs to maximize the expected sum of future rewards. The resulting optimal policy (belief-to-action mapping is shown to be equivalent to a collapsing decision threshold that governs the switch from evidence accumulation to a discrimination decision. We show that the model accounts for both accuracy and reaction time as a function of stimulus strength as well as different speed-accuracy conditions in the random dots task.

  16. Reward optimization in the primate brain: a probabilistic model of decision making under uncertainty.

    Science.gov (United States)

    Huang, Yanping; Rao, Rajesh P N

    2013-01-01

    A key problem in neuroscience is understanding how the brain makes decisions under uncertainty. Important insights have been gained using tasks such as the random dots motion discrimination task in which the subject makes decisions based on noisy stimuli. A descriptive model known as the drift diffusion model has previously been used to explain psychometric and reaction time data from such tasks but to fully explain the data, one is forced to make ad-hoc assumptions such as a time-dependent collapsing decision boundary. We show that such assumptions are unnecessary when decision making is viewed within the framework of partially observable Markov decision processes (POMDPs). We propose an alternative model for decision making based on POMDPs. We show that the motion discrimination task reduces to the problems of (1) computing beliefs (posterior distributions) over the unknown direction and motion strength from noisy observations in a bayesian manner, and (2) selecting actions based on these beliefs to maximize the expected sum of future rewards. The resulting optimal policy (belief-to-action mapping) is shown to be equivalent to a collapsing decision threshold that governs the switch from evidence accumulation to a discrimination decision. We show that the model accounts for both accuracy and reaction time as a function of stimulus strength as well as different speed-accuracy conditions in the random dots task.

  17. The Partisan Brain: An Identity-Based Model of Political Belief.

    Science.gov (United States)

    Van Bavel, Jay J; Pereira, Andrea

    2018-03-01

    Democracies assume accurate knowledge by the populace, but the human attraction to fake and untrustworthy news poses a serious problem for healthy democratic functioning. We articulate why and how identification with political parties - known as partisanship - can bias information processing in the human brain. There is extensive evidence that people engage in motivated political reasoning, but recent research suggests that partisanship can alter memory, implicit evaluation, and even perceptual judgments. We propose an identity-based model of belief for understanding the influence of partisanship on these cognitive processes. This framework helps to explain why people place party loyalty over policy, and even over truth. Finally, we discuss strategies for de-biasing information processing to help to create a shared reality across partisan divides. Copyright © 2018 Elsevier Ltd. All rights reserved.

  18. Locus coeruleus: A brain region exhibiting neuronal alterations in Parkinson’s disease rat model

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    Samah M. Fathy

    2015-05-01

    Full Text Available Toxic insults lead to increased α-synuclein expression in dopaminergic neurons. However, little information is known about α-synuclein alterations in relation to tyrosine hydroxylase (TH changes in locus coeruleus (LC of 1-methyl-4-phenyl-1,2,3,6-tetrahydropyridine (MPTP rat model for Parkinson’s disease (PD. Four injections (15 mg/kg each of the neurotoxicant MPTP to rats led to an upregulation of α-synuclein level and increased immunoreactivity with aggregated protein in the MPTP-treated group as revealed by Western blotting and immunohistochemical techniques. Meanwhile, MPTP reduced the level of and caused immunoreactivity toward TH antibody in LC and adjoining noradrenergic neurons. These data indicate that MPTP can induce α-synuclein alterations in other brain regions that have been implicated in the pathogenesis of PD. The findings are also consistent with a pattern that α-synuclein modification influences the TH level.

  19. Bicuculline methiodide in the blood-brain barrier-epileptogen model of epilepsy

    Energy Technology Data Exchange (ETDEWEB)

    Remler, M.P.; Marcussen, W.H.

    Focal epilepsy can be produced by a blood-brain barrier (BBB)-excluded systemic convulsant (penicillin, folic acid, etc.) in the presence of a focal BBB lesion. Bicuculline methiodide, a gamma-aminobutyric acid blocking epileptogen, crosses the normal BBB of rats poorly and produces no consistent abnormality behaviorally or on EEG at 36 mg/kg. When the BBB is opened in 0.25 ml of cortex by 6,000 rad of alpha particles, by a pin trauma lesion, or by a heat lesion, the rats are normal clinically and on EEG. When these lesioned rats are challenged with bicuculline methiodide, 36 mg/kg, an intense, highly localized epileptiform discharge results that begins approximately 20 min after injection and lasts 30-90 min. The plausibility and experimental utility of the BBB-epileptogen model of epilepsy are enhanced by these observations.

  20. Brain Emotion Systems, Personality, Hopelessness, Self/Other Perception, and Gambling Cognition: A Structural Equation Model.

    Science.gov (United States)

    Iliceto, Paolo; D'Antuono, Laura; Bowden-Jones, Henrietta; Giovani, Eleni; Giacolini, Teodosio; Candilera, Gabriella; Sabatello, Ugo; Panksepp, Jaak

    2016-03-01

    The aim of this study was to explore the relations between gambling, brain emotion systems, personality, self/other perception, and hopelessness in an Italian community. Dimensions of gambling, positive and negative emotions, self/other perception, personality and hopelessness were assessed in a community sample of 235 adults aged 19-59 years. Two structural models were tested. We found a significant correlation between problem gambling and impulsivity, which in association with aggressivity and negative personality dimensions may help explain the psychopathology factor, i.e. a latent variable involving neurotic personality, hopelessness, high sensation seeking, low metacognitive responsiveness, and disorganized patterns of interpersonal relationships. These results contribute to develop a theoretical framework of gambling in relation with personality factors and provide a new approach for clinical intervention of problem gambling that relies on a solid multidimensional perspective.

  1. Expression and roles of aquaporin 1 in hippocampus of mice model with traumatic brain injury

    Directory of Open Access Journals (Sweden)

    Bo QIU

    2014-03-01

    Full Text Available Background The "secondary brain insult" including ischemia, hypoxia and edema after primary traumatic brain injury (TBI may deteriorate the brain damages and greatly influence the prognosis. As a selective vulnerable region, the hippocampus is especially sensitive to ischemia, hypoxia or edema and yields irreversible sequelae. Aquaporin 1 (AQP1 has been reported to be related to cerebral edema, but the expression and role of AQP1 in hippocampal edema after TBI have seldomly been investigated. In this study, we established BALB/c mouse closed craniocerebral injury models and investigated the changes of AQP1 expression in hippocampus of mouse models after TBI, thereby discussing its effects on relevant pathophysiological processes.  Methods Seventy-five BALB/c mice were used to establish experimental closed TBI models with a free-falling weight drop device, and the equal numbers of mice were subject to sham operation and categorized as sham group. The neurological function of each mouse in either TBI group or sham group was scored at different time points (1, 6, 24 and 72 h after TBI or sham operation, and brain edema formation of the mice in both groups was also evaluated accordingly at 6, 24 and 72 h. The apoptotic hippocampal cells were stained in situ and detected using TdT-mediated dUTP-biotin nick end labeling (TUNEL method at different time points (6, 24 and 72 h, then AQP1 expression in hippocampus was also correspondingly detected using immunohistochemistry and Western blotting. All the data were finally compared with those in sham operation group and analyzed.  Results Experimental TBI models were successfully established and confirmed by the neurological function score and hippocampal edema evaluation. Six hours after craniocerebral injury, the apoptotic cells increased significantly in the hippocampus of mice in TBI group compared with those in sham group [(44.26 ± 15.18% vs (8.61 ± 8.25% , t = - 9.676, P = 0.002]. The apoptotic

  2. Fish oil improves motor function, limits blood-brain barrier disruption, and reduces Mmp9 gene expression in a rat model of juvenile traumatic brain injury.

    Science.gov (United States)

    Russell, K L; Berman, N E J; Gregg, P R A; Levant, B

    2014-01-01

    The effects of an oral fish oil treatment regimen on sensorimotor, blood-brain barrier, and biochemical outcomes of traumatic brain injury (TBI) were investigated in a juvenile rat model. Seventeen-day old Long-Evans rats were given a 15mL/kg fish oil (2.01g/kg EPA, 1.34g/kg DHA) or soybean oil dose via oral gavage 30min prior to being subjected to a controlled cortical impact injury or sham surgery, followed by daily doses for seven days. Fish oil treatment resulted in less severe hindlimb deficits after TBI as assessed with the beam walk test, decreased cerebral IgG infiltration, and decreased TBI-induced expression of the Mmp9 gene one day after injury. These results indicate that fish oil improved functional outcome after TBI resulting, at least in part from decreased disruption of the blood-brain barrier through a mechanism that includes attenuation of TBI-induced expression of Mmp9. © 2013 Elsevier Ltd. All rights reserved.

  3. The "proactive" model of learning: Integrative framework for model-free and model-based reinforcement learning utilizing the associative learning-based proactive brain concept.

    Science.gov (United States)

    Zsuga, Judit; Biro, Klara; Papp, Csaba; Tajti, Gabor; Gesztelyi, Rudolf

    2016-02-01

    Reinforcement learning (RL) is a powerful concept underlying forms of associative learning governed by the use of a scalar reward signal, with learning taking place if expectations are violated. RL may be assessed using model-based and model-free approaches. Model-based reinforcement learning involves the amygdala, the hippocampus, and the orbitofrontal cortex (OFC). The model-free system involves the pedunculopontine-tegmental nucleus (PPTgN), the ventral tegmental area (VTA) and the ventral striatum (VS). Based on the functional connectivity of VS, model-free and model based RL systems center on the VS that by integrating model-free signals (received as reward prediction error) and model-based reward related input computes value. Using the concept of reinforcement learning agent we propose that the VS serves as the value function component of the RL agent. Regarding the model utilized for model-based computations we turned to the proactive brain concept, which offers an ubiquitous function for the default network based on its great functional overlap with contextual associative areas. Hence, by means of the default network the brain continuously organizes its environment into context frames enabling the formulation of analogy-based association that are turned into predictions of what to expect. The OFC integrates reward-related information into context frames upon computing reward expectation by compiling stimulus-reward and context-reward information offered by the amygdala and hippocampus, respectively. Furthermore we suggest that the integration of model-based expectations regarding reward into the value signal is further supported by the efferent of the OFC that reach structures canonical for model-free learning (e.g., the PPTgN, VTA, and VS). (c) 2016 APA, all rights reserved).

  4. Late radiation damage in bone, bone marrow and brain vasculature, with particular emphasis upon fractionation models

    International Nuclear Information System (INIS)

    Pitkaenen, Maunu.

    1986-04-01

    X-ray induced changes in rat and human bone and bone marrow vasculature and in rat brain vasculature were measured as a function of time after irradiation and absorbed dose. The absorbed dose in the organ varied from 5 to 25 Gy for single dose irradiations and from 19 to 58 Gy for fractionated irradiations.The number of fractions varied from 3 to 10 for the rats and from 12 to 25 for the human. Blood flow changes were measured using an ''1''2''5I antipyrine or ''8''6RbCl extraction technique. The red blood cell (RBC) volume was examined by ''5''1Cr labelled red cells. Different fractionation models have been compared. Radiation induced reduction of bone and bone marrow blood flow were both time and dose dependent. Reduced blood flow 3 months after irradiation would seem to be an important factor in the subsequent atrophy of bones. With a single dose of 10 Gy the bone marrow blood flow returned to the control level by 7 months after irradiation. In the irradiated bone the RBC volume was about same as that in the control side but in bone marrow the reduction was from 32 to 59%. The dose levels predicted by the nominal standard dose (NSD) formula produced about the same damage to the rat femur seven months after irradiation when the extraction of ''8''6Rb chloride and the dry weight were concerned as the end points. However, the results suggest that the NSB formula underestimates the late radiation damage in bone marrow when a small number of large fractions are used. In the irradiated brains of the rats the blood flow was on average 20.4% higher compared to that in the control group. There was no significant difference in brain blood flow between different fractionation schemes. The value of 0.42 for the exponent of N corresponds to the average value for central nervous system tolerance in the literature. The model used may be sufficiently accurate for clinical work provided the treatment schemes used do not depart too radically from standard practice

  5. Vitamin E Supplementation Reduces Cellular Loss in the Brain of a Premature Aging Mouse Model.

    Science.gov (United States)

    La Fata, G; van Vliet, N; Barnhoorn, S; Brandt, R M C; Etheve, S; Chenal, E; Grunenwald, C; Seifert, N; Weber, P; Hoeijmakers, J H J; Mohajeri, M H; Vermeij, W P

    2017-01-01

    Aging is a highly complex biological process driven by multiple factors. Its progression can partially be influenced by nutritional interventions. Vitamin E is a lipid-soluble anti-oxidant that is investigated as nutritional supplement for its ability to prevent or delay the onset of specific aging pathologies, including neurodegenerative disorders. We aimed here to investigate the effect of vitamin E during aging progression in a well characterized mouse model for premature aging. Xpg-/- animals received diets with low (~2.5 mg/kg feed), medium (75 mg/kg feed) or high (375 mg/kg feed) vitamin E concentration and their phenotype was monitored during aging progression. Vitamin E content was analyzed in the feed, for stability reasons, and in mouse plasma, brain, and liver, for effectiveness of the treatment. Subsequent age-related changes were monitored for improvement by increased vitamin E or worsening by depletion in both liver and nervous system, organs sensitive to oxidative stress. Mice supplemented with high levels of vitamin E showed a delayed onset of age-related body weight decline and appearance of tremors when compared to mice with a low dietary vitamin E intake. DNA damage resulting in liver abnormalities such as changes in polyploidy, was considerably prevented by elevated amounts of vitamin E. Additionally, immunohistochemical analyses revealed that high intake of vitamin E, when compared with low and medium levels of vitamin E in the diet, reduces the number of p53-positive cells throughout the brain, indicative of a lower number of cells dying due to DNA damage accumulated over time. Our data underline a neuroprotective role of vitamin E in the premature aging animal model used in this study, likely via a reduction of oxidative stress, and implies the importance of improved nutrition to sustain health.

  6. Cognitive and behavioral evaluation of nutritional interventions in rodent models of brain aging and dementia

    Directory of Open Access Journals (Sweden)

    Wahl D

    2017-09-01

    Full Text Available Devin Wahl,1,2 Sean CP Coogan,1,3 Samantha M Solon-Biet,1,2 Rafael de Cabo,4 James B Haran,5 David Raubenheimer,1,6,7 Victoria C Cogger,1,2 Mark P Mattson,8 Stephen J Simpson,1,2,7 David G Le Couteur1,2 1Charles Perkins Centre, University of Sydney, Sydney, 2Aging and Alzheimers Institute, ANZAC Research Institute, Concord Clinical School/Sydney Medical School, Concord, NSW, Australia; 3Department of Renewable Resources, University of Alberta, Edmonton, AB, Canada; 4Translational Gerontology Branch, National Institute on Aging, National Institutes of Health, Baltimore, MD, USA; 5Philadelphia College of Osteopathic Medicine, Philadelphia, PA, USA; 6Faculty of Veterinary Science, 7School of Life and Environmental Sciences, University of Sydney, Sydney, NSW, Australia; 8Laboratory of Neurosciences, National Institute on Aging’s Intramural Research Program, National Institutes of Health, Baltimore, MD, USA Abstract: Evaluation of behavior and cognition in rodent models underpins mechanistic and interventional studies of brain aging and neurodegenerative diseases, especially ­dementia. Commonly used tests include Morris water maze, Barnes maze, object recognition, fear ­conditioning, radial arm water maze, and Y maze. Each of these tests reflects some aspects of human memory including episodic memory, recognition memory, semantic memory, spatial memory, and emotional memory. Although most interventional studies in rodent models of dementia have focused on pharmacological agents, there are an increasing number of studies that have evaluated nutritional interventions including caloric restriction, intermittent fasting, and manipulation of macronutrients. Dietary interventions have been shown to influence ­various cognitive and behavioral tests in rodents indicating that nutrition can influence brain aging and possibly neurodegeneration. Keywords: calorie restriction, intermittent fasting, aging, memory, macronutrients

  7. Functional Brain Imaging Synthesis Based on Image Decomposition and Kernel Modeling: Application to Neurodegenerative Diseases

    Science.gov (United States)

    Martinez-Murcia, Francisco J.; Górriz, Juan M.; Ramírez, Javier; Illán, Ignacio A.; Segovia, Fermín; Castillo-Barnes, Diego; Salas-Gonzalez, Diego

    2017-01-01

    The rise of neuroimaging in research and clinical practice, together with the development of new machine learning techniques has strongly encouraged the Computer Aided Diagnosis (CAD) of different diseases and disorders. However, these algorithms are often tested in proprietary datasets to which the access is limited and, therefore, a direct comparison between CAD procedures is not possible. Furthermore, the sample size is often small for developing accurate machine learning methods. Multi-center initiatives are currently a very useful, although limited, tool in the recruitment of large populations and standardization of CAD evaluation. Conversely, we propose a brain image synthesis procedure intended to generate a new image set that share characteristics with an original one. Our system focuses on nuclear imaging modalities such as PET or SPECT brain images. We analyze the dataset by applying PCA to the original dataset, and then model the distribution of samples in the projected eigenbrain space using a Probability Density Function (PDF) estimator. Once the model has been built, we can generate new coordinates on the eigenbrain space belonging to the same class, which can be then projected back to the image space. The system has been evaluated on different functional neuroimaging datasets assessing the: resemblance of the synthetic images with the original ones, the differences between them, their generalization ability and the independence of the synthetic dataset with respect to the original. The synthetic images maintain the differences between groups found at the original dataset, with no significant differences when comparing them to real-world samples. Furthermore, they featured a similar performance and generalization capability to that of the original dataset. These results prove that these images are suitable for standardizing the evaluation of CAD pipelines, and providing data augmentation in machine learning systems -e.g. in deep learning-, or even to

  8. Functional Brain Imaging Synthesis Based on Image Decomposition and Kernel Modeling: Application to Neurodegenerative Diseases

    Directory of Open Access Journals (Sweden)

    Francisco J. Martinez-Murcia

    2017-11-01

    Full Text Available The rise of neuroimaging in research and clinical practice, together with the development of new machine learning techniques has strongly encouraged the Computer Aided Diagnosis (CAD of different diseases and disorders. However, these algorithms are often tested in proprietary datasets to which the access is limited and, therefore, a direct comparison between CAD procedures is not possible. Furthermore, the sample size is often small for developing accurate machine learning methods. Multi-center initiatives are currently a very useful, although limited, tool in the recruitment of large populations and standardization of CAD evaluation. Conversely, we propose a brain image synthesis procedure intended to generate a new image set that share characteristics with an original one. Our system focuses on nuclear imaging modalities such as PET or SPECT brain images. We analyze the dataset by applying PCA to the original dataset, and then model the distribution of samples in the projected eigenbrain space using a Probability Density Function (PDF estimator. Once the model has been built, we can generate new coordinates on the eigenbrain space belonging to the same class, which can be then projected back to the image space. The system has been evaluated on different functional neuroimaging datasets assessing the: resemblance of the synthetic images with the original ones, the differences between them, their generalization ability and the independence of the synthetic dataset with respect to the original. The synthetic images maintain the differences between groups found at the original dataset, with no significant differences when comparing them to real-world samples. Furthermore, they featured a similar performance and generalization capability to that of the original dataset. These results prove that these images are suitable for standardizing the evaluation of CAD pipelines, and providing data augmentation in machine learning systems -e.g. in deep

  9. WASICA: An effective wavelet-shrinkage based ICA model for brain fMRI data analysis.

    Science.gov (United States)

    Wang, Nizhuan; Zeng, Weiming; Shi, Yingchao; Ren, Tianlong; Jing, Yanshan; Yin, Jun; Yang, Jiajun

    2015-05-15

    Researches declared that the super-Gaussian property contributed to the success of some spatial independent component analysis (ICA) algorithms in brain fMRI source separation (e.g., Infomax and FastICA), which implied that sparse approximation transforming the sources (super-Gaussian or Gaussian-like) with stronger super-Gaussian feature would possibly improve the separation performance of these algorithms. This paper presented a novel wavelet-shrinkage based ICA (WASICA) model, an extension of our previous SACICA, for single-subject analysis. In contrast, two main aspects had been effectively enhanced: (1) sparse approximation coefficients set formation, made up of two sub-procedures: the wavelet-shrinkage of wavelet packet (WP) tree nodes, and the automatic nodes selection and integration based on the relative WP energy; (2) ICA-based decomposition and reconstruction, composed of temporal dynamics extraction using ICA, WP reconstruction based on the sparse approximation coefficients set and least-square-based functional networks reconstruction. The wavelet-shrinkage and the automatic nodes selection and integration simultaneously transformed both the mixtures and underlying sources into effective sparse approximation coefficients sets, exhibiting stronger super-Gaussian distribution; WP projected-back approximation with nuisance-exclusion contributed to networks reconstruction. Simulation 1 revealed WASICA successfully recovered super-Gaussian and some Gaussian-like sources. Simulation 2 and hybrid data experiments showed that WASICA with good temporal performance had stronger source recovery ability and signal detection sensitivity spatially than FastICA, Infomax and SACICA did; the higher intra-consistency in task-related experiments denoted WASICA occupied stronger spatial robustness against smooth kernels. WASICA was a promising brain signal separation model with charming spatial-temporal performance. Copyright © 2015 Elsevier B.V. All rights reserved.

  10. Designing Closed-Loop Brain-Machine Interfaces Using Model Predictive Control

    Directory of Open Access Journals (Sweden)

    Gautam Kumar

    2016-06-01

    Full Text Available Brain-machine interfaces (BMIs are broadly defined as systems that establish direct communications between living brain tissue and external devices, such as artificial arms. By sensing and interpreting neuronal activities to actuate an external device, BMI-based neuroprostheses hold great promise in rehabilitating motor disabled subjects, such as amputees. In this paper, we develop a control-theoretic analysis of a BMI-based neuroprosthetic system for voluntary single joint reaching task in the absence of visual feedback. Using synthetic data obtained through the simulation of an experimentally validated psycho-physiological cortical circuit model, both the Wiener filter and the Kalman filter based linear decoders are developed. We analyze the performance of both decoders in the presence and in the absence of natural proprioceptive feedback information. By performing simulations, we show that the performance of both decoders degrades significantly in the absence of the natural proprioception. To recover the performance of these decoders, we propose two problems, namely tracking the desired position trajectory and tracking the firing rate trajectory of neurons which encode the proprioception, in the model predictive control framework to design optimal artificial sensory feedback. Our results indicate that while the position trajectory based design can only recover the position and velocity trajectories, the firing rate trajectory based design can recover the performance of the motor task along with the recovery of firing rates in other cortical regions. Finally, we extend our design by incorporating a network of spiking neurons and designing artificial sensory feedback in the form of a charged balanced biphasic stimulating current.

  11. Comparison of BrainTool to other UML modeling and model transformation tools

    Science.gov (United States)

    Nikiforova, Oksana; Gusarovs, Konstantins

    2017-07-01

    In the last 30 years there were numerous model generated software systems offered targeting problems with the development productivity and the resulting software quality. CASE tools developed due today's date are being advertised as having "complete code-generation capabilities". Nowadays the Object Management Group (OMG) is calling similar arguments in regards to the Unified Modeling Language (UML) models at different levels of abstraction. It is being said that software development automation using CASE tools enables significant level of automation. Actual today's CASE tools are usually offering a combination of several features starting with a model editor and a model repository for a traditional ones and ending with code generator (that could be using a scripting or domain-specific (DSL) language), transformation tool to produce the new artifacts from the manually created and transformation definition editor to define new transformations for the most advanced ones. Present paper contains the results of CASE tool (mainly UML editors) comparison against the level of the automation they are offering.

  12. Individualized model predicts brain current flow during transcranial direct-current stimulation treatment in responsive stroke patient.

    Science.gov (United States)

    Datta, Abhishek; Baker, Julie M; Bikson, Marom; Fridriksson, Julius

    2011-07-01

    Although numerous published reports have demonstrated the beneficial effects of transcranial direct-current stimulation (tDCS) on task performance, fundamental questions remain regarding the optimal electrode configuration on the scalp. Moreover, it is expected that lesioned brain tissue will influence current flow and should therefore be considered (and perhaps leveraged) in the design of individualized tDCS therapies for stroke. The current report demonstrates how different electrode configurations influence the flow of electrical current through brain tissue in a patient who responded positively to a tDCS treatment targeting aphasia. The patient, a 60-year-old man, sustained a left hemisphere ischemic stroke (lesion size = 87.42 mL) 64 months before his participation. In this study, we present results from the first high-resolution (1 mm(3)) model of tDCS in a brain with considerable stroke-related damage; the model was individualized for the patient who received anodal tDCS to his left frontal cortex with the reference cathode electrode placed on his right shoulder. We modeled the resulting brain current flow and also considered three additional reference electrode positions: right mastoid, right orbitofrontal cortex, and a "mirror" configuration with the anode over the undamaged right cortex. Our results demonstrate the profound effect of lesioned tissue on resulting current flow and the ability to modulate current pattern through the brain, including perilesional regions, through electrode montage design. The complexity of brain current flow modulation by detailed normal and pathologic anatomy suggest: (1) That computational models are critical for the rational interpretation and design of individualized tDCS stroke-therapy; and (2) These models must accurately reproduce head anatomy as shown here. Copyright © 2011 Elsevier Inc. All rights reserved.

  13. Neuroprotective effect of hyperbaric oxygen therapy in a juvenile rat model of repetitive mild traumatic brain injury

    Directory of Open Access Journals (Sweden)

    Lei Huang

    2016-01-01

    Full Text Available Repetitive mild traumatic brain injury (rmTBI is an important medical concern for adolescent athletes that can lead to long-term disabilities. Multiple mild injuries may exacerbate tissue damage resulting in cumulative brain injury and poor functional recovery. In the present study, we investigated the increased brain vulnerability to rmTBI and the effect of hyperbaric oxygen treatment using a juvenile rat model of rmTBI. Two episodes of mild cortical controlled impact (3 days apart were induced in juvenile rats. Hyperbaric oxygen (HBO was applied 1 hour/day × 3 days at 2 atmosphere absolute consecutively, starting at 1 day after initial mild traumatic brain injury (mTBI. Neuropathology was assessed by multi-modal magnetic resonance imaging (MRI and tissue immunohistochemistry. After repetitive mTBI, there were increases in T2-weighted imaging-defined cortical lesions and susceptibility weighted imaging-defined cortical microhemorrhages, correlated with brain tissue gliosis at the site of impact. HBO treatment significantly decreased the MRI-identified abnormalities and tissue histopathology. Our findings suggest that HBO treatment improves the cumulative tissue damage in juvenile brain following rmTBI. Such therapy regimens could be considered in adolescent athletes at the risk of repeated concussions exposures.

  14. Association between resting-state brain network topological organization and creative ability: Evidence from a multiple linear regression model.

    Science.gov (United States)

    Jiao, Bingqing; Zhang, Delong; Liang, Aiying; Liang, Bishan; Wang, Zengjian; Li, Junchao; Cai, Yuxuan; Gao, Mengxia; Gao, Zhenni; Chang, Song; Huang, Ruiwang; Liu, Ming

    2017-10-01

    Previous studies have indicated a tight linkage between resting-state functional connectivity of the human brain and creative ability. This study aimed to further investigate the association between the topological organization of resting-state brain networks and creativity. Therefore, we acquired resting-state fMRI data from 22 high-creativity participants and 22 low-creativity participants (as determined by their Torrance Tests of Creative Thinking scores). We then constructed functional brain networks for each participant and assessed group differences in network topological properties before exploring the relationships between respective network topological properties and creative ability. We identified an optimized organization of intrinsic brain networks in both groups. However, compared with low-creativity participants, high-creativity participants exhibited increased global efficiency and substantially decreased path length, suggesting increased efficiency of information transmission across brain networks in creative individuals. Using a multiple linear regression model, we further demonstrated that regional functional integration properties (i.e., the betweenness centrality and global efficiency) of brain networks, particularly the default mode network (DMN) and sensorimotor network (SMN), significantly predicted the individual differences in creative ability. Furthermore, the associations between network regional properties and creative performance were creativity-level dependent, where the difference in the resource control component may be important in explaining individual difference in creative performance. These findings provide novel insights into the neural substrate of creativity and may facilitate objective identification of creative ability. Copyright © 2017 Elsevier B.V. All rights reserved.

  15. Neuroprotective effects of propofol, thiopental, etomidate, and midazolam in fetal rat brain in ischemia-reperfusion model.

    Science.gov (United States)

    Harman, Ferhat; Hasturk, Askin Esen; Yaman, Mehmet; Arca, Turkan; Kilinc, Kamer; Sargon, Mustafa Fevzi; Kaptanoglu, Erkan

    2012-07-01

    The aim of this study was to investigate the neuroprotective effects of propofol, thiopental, etomidate, and midazolam as anesthetic drugs in fetal rat brain in the ischemia-reperfusion (IR) model. Pregnant rats of day 19 were randomly allocated into eight groups. Fetal brain ischemia was induced by clamping the utero-ovarian artery bilaterally for 30 min and reperfusion was achieved by removing the clamps for 60 min. In the control group, fetal rat brains were obtained immediately after laparotomy. In the sham group, fetal rat brains were obtained 90 min after laparotomy. In the IR group, IR procedure was performed. No treatment was given in the IR group. One milliliter intralipid solution, 40 mg/kg propofol, 3 mg/kg thiopental, 0.1 mg/kg etomidate, and 3 mg/kg midazolam was administered intraperitoneally in the vehicle group, propofol group, thiopental group, etomidate group, and midazolam group, respectively, 20 min before IR procedure. At the end of the reperfusion period, the whole brains of the fetal rats were removed for evaluation of thiobarbituric acid reactive substances and for examination by electron microscopy. According to lipid peroxidation data, all the anesthetic drugs provide neuroprotection; however, ultrastructural findings and mitochondrial scoring confirms that only propofol and midazolam provides a strong neuroprotective effect. Propofol and midazolam may be used to protect fetal brain in case of acute fetal distress and hypoxic injury as a first choice anesthetic drug in cesarean delivery.

  16. Robust Brain-Machine Interface Design Using Optimal Feedback Control Modeling and Adaptive Point Process Filtering.

    Science.gov (United States)

    Shanechi, Maryam M; Orsborn, Amy L; Carmena, Jose M

    2016-04-01

    Much progress has been made in brain-machine interfaces (BMI) using decoders such as Kalman filters and finding their parameters with closed-loop decoder adaptation (CLDA). However, current decoders do not model the spikes directly, and hence may limit the processing time-scale of BMI control and adaptation. Moreover, while specialized CLDA techniques for intention estimation and assisted training exist, a unified and systematic CLDA framework that generalizes across different setups is lacking. Here we develop a novel closed-loop BMI training architecture that allows for processing, control, and adaptation using spike events, enables robust control and extends to various tasks. Moreover, we develop a unified control-theoretic CLDA framework within which intention estimation, assisted training, and adaptation are performed. The architecture incorporates an infinite-horizon optimal feedback-control (OFC) model of the brain's behavior in closed-loop BMI control, and a point process model of spikes. The OFC model infers the user's motor intention during CLDA-a process termed intention estimation. OFC is also used to design an autonomous and dynamic assisted training technique. The point process model allows for neural processing, control and decoder adaptation with every spike event and at a faster time-scale than current decoders; it also enables dynamic spike-event-based parameter adaptation unlike current CLDA methods that use batch-based adaptation on much slower adaptation time-scales. We conducted closed-loop experiments in a non-human primate over tens of days to dissociate the effects of these novel CLDA components. The OFC intention estimation improved BMI performance compared with current intention estimation techniques. OFC assisted training allowed the subject to consistently achieve proficient control. Spike-event-based adaptation resulted in faster and more consistent performance convergence compared with batch-based methods, and was robust to parameter

  17. Development of an in vitro blood-brain barrier model - cytotoxicity of mercury and aluminum

    International Nuclear Information System (INIS)

    Toimela, Tarja; Maeenpaeae, Hanna; Mannerstroem, Marika; Taehti, Hanna

    2004-01-01

    In this study, in vitro blood-brain barrier (BBB) models composed of two different cell types were compared. The aim of our study was to find an alternative human cell line that could be used in BBB models. Inorganic and organic mercury and aluminum were studied as model chemicals in the testing of the system. BBB models were composed of endothelial RBE4 cell line or retinal pigment epithelial (RPE) cell line ARPE-19 and neuronal SH-SY5Y cells as target cells. Glial U-373 MG cells were included in part of the tests to induce the formation of a tighter barrier. Millicell CM filter inserts were coated with rat-tail collagen, and RBE4 or ARPE-19 cells were placed on the filters at the density of 3.5-4 x 10 5 cells/filter. During culture, the state of confluency was microscopically observed and confirmed by the measurement of electrical resistance caused by the developing cell layer. The target cells, SH-SY5Y neuroblastoma cells, were plated on the bottom of cell culture wells at the density of 100 000 cells/cm 2 . In part of the studies, glial U-373 MG cells were placed on the under side of the membrane filter. When confluent filters with ARPE-19 or RBE4 cells were placed on top of the SH-SY5Y cells, different concentrations of mercuric chloride, methyl mercury chloride, and aluminum chloride were added into the filter cups along with a fluorescent tracer. Exposure time was 24 h, after which the cytotoxicity in the SH-SY5Y cell layer, as well as in the ARPE-19 or RBE4 cell layer, was evaluated by the luminescent measurement of total ATP. The leakage of the fluorescent tracer was also monitored. The results showed that both barrier cell types were induced by glial cells. Inorganic and organic mercury caused a leakage of the dye and cytotoxicity in SH-SY5Y cells. Especially, methyl mercury chloride could exert an effect on target cells before any profound cytotoxicity in barrier cells could be seen. Aluminum did not cause any leakage in the barrier cell layer, and even

  18. A retinoic acid-enhanced, multicellular human blood-brain barrier model derived from stem cell sources

    Science.gov (United States)

    Lippmann, Ethan S.; Al-Ahmad, Abraham; Azarin, Samira M.; Palecek, Sean P.; Shusta, Eric V.

    2014-02-01

    Blood-brain barrier (BBB) models are often used to investigate BBB function and screen brain-penetrating therapeutics, but it has been difficult to construct a human model that possesses an optimal BBB phenotype and is readily scalable. To address this challenge, we developed a human in vitro BBB model comprising brain microvascular endothelial cells (BMECs), pericytes, astrocytes and neurons derived from renewable cell sources. First, retinoic acid (RA) was used to substantially enhance BBB phenotypes in human pluripotent stem cell (hPSC)-derived BMECs, particularly through adherens junction, tight junction, and multidrug resistance protein regulation. RA-treated hPSC-derived BMECs were subsequently co-cultured with primary human brain pericytes and human astrocytes and neurons derived from human neural progenitor cells (NPCs) to yield a fully human BBB model that possessed significant tightness as measured by transendothelial electrical resistance (~5,000 Ωxcm2). Overall, this scalable human BBB model may enable a wide range of neuroscience studies.

  19. Local infusion of Staphylococcus aureus into the porcine internal carotid artery as a model of sepsis-related brain abscesses - A pilot study

    DEFF Research Database (Denmark)

    Astrup, Lærke B.; Iburg, Tine M.; Agerholm, Jørgen S.

    2017-01-01

    Brain pathology is an important aspect of human sepsis but is difficult to study in human patients. Th erefore, animal models of sepsis-related brain pathology are needed. As pigs mirror multiple aspects of sepsis-related brain pathology in humans, this makes the pig a potentially suitable model....... Unfortunately, models of sepsis in pigs are difficult to manage due to the accompanying massive systemic inflammatory response. To overcome these difficulties we designed a model in pigs of brain bacteremia established by local brain infusion in order to evaluate if this approach could reduce the systemic...... responses but still reflect the brain pathology of sepsis in humans. As a pilot study to obtain basic knowledge, we evaluated two methods of local infusion: long term infusion (60 minutes) of Staphylococcus aureus suspended in saline and, short-term infusion (10 minutes) of S. aureus embedded in autologous...

  20. Steady-state brain glucose transport kinetics re-evaluated with a four-state conformational model

    Directory of Open Access Journals (Sweden)

    João M N Duarte

    2009-10-01

    Full Text Available Glucose supply from blood to brain occurs through facilitative transporter proteins. A near linear relation between brain and plasma glucose has been experimentally determined and described by a reversible model of enzyme kinetics. A conformational four-state exchange model accounting for trans-acceleration and asymmetry of the carrier was included in a recently developed multi-compartmental model of glucose transport. Based on this model, we demonstrate that brain glucose (Gbrain as function of plasma glucose (Gplasma can be described by a single analytical equation namely comprising three kinetic compartments: blood, endothelial cells and brain. Transport was described by four parameters: apparent half saturation constant Kt, apparent maximum rate constant Tmax, glucose consumption rate CMRglc, and the iso-inhibition constant Kii that suggests Gbrain as inhibitor of the isomerisation of the unloaded carrier. Previous published data, where Gbrain was quantified as a function of plasma glucose by either biochemical methods or NMR spectroscopy, were used to determine the aforementioned kinetic parameters. Glucose transport was characterized by Kt ranging from 1.5 to 3.5 mM, Tmax/CMRglc from 4.6 to 5.6, and Kii from 51 to 149 mM. It was noteworthy that Kt was on the order of a few mM, as previously determined from the reversible model. The conformational four-state exchange model of glucose transport into the brain includes both efflux and transport inhibition by Gbrain, predicting that Gbrain eventually approaches a maximum concentration. However, since Kii largely exceeds Gplasma, iso-inhibition is unlikely to be of substantial importance for plasma glucose below 25 mM. As a consequence, the reversible model can account for most experimental observations under euglycaemia and moderate cases of hypo- and hyperglycaemia.

  1. Electrospun gelatin biopapers as substrate for in vitro bilayer models of blood-brain barrier tissue.

    Science.gov (United States)

    Bischel, Lauren L; Coneski, Peter N; Lundin, Jeffrey G; Wu, Peter K; Giller, Carl B; Wynne, James; Ringeisen, Brad R; Pirlo, Russell K

    2016-04-01

    Gaining a greater understanding of the blood-brain barrier (BBB) is critical for improvement in drug delivery, understanding pathologies that compromise the BBB, and developing therapies to protect the BBB. In vitro human tissue models are valuable tools for studying these issues. The standard in vitro BBB models use commercially available cell culture inserts to generate bilayer co-cultures of astrocytes and endothelial cells (EC). Electrospinning can be used to produce customized cell culture substrates with optimized material composition and mechanical properties with advantages over off-the-shelf materials. Electrospun gelatin is an ideal cell culture substrate because it is a natural polymer that can aid cell attachment and be modified and degraded by cells. Here, we have developed a method to produce cell culture inserts with electrospun gelatin "biopaper" membranes. The electrospun fiber diameter and cross-linking method were optimized for the growth of primary human endothelial cell and primary human astrocyte bilayer co-cultures to model human BBB tissue. BBB co-cultures on biopaper were characterized via cell morphology, trans-endothelial electrical resistance (TEER), and permeability to FITC-labeled dextran and compared to BBB co-cultures on standard cell culture inserts. Over longer culture periods (up to 21 days), cultures on the optimized electrospun gelatin biopapers were found to have improved TEER, decreased permeability, and permitted a smaller separation between co-cultured cells when compared to standard PET inserts. © 2016 Wiley Periodicals, Inc.

  2. An Anatomically Constrained Model for Path Integration in the Bee Brain.

    Science.gov (United States)

    Stone, Thomas; Webb, Barbara; Adden, Andrea; Weddig, Nicolai Ben; Honkanen, Anna; Templin, Rachel; Wcislo, William; Scimeca, Luca; Warrant, Eric; Heinze, Stanley

    2017-10-23

    Path integration is a widespread navigational strategy in which directional changes and distance covered are continuously integrated on an outward journey, enabling a straight-line return to home. Bees use vision for this task-a celestial-cue-based visual compass and an optic-flow-based visual odometer-but the underlying neural integration mechanisms are unknown. Using intracellular electrophysiology, we show that polarized-light-based compass neurons and optic-flow-based speed-encoding neurons converge in the central complex of the bee brain, and through block-face electron microscopy, we identify potential integrator cells. Based on plausible output targets for these cells, we propose a complete circuit for path integration and steering in the central complex, with anatomically identified neurons suggested for each processing step. The resulting model circuit is thus fully constrained biologically and provides a functional interpretation for many previously unexplained architectural features of the central complex. Moreover, we show that the receptive fields of the newly discovered speed neurons can support path integration for the holonomic motion (i.e., a ground velocity that is not precisely aligned with body orientation) typical of bee flight, a feature not captured in any previously proposed model of path integration. In a broader context, the model circuit presented provides a general mechanism for producing steering signals by comparing current and desired headings-suggesting a more basic function for central complex connectivity, from which path integration may have evolved. Copyright © 2017 Elsevier Ltd. All rights reserved.

  3. Humanin prevents brain mitochondrial dysfunction in a cardiac ischaemia-reperfusion injury model.

    Science.gov (United States)

    Kumfu, Sirinart; Charununtakorn, Savitree T; Jaiwongkam, Thidarat; Chattipakorn, Nipon; Chattipakorn, Siriporn C

    2016-06-01

    What is the central question of this study? Myocardial ischaemia-reperfusion (I/R) injury causes interference in the systemic circulation and damages not only the heart but also several vital organs, including the brain. Recently, a novel peptide called humanin has been shown to exert potent neuroprotective effects. However, the effect of humanin on the brain during cardiac I/R injury has not yet been investigated. What is the main finding and its importance? The I/R injury caused blood-brain barrier breakdown, increased brain oxidative stress and resulted in mitochondrial dysfunction. Only the humanin treatment before ischaemia attenuated brain mitochondrial dysfunction, but it did not prevent blood-brain barrier breakdown or brain oxidative stress. Humanin treatment during ischaemia and in the reperfusion period provided no neuroprotection. These findings indicate that humanin exerted neuroprotection during cardiac I/R injury via improved brain mitochondrial function. Myocardial ischaemia-reperfusion (I/R) injury causes interference in the systemic circulation and damages not only the heart but also several vital organs, including the brain. Nevertheless, limited information is available regarding the effect of cardiac I/R injury on the brain, including blood-brain barrier (BBB) breakdown, brain oxidative stress and mitochondrial function. Recently, a novel peptide called humanin has been shown to exert potent neuroprotective effects. However, the effect of humanin on the brain during cardiac I/R injury has not yet been investigated. Forty-two male Wistar rats were divided into the following two groups: an I/R group, which was subjected to a 30 min left anterior descending coronary artery occlusion followed by 120 min reperfusion (I/R group; n = 36); and a sham group (n = 6). The I/R group was divided into six subgroups. Each subgroup was given either vehicle or humanin analogue (84 μg kg(-1) , i.v.) at three different time points, namely before

  4. The influence of surrogate blood vessels on the impact response of a physical model of the brain.

    Science.gov (United States)

    Parnaik, Yednesh; Beillas, Philippe; Demetropoulos, Constantine K; Hardy, Warren N; Yang, King H; King, Albert I

    2004-11-01

    Cerebral blood vessels are an integral part of the brain and may play a role in the response of the brain to impact. The purpose of this study was to quantify the effects of surrogate vessels on the deformation patterns of a physical model of the brain under various impact conditions. Silicone gel and tubing were used as surrogates for brain tissue and blood vessels, respectively. Two aluminum cylinders representing a coronal section of the brain were constructed. One cylinder was filled with silicone gel only, and the other was filled with silicone gel and silicone tubing arranged in the radial direction in the peripheral region. An array of markers was embedded in the gel in both cylinders to facilitate strain calculation via high-speed video analysis. Both cylinders were simultaneously subjected to a combination of linear and angular acceleration using a two-segment pendulum. Marker motion was tracked, and maximum shear strain (MSS) and maximum principal strain (MPS) were calculated using markers clustered in groups of three. Four test series were conducted. Peak angular acceleration varied from 2,600 to 26,000 rad/s2, and peak angular speed varied from 17 to 29 rad/s. For a given impact condition, the test-to-test variation of these values was less than 5.5%. For all clusters, the peak MSS and peak MPS for both physical models were less than 26% and 32%, respectively. For 90% of the cluster locations, the absolute value of the difference in peak MSS and peak MPS between the physical models was 4% and 6%, respectively. In the physical model with tubing, strain tended to decrease in the periphery (near to the tubing), while it tended to increase toward the center (away from the tubing). Strain amplitudes were found to be sensitive to the peak angular speeds. In general, this study suggests that the vasculature could influence the deformation response of the brain.

  5. Organotypic brain slice cultures of adult transgenic P301S mice--a model for tauopathy studies.

    Directory of Open Access Journals (Sweden)

    Agneta Mewes

    Full Text Available BACKGROUND: Organotypic brain slice cultures represent an excellent compromise between single cell cultures and complete animal studies, in this way replacing and reducing the number of animal experiments. Organotypic brain slices are widely applied to model neuronal development and regeneration as well as neuronal pathology concerning stroke, epilepsy and Alzheimer's disease (AD. AD is characterized by two protein alterations, namely tau hyperphosphorylation and excessive amyloid β deposition, both causing microglia and astrocyte activation. Deposits of hyperphosphorylated tau, called neurofibrillary tangles (NFTs, surrounded by activated glia are modeled in transgenic mice, e.g. the tauopathy model P301S. METHODOLOGY/PRINCIPAL FINDINGS: In this study we explore the benefits and limitations of organotypic brain slice cultures made of mature adult transgenic mice as a potential model system for the multifactorial phenotype of AD. First, neonatal (P1 and adult organotypic brain slice cultures from 7- to 10-month-old transgenic P301S mice have been compared with regard to vitality, which was monitored with the lactate dehydrogenase (LDH- and the MTT (3-(4,5-Dimethylthiazol-2-yl-2,5-diphenyltetrazolium bromide assays over 15 days. Neonatal slices displayed a constant high vitality level, while the vitality of adult slice cultures decreased significantly upon cultivation. Various preparation and cultivation conditions were tested to augment the vitality of adult slices and improvements were achieved with a reduced slice thickness, a mild hypothermic cultivation temperature and a cultivation CO(2 concentration of 5%. Furthermore, we present a substantial immunohistochemical characterization analyzing the morphology of neurons, astrocytes and microglia in comparison to neonatal tissue. CONCLUSION/SIGNIFICANCE: Until now only adolescent animals with a maximum age of two months have been used to prepare organotypic brain slices. The current study

  6. Merging Transport Data for Choroid Plexus with Blood-Brain Barrier to Model CNS Homeostasis and Disease More Effectively.

    Science.gov (United States)

    Johanson, Conrad; Johanson, Nancy

    2016-01-01

    Robust modeling of CNS transport integrates molecular fluxes at the microvascular blood-brain barrier and epithelial choroid plexus blood-cerebrospinal fluid (CSF) barrier. Normal activity of solute transporters, channels and aquaporins, in the cerebral endothelium and choroidal epithelium, sets the microenvironment composition for neurons and glia. Conversely, perturbed transport/permeability at the barrier interfaces causes interstitial fluid dyshomeostasis (e.g. edema) arising in neural disorders. Critically-important transependymal solute/water distribution between brain and CSF needs more attention. This treatise encourages procuring transport data simultaneously for blood-brain barrier, blood-CSF barrier and CSF. In situ perfusion and multicompartmental analyses (tracers, microdialysis) provide dynamic assessments of molecular transfer among various CNS regions. Diffusion, active transport and convection are distorted by disease- and age-associated alterations in barrier permeability and CSF turnover (sink action). Clinical complications result from suboptimal conveyance of micronutrients (folate), catabolites (β-amyloid) and therapeutic agents (antibiotics) within the CNS. Neurorestorative therapies for stroke, traumatic brain injury, multiple sclerosis and brain tumors are facilitated by insight on molecular and cellular trafficking through the choroid plexus-CSF nexus. Knowledge is needed about fluxes of growth factors, neurotrophins, hormones and leukocytes from ventricular CSF into the hippocampus, subventricular zone and hypothalamus. CSF and brain removal of potentially toxic catabolites and neuropeptides merits further investigation to manage the degeneration of Alzheimer's disease and normal pressure hydrocephalus. Novel therapies will rely on delineating peptide and drug distributions across the blood-brain barrier and choroid plexus-CSF, and how they modulate the intervening neural-glial networks and neurogenic sites. Multicompartmental transport

  7. Quantification of Brain Access of Exendin-4 in the C57BL Mouse Model by SPIM Fluorescence Imaging and the Allen Mouse Brain Reference Model

    DEFF Research Database (Denmark)

    Jensen, Casper Bo; Secher, Anna; Hecksher-Sørensen, Jacob

    2015-01-01

    With the recent advance in 3D microscopy such as Single Plane Illumination Microscopy (SPIM) it is possible to obtain high resolution image volumes of the entire mouse brain. These data can be used to study the access of several peptides such as the glucagon-like peptide-1 (GLP-1) analogue Exendi...

  8. Monte Carlo modeling and optimization of contrast-enhanced radiotherapy of brain tumors

    Energy Technology Data Exchange (ETDEWEB)

    Perez-Lopez, C E; Garnica-Garza, H M, E-mail: hgarnica@cinvestav.mx [Centro de Investigacion y de Estudios Avanzados del Instituto Politecnico Nacional Unidad Monterrey, Via del Conocimiento 201 Parque de Investigacion e Innovacion Tecnologica, Apodaca NL CP 66600 (Mexico)

    2011-07-07

    Contrast-enhanced radiotherapy involves the use of a kilovoltage x-ray beam to impart a tumoricidal dose to a target into which a radiological contrast agent has previously been loaded in order to increase the x-ray absorption efficiency. In this treatment modality the selection of the proper x-ray spectrum is important since at the energy range of interest the penetration ability of the x-ray beam is limited. For the treatment of brain tumors, the situation is further complicated by the presence of the skull, which also absorbs kilovoltage x-ray in a very efficient manner. In this work, using Monte Carlo simulation, a realistic patient model and the Cimmino algorithm, several irradiation techniques and x-ray spectra are evaluated for two possible clinical scenarios with respect to the location of the target, these being a tumor located at the center of the head and at a position close to the surface of the head. It will be shown that x-ray spectra, such as those produced by a conventional x-ray generator, are capable of producing absorbed dose distributions with excellent uniformity in the target as well as dose differential of at least 20% of the prescribed tumor dose between this and the surrounding brain tissue, when the tumor is located at the center of the head. However, for tumors with a lateral displacement from the center and close to the skull, while the absorbed dose distribution in the target is also quite uniform and the dose to the surrounding brain tissue is within an acceptable range, hot spots in the skull arise which are above what is considered a safe limit. A comparison with previously reported results using mono-energetic x-ray beams such as those produced by a radiation synchrotron is also presented and it is shown that the absorbed dose distributions rendered by this type of beam are very similar to those obtained with a conventional x-ray beam.

  9. Effects of oxidative stress on hyperglycaemia-induced brain malformations in a diabetes mouse model

    Energy Technology Data Exchange (ETDEWEB)

    Jin, Ya [Department of Pediatrics, The First Affiliated Hospital, Jinan University, Guangzhou 510630, China (China); Wang, Guang [Division of Histology & Embryology, Key Laboratory for Regenerative Medicine of the Ministry of Education, Medical College, Jinan University, Guangzhou 510632 (China); Han, Sha-Sha; He, Mei-Yao [Department of Pediatrics, The First Affiliated Hospital, Jinan University, Guangzhou 510630, China (China); Cheng, Xin; Ma, Zheng-Lai [Division of Histology & Embryology, Key Laboratory for Regenerative Medicine of the Ministry of Education, Medical College, Jinan University, Guangzhou 510632 (China); Wu, Xia [Department of Pediatrics, The First Affiliated Hospital, Jinan University, Guangzhou 510630, China (China); Yang, Xuesong, E-mail: yang_xuesong@126.com [Division of Histology & Embryology, Key Laboratory for Regenerative Medicine of the Ministry of Education, Medical College, Jinan University, Guangzhou 510632 (China); Liu, Guo-Sheng, E-mail: tlgs@jnu.edu.cn [Department of Pediatrics, The First Affiliated Hospital, Jinan University, Guangzhou 510630, China (China)

    2016-09-10

    Pregestational diabetes mellitus (PGDM) enhances the risk of fetal neurodevelopmental defects. However, the mechanism of hyperglycaemia-induced neurodevelopmental defects is not fully understood. In this study, several typical neurodevelopmental defects were identified in the streptozotocin-induced diabetes mouse model. The neuron-specific class III beta-tubulin/forkhead box P1-labelled neuronal differentiation was suppressed and glial fibrillary acidic protein-labelled glial cell lineage differentiation was slightly promoted in pregestational diabetes mellitus (PGDM) mice. Various concentrations of glucose did not change the U87 cell viability, but glial cell line-derived neurotrophic factor expression was altered with varying glucose concentrations. Mouse maternal hyperglycaemia significantly increased Tunel{sup +} apoptosis but did not dramatically affect PCNA{sup +} cell proliferation in the process. To determine the cause of increased apoptosis, we determined the SOD activity, the expression of Nrf2 as well as its downstream anti-oxidative factors NQO1 and HO1, and found that all of them significantly increased in PGDM fetal brains compared with controls. However, Nrf2 expression in U87 cells was not significantly changed by different glucose concentrations. In mouse telencephalon, we observed the co-localization of Tuj-1 and Nrf2 expression in neurons, and down-regulating of Nrf2 in SH-SY5Y cells altered the viability of SH-SY5Y cells exposed to high glucose concentrations. Taken together, the data suggest that Nrf2-modulated antioxidant stress plays a crucial role in maternal hyperglycaemia-induced neurodevelopmental defects. - Highlights: • Typical neurodevelopmental defects could be observed in STZ-treated mouse fetuses. • Nrf2 played a crucial role in hyperglycaemia-induced brain malformations. • The effects of hyperglycaemia on neurons and glia cells were not same.

  10. Avian-like attributes of a virtual brain model of the oviraptorid theropod Conchoraptor gracilis

    Science.gov (United States)

    Kundrát, Martin

    2007-06-01

    An almost complete adult endoneurocranium of Conchoraptor gracilis Barsbold 1986 (Oviraptoridae; ZPAL MgD-I/95), discovered at the Hermiin Tsav locality (the Upper Cretaceous) in Mongolia, is analyzed. A virtual model of the endoneurocranial cavity was derived from CT scans and represents the most complete maniraptoran endocast to date. It displays reduced olfactory bulbs, large cerebral hemispheres in contact with the expanded cerebellum, an epiphysial projection, optic lobes displaced latero-ventrally, presumptive cerebellar folia, enlarged cerebellar auricles, and a deep medulla oblongata with a prominent ventral flexure. Contrary to Archaeopteryx, the shortened olfactory tract and cerebellum overtopping cerebral hemispheres of Conchoraptor resemble conditions in modern birds. Calculating brain mass relative to body mass indicates that Conchoraptor falls within the range of extant birds, whereas Archaeopteryx occupies a marginal position. Most of the endoneurocranial attributes, however, have a less birdlike appearance in Conchoraptor than do corresponding structures in Archaeopteryx and modern birds in which 1) postero-laterally expanded hemispheral domains broadly overlap the optic lobes, 2) the epiphysis projects to the posterior cerebrum, 3) lateral extension of the optic lobes substantially decreases a brain length-to-width ratio, 4) optic lobe and anterior hindbrain are superposed in lateral view, and 5) cerebellar and midbrain compartments are in distinct superposition. The endoneurocranial characteristics of Conchoraptor, taken together, suggest that the animal had a keen sense of vision, balance, and coordination. The data presented in this study do not allow an unambiguous assessment whether the avian-like endoneurocranial characteristics of the flightless Conchoraptor evolved convergently to those of avian theropods, or indicate a derivation of oviraptorosaurs from volant ancestors.

  11. Microwave and magnetic (M2 proteomics of a mouse model of mild traumatic brain injury

    Directory of Open Access Journals (Sweden)

    Teresa M. Evans

    2014-06-01

    Full Text Available Short-term increases in oxidative stress and decreases in motor function, including debilitating effects on balance and motor control, can occur following primary mild traumatic brain injuries (mTBI. However, the long-term effects on motor unit impairment and integrity as well as the molecular mechanisms underlying secondary injuries are poorly understood. We hypothesized that changes in central nervous system-specific protein (CSP expression might correlate to these long-term effects. To test our hypothesis, we longitudinally assessed a closed-skull mTBI mouse model, vs. sham control, at 1, 7, 30, and 120 days post-injury. Motor impairment was determined by rotarod and grip strength performance measures, while motor unit integrity was determined using electromyography. Relative protein expression was determined by microwave and magnetic (M2 proteomics of ipsilateral brain tissue, as previously described. Isoprostane measurements were performed to confirm a primary oxidative stress response. Decoding the relative expression of 476 ± 56 top-ranked proteins for each specimen revealed statistically significant changes in the expression of two well-known CSPs at 1, 7 and 30 days post-injury: P < 0.001 for myelin basic protein (MBP and p < 0.05 for myelin associated glycoprotein (MAG. This was confirmed by Western blot. Moreover, MAG, αII-spectrin (SPNA2 and neurofilament light (NEFL expression at 30 days post-injury were directly related to grip strength (p < 0.05. While higher-powered studies of larger cohorts merit further investigation, this study supports the proof-of-concept that M2 proteomics is a rapid method to quantify putative protein biomarkers and therapeutic targets of mTBI and suggests the feasibility of CSP expression correlations to long-term effects on motor impairment.

  12. Improving zero-training brain-computer interfaces by mixing model estimators

    Science.gov (United States)

    Verhoeven, T.; Hübner, D.; Tangermann, M.; Müller, K. R.; Dambre, J.; Kindermans, P. J.

    2017-06-01

    Objective. Brain-computer interfaces (BCI) based on event-related potentials (ERP) incorporate a decoder to classify recorded brain signals and subsequently select a control signal that drives a computer application. Standard supervised BCI decoders require a tedious calibration procedure prior to every session. Several unsupervised classification methods have been proposed that tune the decoder during actual use and as such omit this calibration. Each of these methods has its own strengths and weaknesses. Our aim is to improve overall accuracy of ERP-based BCIs without calibration. Approach. We consider two approaches for unsupervised classification of ERP signals. Learning from label proportions (LLP) was recently shown to be guaranteed to converge to a supervised decoder when enough data is available. In contrast, the formerly proposed expectation maximization (EM) based decoding for ERP-BCI does not have this guarantee. However, while this decoder has high variance due to random initialization of its parameters, it obtains a higher accuracy faster than LLP when the initialization is good. We introduce a method to optimally combine these two unsupervised decoding methods, letting one method’s strengths compensate for the weaknesses of the other and vice versa. The new method is compared to the aforementioned methods in a resimulation of an experiment with a visual speller. Main results. Analysis of the experimental results shows that the new method exceeds the performance of the previous unsupervised classification approaches in terms of ERP classification accuracy and symbol selection accuracy during the spelling experiment. Furthermore, the method shows less dependency on random initialization of model parameters and is consequently more reliable. Significance. Improving the accuracy and subsequent reliability of calibrationless BCIs makes these systems more appealing for frequent use.

  13. Brain neurotransmitters in an animal model with postpartum depressive-like behavior.

    Science.gov (United States)

    Avraham, Y; Hants, Y; Vorobeiv, L; Staum, M; Abu Ahmad, Wiessam; Mankuta, D; Galun, E; Arbel-Alon, S

    2017-05-30

    Post-Partum Depression (PPD) occurs in 15% of pregnancies and its patho-physiology is not known. We studied female BALB/c ("depressive") and C57BL/6 (control) mice as a model for PPD and assessed their behavior and correlates with brain neurotransmitters (NTs) - norepinephrine, dopamine, serotonin and intermediates, during the pre-pregnancy (PREP), pregnancy (PREG) and post-partum (PP) periods. Depressive-like behavior was evaluated by the Open Field (OFT), Tail Suspension (TST) and Forced Swim (FST) tests. Neurotransmitters (NTs) were determined in the striatum (care-giving), hippocampus (cognitive function) and hypothalamus (maternal care & eating behavior). In the BALB/c mice, while their performance in all behavioral tests was significantly reduced during pregnancy and P-P indicative of the development of depressive-like responses, no changes were observed in the C57BL/6 mice. Changes in NTs in BALB/C were as follows: PREP, all NTs in the three brain areas were decreased, although an increase in dopamine release was observed in the hippocampus. PREG: No changes were observed in the NTs except for a decrease in 5-HT in the striatum. P-P: striatum, low 5-HT, NE and dopamine; Hippocampus: low 5-HT, NE and high Dopamine; hypothalamus: all NTs increased, especially NE. Following pregnancy and delivery, the BALB/c mice developed depressive-like behavior associated with a significant decrease in 5-HT, dopamine and NE in the striatum and 5-HT and NE in the hippocampus. Dopamine increased in the latter together with a significant increase in all NTs in the hypothalamus. These findings suggest that the development of PPD may be associated with NT changes. Normalization of these alterations may have a role in the treatment of PPD. Copyright © 2017 Elsevier B.V. All rights reserved.

  14. Estimating Memory Deterioration Rates Following Neurodegeneration and Traumatic Brain Injuries in a Hopfield Network Model

    Directory of Open Access Journals (Sweden)

    Melanie Weber

    2017-11-01

    Full Text Available Neurodegenerative diseases and traumatic brain injuries (TBI are among the main causes of cognitive dysfunction in humans. At a neuronal network level, they both extensively exhibit focal axonal swellings (FAS, which in turn, compromise the information encoded in spike trains and lead to potentially severe functional deficits. There are currently no satisfactory quantitative predictors of decline in memory-encoding neuronal networks based on the impact and statistics of FAS. Some of the challenges of this translational approach include our inability to access small scale injuries with non-invasive methods, the overall complexity of neuronal pathologies, and our limited knowledge of how networks process biological signals. The purpose of this computational study is three-fold: (i to extend Hopfield's model for associative memory to account for the effects of FAS, (ii to calibrate FAS parameters from biophysical observations of their statistical distribution and size, and (iii to systematically evaluate deterioration rates for different memory-recall tasks as a function of FAS injury. We calculate deterioration rates for a face-recognition task to account for highly correlated memories and also for a discrimination task of random, uncorrelated memories with a size at the capacity limit of the Hopfield network. While it is expected that the performance of any injured network should decrease with injury, our results link, for the first time, the memory recall ability to observed FAS statistics. This allows for plausible estimates of cognitive decline for different stages of brain disorders within neuronal networks, bridging experimental observations following neurodegeneration and TBI with compromised memory recall. The work lends new insights to help close the gap between theory and experiment on how biological signals are processed in damaged, high-dimensional functional networks, and towards positing new diagnostic tools to measure cognitive

  15. Deep brain stimulation improves behavior and modulates neural circuits in a rodent model of schizophrenia.

    Science.gov (United States)

    Bikovsky, Lior; Hadar, Ravit; Soto-Montenegro, María Luisa; Klein, Julia; Weiner, Ina; Desco, Manuel; Pascau, Javier; Winter, Christine; Hamani, Clement

    2016-09-01

    Schizophrenia is a debilitating psychiatric disorder with a significant number of patients not adequately responding to treatment. Deep brain stimulation (DBS) is a surgical technique currently investigated for medically-refractory psychiatric disorders. Here, we use the poly I:C rat model of schizophrenia to study the effects of medial prefrontal cortex (mPFC) and nucleus accumbens (Nacc) DBS on two behavioral schizophrenia-like deficits, i.e. sensorimotor gating, as reflected by disrupted prepulse inhibition (PPI), and attentional selectivity, as reflected by disrupted latent inhibition (LI). In addition, the neurocircuitry influenced by DBS was studied using FDG PET. We found that mPFC- and Nacc-DBS alleviated PPI and LI abnormalities in poly I:C offspring, whereas Nacc- but not mPFC-DBS disrupted PPI and LI in saline offspring. In saline offspring, mPFC-DBS increased metabolism in the parietal cortex, striatum, ventral hippocampus and Nacc, while reducing it in the brainstem, cerebellum, hypothalamus and periaqueductal gray. Nacc-DBS, on the other hand, increased activity in the ventral hippocampus and olfactory bulb and reduced it in the septal area, brainstem, periaqueductal gray and hypothalamus. In poly I:C offspring changes in metabolism following mPFC-DBS were similar to those recorded in saline offspring, except for a reduced activity in the brainstem and hypothalamus. In contrast, Nacc-DBS did not induce any statistical changes in brain metabolism in poly I:C offspring. Our study shows that mPFC- or Nacc-DBS delivered to the adult progeny of poly I:C treated dams improves deficits in PPI and LI. Despite common behavioral responses, stimulation in the two targets induced different metabolic effects. Copyright © 2016. Published by Elsevier Inc.

  16. Estimating Memory Deterioration Rates Following Neurodegeneration and Traumatic Brain Injuries in a Hopfield Network Model

    Science.gov (United States)

    Weber, Melanie; Maia, Pedro D.; Kutz, J. Nathan

    2017-01-01

    Neurodegenerative diseases and traumatic brain injuries (TBI) are among the main causes of cognitive dysfunction in humans. At a neuronal network level, they both extensively exhibit focal axonal swellings (FAS), which in turn, compromise the information encoded in spike trains and lead to potentially severe functional deficits. There are currently no satisfactory quantitative predictors of decline in memory-encoding neuronal networks based on the impact and statistics of FAS. Some of the challenges of this translational approach include our inability to access small scale injuries with non-invasive methods, the overall complexity of neuronal pathologies, and our limited knowledge of how networks process biological signals. The purpose of this computational study is three-fold: (i) to extend Hopfield's model for associative memory to account for the effects of FAS, (ii) to calibrate FAS parameters from biophysical observations of their statistical distribution and size, and (iii) to systematically evaluate deterioration rates for different memory-recall tasks as a function of FAS injury. We calculate deterioration rates for a face-recognition task to account for highly correlated memories and also for a discrimination task of random, uncorrelated memories with a size at the capacity limit of the Hopfield network. While it is expected that the performance of any injured network should decrease with injury, our results link, for the first time, the memory recall ability to observed FAS statistics. This allows for plausible estimates of cognitive decline for different stages of brain disorders within neuronal networks, bridging experimental observations following neurodegeneration and TBI with compromised memory recall. The work lends new insights to help close the gap between theory and experiment on how biological signals are processed in damaged, high-dimensional functional networks, and towards positing new diagnostic tools to measure cognitive deficits. PMID

  17. How much detail is needed in modeling a transcranial magnetic stimulation figure-8 coil : Measurements and brain simulations

    NARCIS (Netherlands)

    Petrov, Petar I.; Mandija, Stefano; Sommer, Iris E.C.; Van Den Berg, Cornelis A.T.; Neggers, Sebastiaan F.W.

    2017-01-01

    Background: Despite TMS wide adoption, its spatial and temporal patterns of neuronal effects are not well understood. Although progress has been made in predicting induced currents in the brain using realistic finite element models (FEM), there is little consensus on how a magnetic field of a

  18. Antidepressant Effects of Pharmacopuncture on Behavior and Brain-Derived Neurotrophic Factor (BDNF Expression in Chronic Stress Model of Mice

    Directory of Open Access Journals (Sweden)

    Yunna Kim

    2017-12-01

    Conclusion: HJ11 improves depressive-like behaviors in the stress-induced mouse model of depression, and the results indicate that the neuroprotective effect of HJ11, identified by brain-derived neurotrophic factor expression, may play a critical role in its antidepressant effect.

  19. Circulation stabilizing therapy and pulmonary high-resolution computed tomography in a porcine brain-dead model

    NARCIS (Netherlands)

    Bozovic, G.; Steen, S. van der; Sjoberg, T.; Schaefer-Prokop, C.M.; Verschakelen, J.; Liao, Q.; Hoglund, P.; Siemund, R.; Bjorkman-Burtscher, I.M.

    2016-01-01

    BACKGROUND: Currently 80% of donor lungs are not accepted for transplantation, often due to fluid overload. Our aim was to investigate if forced fluid infusion may be replaced by a new pharmacological therapy to stabilize circulation after brain death in an animal model, and to assess therapy

  20. Differential effects of vascular endothelial growth factor A isoforms in a mouse brain metastasis model of human melanoma.

    NARCIS (Netherlands)

    Kusters, B.; Waal, R.M.W. de; Wesseling, P.; Verrijp, K.; Maass, C.N.; Heerschap, A.; Barentsz, J.O.; Sweep, C.G.J.; Ruiter, D.J.; Leenders, W.P.J.

    2003-01-01

    We reported previously that vascular endothelial growth factor isoform A (VEGF-A) expression by Mel57 human melanoma cells led to tumor progression in a murine brain metastasis model in an angiogenesis-independent fashion by dilation of co-opted, pre-existing vessels and concomitant enhanced blood

  1. Traumatic brain injury in modern war

    Science.gov (United States)

    Ling, Geoffrey S. F.; Hawley, Jason; Grimes, Jamie; Macedonia, Christian; Hancock, James; Jaffee, Michael; Dombroski, Todd; Ecklund, James M.

    2013-05-01

    Traumatic brain injury (TBI) is common and especially with military service. In Iraq and Afghanistan, explosive blast related TBI has become prominent and is mainly from improvised explosive devices (IED). Civilian standard of care clinical practice guidelines (CPG) were appropriate has been applied to the combat setting. When such CPGs do not exist or are not applicable, new practice standards for the military are created, as for TBI. Thus, CPGs for prehospital care of combat TBI CPG [1] and mild TBI/concussion [2] were introduced as was a DoD system-wide clinical care program, the first large scale system wide effort to address all severities of TBI in a comprehensive organized way. As TBI remains incompletely understood, substantial research is underway. For the DoD, leading this effort are The Defense and Veterans Brain Injury Center, National Intrepid Center of Excellence and the Defense Centers of Excellence for Psychological Health and Traumatic Brain Injury. This program is a beginning, a work in progress ready to leverage advances made scientifically and always with the intent of providing the best care to its military beneficiaries.

  2. Characterizing Deep Brain Stimulation effects in computationally efficient neural network models

    OpenAIRE

    Latteri, Alberta; Arena, Paolo; Mazzone, Paolo

    2011-01-01

    Background Recent studies on the medical treatment of Parkinson's disease (PD) led to the introduction of the so called Deep Brain Stimulation (DBS) technique. This particular therapy allows to contrast actively the pathological activity of various Deep Brain structures, responsible for the well known PD symptoms. This technique, frequently joined to dopaminergic drugs administration, replaces the surgical interventions implemented to contrast the activity of specific brain nuclei, called Bas...

  3. Brain Basics

    Medline Plus

    Full Text Available ... About Us Home > Health & Education > Educational Resources Brain Basics Introduction The Growing Brain The Working Brain Brain ... called the hypothalamic-pituitary-adrenal (HPA) axis. Brain Basics in Real Life Brain Basics in Real Life— ...

  4. Ammonium accumulation and cell death in a rat 3D brain cell model of glutaric aciduria type I.

    Directory of Open Access Journals (Sweden)

    Paris Jafari

    Full Text Available Glutaric aciduria type I (glutaryl-CoA dehydrogenase deficiency is an inborn error of metabolism that usually manifests in infancy by an acute encephalopathic crisis and often results in permanent motor handicap. Biochemical hallmarks of this disease are elevated levels of glutarate and 3-hydroxyglutarate in blood and urine. The neuropathology of this disease is still poorly understood, as low lysine diet and carnitine supplementation do not always prevent brain damage, even in early-treated patients. We used a 3D in vitro model of rat organotypic brain cell cultures in aggregates to mimic glutaric aciduria type I by repeated administration of 1 mM glutarate or 3-hydroxyglutarate at two time points representing different developmental stages. Both metabolites were deleterious for the developing brain cells, with 3-hydroxyglutarate being the most toxic metabolite in our model. Astrocytes were the cells most strongly affected by metabolite exposure. In culture medium, we observed an up to 11-fold increase of ammonium in the culture medium with a concomitant decrease of glutamine. We further observed an increase in lactate and a concomitant decrease in glucose. Exposure to 3-hydroxyglutarate led to a significantly increased cell death rate. Thus, we propose a three step model for brain damage in glutaric aciduria type I: (i 3-OHGA causes the death of astrocytes, (ii deficiency of the astrocytic enzyme glutamine synthetase leads to intracerebral ammonium accumulation, and (iii high ammonium triggers secondary death of other brain cells. These unexpected findings need to be further investigated and verified in vivo. They suggest that intracerebral ammonium accumulation might be an important target for the development of more effective treatment strategies to prevent brain damage in patients with glutaric aciduria type I.

  5. Prospective Tracking and Analysis of Traumatic Brain Injury in Veterans and Military Personnel.

    Science.gov (United States)

    Licona, Nytzia E; Chung, Joyce S; Poole, John H; Salerno, Rose M; Laurenson, Nancy M; Harris, Odette A

    2017-02-01

    To describe the ongoing Clinical Tracking Form (CTF) study of the Defense and Veterans Brain Injury Center (DVBIC). Prospective longitudinal study. Data at baseline and postinjury are collected on participants through interview and questionnaire, review of medical records, and periodic follow-ups throughout their lifetime. A regional DVBIC site located at a Veterans Affairs Medical Center. Participants (N=211; age range, 18-75y) were enrolled between January 1, 2005, and December 31, 2012, at a regional DVBIC site. Not applicable. Injury information, functioning, and psychological health. Sixty percent of 211 participants were identified as having severe traumatic brain injuries (TBIs), 14% moderate TBIs, and 26% mild TBIs. Of these 211 participants, 79% sustained closed head injuries, 15% penetrating head injuries, and 6% were not reported. Comparing the severity of TBI in combat versus stateside situations, most of the mild injuries (71%) occurred in combat locations, while most of the severe injuries (62%) occurred in the United States. Among those injured in combat, blast-related TBIs (82%) greatly outnumbered non-blast-related TBIs, regardless of severity. The CTF study serves as a significant resource of data to understand the effect and outcomes of TBI in the military population. The lifelong experience of military veterans across the full spectrum of TBI and recovery will be recorded through the CTF, and will translate into more informed clinical decisions and educational efforts to guide future research pathways. Copyright © 2016 American Congress of Rehabilitation Medicine. All rights reserved.

  6. Comparison of brain capillary endothelial cell-based and epithelial (MDCK-MDR1, Caco-2, and VB-Caco-2) cell-based surrogate blood-brain barrier penetration models.

    Science.gov (United States)

    Hellinger, Eva; Veszelka, Szilvia; Tóth, Andrea E; Walter, Fruzsina; Kittel, Agnes; Bakk, Mónika Laura; Tihanyi, Károly; Háda, Viktor; Nakagawa, Shinsuke; Duy, Thuy Dinh Ha; Niwa, Masami; Deli, Mária A; Vastag, Monika

    2012-10-01

    An accurate means of predicting blood-brain barrier (BBB) penetration and blood-brain partitioning of NCEs (new chemical entities) would fulfill a major need in pharmaceutical research. Currently, an industry-standard BBB drug penetration model is not available. Primary brain capillary endothelial cells, optionally co-cultured with astrocytes and/or pericytes, are the most valued models of BBB. For routine use, establishing and maintaining a co-culture system is too costly and labor intensive. Alternatively, non-cerebral cell lines such as MDCK-MDR1 are used, and most recently, the suitability of native and modified Caco-2 for predicting brain penetration has also come under investigation. This study provides comparative data on the morphology and functionality of the high integrity brain capillary endothelial BBB model (EPA: triple culture of brain capillary endothelial cells with pericytes and astrocytes) and the epithelial cell-based (native Caco-2, high P-glycoprotein expressing vinblastine-treated VB-Caco-2 and MDCK-MDR1) surrogate BBB models. Using a panel of 10 compounds VB-Caco-2 and MDCK-MDR1 cell lines show restrictive paracellular pathway and BBB-like selective passive permeability that makes them comparable to the rat brain BBB model, which gave correlation with the highest r(2) value with in vivo permeability data. In bidirectional assay, the VB-Caco-2 and the MDCK-MDR1 models identified more P-glycoprotein drug substrates than the rat brain BBB model. While the complexity and predictive value of the BBB model is the highest, for the screening of NCEs to determine whether they are efflux substrates or not, the VB-Caco-2 and the MDCK-MDR1 models may provide a simple and inexpensive tool. Copyright © 2012 Elsevier B.V. All rights reserved.

  7. Brain Organization into Resting State Networks Emerges at Criticality on a Model of the Human Connectome

    Science.gov (United States)

    Haimovici, Ariel; Tagliazucchi, Enzo; Balenzuela, Pablo; Chialvo, Dante R.

    2013-04-01

    The relation between large-scale brain structure and function is an outstanding open problem in neuroscience. We approach this problem by studying the dynamical regime under which realistic spatiotemporal patterns of brain activity emerge from the empirically derived network of human brain neuroanatomical connections. The results show that critical dynamics unfolding on the structural connectivity of the human brain allow the recovery of many key experimental findings obtained from functional magnetic resonance imaging, such as divergence of the correlation length, the anomalous scaling of correlation fluctuations, and the emergence of large-scale resting state networks.

  8. In situ mouse carotid perfusion model: glucose and cholesterol transport in the eye and brain.

    Science.gov (United States)

    Cattelotte, Julie; André, Pascal; Ouellet, Mélissa; Bourasset, Fanchon; Scherrmann, Jean-Michel; Cisternino, Salvatore

    2008-08-01

    The in situ mouse brain perfusion method for measuring blood-brain barrier permeability was adapted to assess transport of solutes at the blood-brain and blood-eye barriers. The procedure was checked with radiolabeled markers in oxygenated bicarbonate-buffered fluid infused for 30 to 120 sec via a carotid artery. Vascular flow estimated with diazepam was 2.2-fold lower in the eye than in the brain. The vascular volume and the integrity markers sucrose and inulin indicated that a perfusion flow rate of 2.5 mL/min preserved the physical integrity of these organs. However, the brain vasculature integrity was more sensitive to acute perfusion pressure than the eye vasculature. The functional capacities of blood barriers were assessed with D-glucose; its transport followed Michaelis-Menten kinetics with an apparent K(m) of 7.6 mmol/L and a V(max) of 23 micromol/sec per g in the brain, and a K(m) of 22.9 mmol/L and a V(max) of 40 micromol/sec per g in the eye. The transport of cholesterol to the brain and eye was significantly enhanced by adding the Abca1 inhibitor probucol, suggesting an Abca1-mediated efflux at the mouse brain and eye blood barriers. Thus in situ carotid perfusion is suitable for elucidating transport processes at the blood-brain and blood-eye barriers.

  9. Brain Mapping-Based Model of Δ(9)-Tetrahydrocannabinol Effects on Connectivity in the Pain Matrix.

    Science.gov (United States)

    Walter, Carmen; Oertel, Bruno G; Felden, Lisa; Kell, Christian A; Nöth, Ulrike; Vermehren, Johannes; Kaiser, Jochen; Deichmann, Ralf; Lötsch, Jörn

    2016-05-01

    Cannabinoids receive increasing interest as analgesic treatments. However, the clinical use of Δ(9)-tetrahydrocannabinol (Δ(9)-THC) has progressed with justified caution, which also owes to the incomplete mechanistic understanding of its analgesic effects, in particular its interference with the processing of sensory or affective components of pain. The present placebo-controlled crossover study therefore focused on the effects of 20 mg oral THC on the connectivity between brain areas of the pain matrix following experimental stimulation of trigeminal nocisensors in 15 non-addicted healthy volunteers. A general linear model (GLM) analysis identified reduced activations in the hippocampus and the anterior insula following THC administration. However, assessment of psychophysiological interaction (PPI) revealed that the effects of THC first consisted in a weakening of the interaction between the thalamus and the secondary somatosensory cortex (S2). From there, dynamic causal modeling (DCM) was employed to infer that THC attenuated the connections to the hippocampus and to the anterior insula, suggesting that the reduced activations in these regions are secondary to a reduction of the connectivity from somatosensory regions by THC. These findings may have consequences for the way THC effects are currently interpreted: as cannabinoids are increasingly considered in pain treatment, present results provide relevant information about how THC interferes with the affective component of pain. Specifically, the present experiment suggests that THC does not selectively affect limbic regions, but rather interferes with sensory processing which in turn reduces sensory-limbic connectivity, leading to deactivation of affective regions.

  10. Implementing Innovative Models of Dementia Care: The Healthy Aging Brain Center

    Science.gov (United States)

    Boustani, Malaz A.; Sachs, Greg A.; Alder, Catherine A.; Munger, Stephanie; Schubert, Cathy C.; Guerriero Austrom, Mary; Hake, Ann; Unverzagt, Frederick W.; Farlow, Martin; Matthews, Brandy R.; Perkins, Anthony J.; Beck, Robin A.; Callahan, Christopher M.

    2010-01-01

    BACKGROUND Recent randomized controlled trials have demonstrated the effectiveness of the collaborative dementia care model targeting both patients suffering from dementia and their informal caregivers. OBJECTIVE To implement a sustainable collaborative dementia care program in a public health care system in Indianapolis. METHODS We used the framework of Complex Adaptive System and the tool of the Reflective Adaptive Process to translate the results of the dementia care trial into the Healthy Aging Brain Center (HABC). RESULTS Within its first year of operation, the HABC delivered 528 visits to serve 208 patients and 176 informal caregivers. The mean age of HABC patients was 73.8 (SD 9.5), 40% were African Americans, 42% had less than high school education, 14% had normal cognitive status, 39% received a diagnosis of mild cognitive impairment, and 46% were diagnosed with dementia. Within 12 months of the initial HABC visit, 28% of patients had at least one visit to an emergency room (ER) and 14% were hospitalized with a mean length of stay of five days. The rate of a one-week ER revisit was 14% and the 30-day re-hospitalization rate was 11%. Only 5% of HABC patients received an order for neuroleptics and only 16% had simultaneous orders for both definite anticholinergic and anti-dementia drugs. CONCLUSION The tools of “implementation science” can be utilized to translate a health care delivery model developed in the research laboratory to a practical, operational, health care delivery program. PMID:21271387

  11. Deep models for brain EM image segmentation: novel insights and improved performance.

    Science.gov (United States)

    Fakhry, Ahmed; Peng, Hanchuan; Ji, Shuiwang

    2016-08-01

    Accurate segmentation of brain electron microscopy (EM) images is a critical step in dense circuit reconstruction. Although deep neural networks (DNNs) have been widely used in a number of applications in computer vision, most of these models that proved to be effective on image classification tasks cannot be applied directly to EM image segmentation, due to the different objectives of these tasks. As a result, it is desirable to develop an optimized architecture that uses the full power of DNNs and tailored specifically for EM image segmentation. In this work, we proposed a novel design of DNNs for this task. We trained a pixel classifier that operates on raw pixel intensities with no preprocessing to generate probability values for each pixel being a membrane or not. Although the use of neural networks in image segmentation is not completely new, we developed novel insights and model architectures that allow us to achieve superior performance on EM image segmentation tasks. Our submission based on these insights to the 2D EM Image Segmentation Challenge achieved the best performance consistently across all the three evaluation metrics. This challenge is still ongoing and the results in this paper are as of June 5, 2015. https://github.com/ahmed-fakhry/dive : sji@eecs.wsu.edu. © The Author 2016. Published by Oxford University Press. All rights reserved. For Permissions, please e-mail: journals.permissions@oup.com.

  12. Longitudinal MRI monitoring of brain damage in the neonatal ventral hippocampal lesion rat model of schizophrenia.

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    Bertrand, Jean-Baptiste; Langlois, Jean-Baptiste; Bégou, Mélina; Volle, Julien; Brun, Philippe; d'Amato, Thierry; Saoud, Mohamed; Suaud-Chagny, Marie-Françoise

    2010-02-01

    Rat with excitotoxic neonatal ventral hippocampal lesions (NVHL rats) is considered as a heuristic neurodevelopmental model for studying schizophrenia. Extensive study of this model is limited by the lack of clear validity criteria of such lesions and because ascertaining of the lesions is realized postmortem with histological examination after completing experiments. Here, in a first experiment, by assessing the locomotor response to amphetamine in adult NVHL rats, we further specify that the lesions must be bilateral and confined to the ventral hippocampus to obtain the validated behavioral phenotype. We then show a longitudinal magnetic resonance imaging (MRI) protocol suitable for the detection of brain structural changes in NVHL rats. The T(2)-weighted images acquired in adult NVHL rats reveal the same structural changes as those appraised with histological protocol. Moreover, we demonstrate that the lesion status in adulthood can be accurately predicted from the T(2)-weighted images acquired in the juvenile period. As technical advantages, our MRI protocol makes possible to select animals according to lesion criteria as soon as in the juvenile period before long-lasting experiments and gives access in vivo to a quantitative parameter indicative of the lesion extent. Finally, we show that the lesion size increases only slightly between juvenile and adult periods. These latter results are discussed in the context of the specific postpubertal emergence of the behavioral deficits in NVHL rats.

  13. Predicting emotional well-being following traumatic brain injury: a test of mediated and moderated models.

    Science.gov (United States)

    Kendall, Elizabeth; Terry, Deborah

    2009-09-01

    This study examined two models for predicting emotional well-being following traumatic brain injury (TBI), namely the Lazarus and Folkman (1984) mediated model of stress and coping and the stress-buffer hypothesis (Cohen & Edwards, 1988). The mediated model suggests that antecedent variables (i.e., personal and environmental resources) will predict emotional well-being, but their effect will be mediated through cognitive variables, such as appraisal and coping. In contrast, the moderated (buffer) hypothesis suggests that resources will protect individuals from the effects of stress, so will have different relationships with outcome at different levels of perceived stress. Ninety individuals with TBI were recruited from a major hospital in Brisbane, Australia. They and their relatives completed questionnaires at three time intervals: discharge, one month and nine months post-discharge, discharge being in 1998. Hierarchical regression was used to examine the relationships among the proposed predictors, mediators and outcomes. Support was found for some aspects of both models in the short-term. In the long-term, stress-buffer effects were no longer apparent. However, with the exception of family support, the predictors all influenced long-term adjustment through their impact on short-term adjustment. The role of family support as a direct predictor of emotional well-being in the long-term is highlighted. The findings have the potential to enable the identification of "at risk" individuals prior to discharge and can highlight important foci for rehabilitation. Specifically, the study has identified the importance of early psychological intervention to address appraisal and the need to engage families in rehabilitation.

  14. Probing the interaction of brain fatty acid binding protein (B-FABP with model membranes.

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    Fábio Dyszy

    Full Text Available Brain fatty acid-binding protein (B-FABP interacts with biological membranes and delivers polyunsaturated fatty acids (FAs via a collisional mechanism. The binding of FAs in the protein and the interaction with membranes involve a motif called "portal region", formed by two small α-helices, A1 and A2, connected by a loop. We used a combination of site-directed mutagenesis and electron spin resonance to probe the changes in the protein and in the membrane model induced by their interaction. Spin labeled B-FABP mutants and lipidic spin probes incorporated into a membrane model confirmed that B-FABP interacts with micelles through the portal region and led to structural changes in the protein as well in the micelles. These changes were greater in the presence of LPG when compared to the LPC models. ESR spectra of B-FABP labeled mutants showed the presence of two groups of residues that responded to the presence of micelles in opposite ways. In the presence of lysophospholipids, group I of residues, whose side chains point outwards from the contact region between the helices, had their mobility decreased in an environment of lower polarity when compared to the same residues in solution. The second group, composed by residues with side chains situated at the interface between the α-helices, experienced an increase in mobility in the presence of the model membranes. These modifications in the ESR spectra of B-FABP mutants are compatible with a less ordered structure of the portal region inner residues (group II that is likely to facilitate the delivery of FAs to target membranes. On the other hand, residues in group I and micelle components have their mobilities decreased probably as a result of the formation of a collisional complex. Our results bring new insights for the understanding of the gating and delivery mechanisms of FABPs.

  15. Deep brain stimulation exacerbates hypokinetic dysarthria in a rat model of Parkinson's disease.

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    King, Nathaniel O; Anderson, Collin J; Dorval, Alan D

    2016-02-01

    Motor symptoms of Parkinson's disease (PD) follow the degeneration of dopaminergic neurons in the substantia nigra pars compacta. Deep brain stimulation (DBS) treats some parkinsonian symptoms, such as tremor, rigidity, and bradykinesia, but may worsen certain medial motor symptoms, including hypokinetic dysarthria. The mechanisms by which DBS exacerbates dysarthria while improving other symptoms are unclear and difficult to study in human patients. This study proposes an animal model of DBS-exacerbated dysarthria. We use the unilateral, 6-hydroxydopamine (6-OHDA) rat model of PD to test the hypothesis that DBS exacerbates quantifiable aspects of vocalization. Mating calls were recorded from sexually experienced male rats under healthy and parkinsonian conditions and during DBS of the subthalamic nucleus. Relative to healthy rats, parkinsonian animals made fewer calls with shorter and less complex vocalizations. In the parkinsonian rats, putatively therapeutic DBS further reduced call frequency, duration, and complexity. The individual utterances of parkinsonian rats spanned a greater bandwidth than those of healthy rats, potentially reducing the effectiveness of the vocal signal. This utterance bandwidth was further increased by DBS. We propose that the parkinsonism-associated changes in call frequency, duration, complexity, and dynamic range combine to constitute a rat analog of parkinsonian dysarthria. Because DBS exacerbates the parkinsonism-associated changes in each of these metrics, the subthalamic stimulated 6-OHDA rat is a good model of DBS-induced hypokinetic dysarthria in PD. This model will help researchers examine how DBS alleviates many motor symptoms of PD while exacerbating parkinsonian speech deficits that can greatly diminish patient quality of life. © 2015 Wiley Periodicals, Inc.

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

    Science.gov (United States)

    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.

  17. Assessment of Blood-Brain Barrier Permeability by Dynamic Contrast-Enhanced MRI in Transient Middle Cerebral Artery Occlusion Model after Localized Brain Cooling in Rats

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    Kim, Eun Soo [Department of Radiology, Hallym University Sacred Heart Hospital, Hallym University College of Medicine, Anyang 14068 (Korea, Republic of); Lee, Seung-Koo [Department of Radiology, Yonsei University College of Medicine, Seoul 03722 (Korea, Republic of); Kwon, Mi Jung [Department of Pathology, Hallym University Sacred Heart Hospital, Hallym University College of Medicine, Anyang 14068 (Korea, Republic of); Lee, Phil Hye [Department of Neurology, Yonsei University College of Medicine, Seoul 03722 (Korea, Republic of); Ju, Young-Su [Department of Industrial Medicine, Hallym University Sacred Heart Hospital, Hallym University College of Medicine, Anyang 14068 (Korea, Republic of); Yoon, Dae Young [Department of Radiology, Hallym University Kangdong Sacred Heart Hospital, Hallym University College of Medicine, Seoul 05355 (Korea, Republic of); Kim, Hye Jeong [Department of Radiology, Kangnam Sacred Heart Hospital, Hallym University College of Medicine, Seoul 07441 (Korea, Republic of); Lee, Kwan Seop [Department of Radiology, Hallym University Sacred Heart Hospital, Hallym University College of Medicine, Anyang 14068 (Korea, Republic of)

    2016-11-01

    The purpose of this study was to evaluate the effects of localized brain cooling on blood-brain barrier (BBB) permeability following transient middle cerebral artery occlusion (tMCAO) in rats, by using dynamic contrast-enhanced (DCE)-MRI. Thirty rats were divided into 3 groups of 10 rats each: control group, localized cold-saline (20℃) infusion group, and localized warm-saline (37℃) infusion group. The left middle cerebral artery (MCA) was occluded for 1 hour in anesthetized rats, followed by 3 hours of reperfusion. In the localized saline infusion group, 6 mL of cold or warm saline was infused through the hollow filament for 10 minutes after MCA occlusion. DCE-MRI investigations were performed after 3 hours and 24 hours of reperfusion. Pharmacokinetic parameters of the extended Tofts-Kety model were calculated for each DCE-MRI. In addition, rotarod testing was performed before tMCAO, and on days 1-9 after tMCAO. Myeloperoxidase (MPO) immunohisto-chemistry was performed to identify infiltrating neutrophils associated with the inflammatory response in the rat brain. Permeability parameters showed no statistical significance between cold and warm saline infusion groups after 3-hour reperfusion 0.09 ± 0.01 min{sup -1} vs. 0.07 ± 0.02 min{sup -1}, p = 0.661 for K{sup trans}; 0.30 ± 0.05 min{sup -1} vs. 0.37 ± 0.11 min{sup -1}, p = 0.394 for kep, respectively. Behavioral testing revealed no significant difference among the three groups. However, the percentage of MPO-positive cells in the cold-saline group was significantly lower than those in the control and warm-saline groups (p < 0.05). Localized brain cooling (20℃) does not confer a benefit to inhibit the increase in BBB permeability that follows transient cerebral ischemia and reperfusion in an animal model, as compared with localized warm-saline (37℃) infusion group.

  18. Assessment of blood-brain barrier permeability by dynamic contrast-enhanced MRI in trans