Science.gov

Sample records for ad neuroimaging initiative

  1. The informatics core of the Alzheimer's Disease Neuroimaging Initiative

    PubMed Central

    Toga, Arthur W.; Crawford, Karen L.

    2010-01-01

    The Alzheimer's Diseases Neuroimaging Initiative project has brought together geographically distributed investigators, each collecting data on the progression of Alzheimer's disease. The quantity and diversity of the imaging, clinical, cognitive, biochemical, and genetic data acquired and generated throughout the study necessitated sophisticated informatics systems to organize, manage, and disseminate data and results. We describe, here, a successful and comprehensive system that provides powerful mechanisms for processing, integrating, and disseminating these data not only to support the research needs of the investigators who make up the Alzheimer's Diseases Neuroimaging Initiative cores, but also to provide widespread data access to the greater scientific community for the study of Alzheimer's Disease. PMID:20451873

  2. Impact of the Alzheimer’s Disease Neuroimaging Initiative, 2004 to 2014

    PubMed Central

    Weiner, Michael W.; Veitch, Dallas P.; Aisen, Paul S.; Beckett, Laurel A.; Cairns, Nigel J.; Cedarbaum, Jesse; Donohue, Michael C.; Green, Robert C.; Harvey, Danielle; Jack, Clifford R.; Jagust, William; Morris, John C.; Petersen, Ronald C.; Saykin, Andrew J.; Shaw, Leslie; Thompson, Paul M.; Toga, Arthur W.; Trojanowski, John Q.

    2015-01-01

    Introduction The Alzheimer’s Disease Neuroimaging Initiative (ADNI) was established in 2004 to facilitate the development of effective treatments for Alzheimer’s disease (AD) by validating biomarkers for AD clinical trials. Methods We searched for ADNI publications using established methods. Results ADNI has (1) developed standardized biomarkers for use in clinical trial subject selection and as surrogate outcome measures; (2) standardized protocols for use across multiple centers; (3) initiated worldwide ADNI; (4) inspired initiatives investigating traumatic brain injury and post-traumatic stress disorder in military populations, and depression, respectively, as an AD risk factor; (5) acted as a data-sharing model; (6) generated data used in over 600 publications, leading to the identification of novel AD risk alleles, and an understanding of the relationship between biomarkers and AD progression; and (7) inspired other public-private partnerships developing biomarkers for Parkinson’s disease and multiple sclerosis. Discussion ADNI has made myriad impacts in its first decade. A competitive renewal of the project in 2015 would see the use of newly developed tau imaging ligands, and the continued development of recruitment strategies and outcome measures for clinical trials. PMID:26194320

  3. The Alzheimer’s Disease Neuroimaging Initiative: Progress report and future plans

    PubMed Central

    Weiner, Michael W.; Aisen, Paul S.; Jack, Clifford R.; Jagust, William J.; Trojanowski, John Q.; Shaw, Leslie; Saykin, Andrew J.; Morris, John C.; Cairns, Nigel; Beckett, Laurel A.; Toga, Arthur; Green, Robert; Walter, Sarah; Soares, Holly; Snyder, Peter; Siemers, Eric; Potter, William; Cole, Patricia E.; Schmidt, Mark

    2010-01-01

    The Alzheimer’s Disease Neuroimaging Initiative (ADNI) beginning in October 2004, is a 6-year re-search project that studies changes of cognition, function, brain structure and function, and biomarkers in elderly controls, subjects with mild cognitive impairment, and subjects with Alzheimer’s disease (AD). A major goal is to determine and validate MRI, PET images, and cerebrospinal fluid (CSF)/blood biomarkers as predictors and outcomes for use in clinical trials of AD treatments. Structural MRI, FDG PET, C-11 Pittsburgh compound B (PIB) PET, CSF measurements of amyloid β (Aβ) and species of tau, with clinical/cognitive measurements were performed on elderly controls, subjects with mild cognitive impairment, and subjects with AD. Structural MRI shows high rates of brain atrophy, and has high statistical power for determining treatment effects. FDG PET, C-11 Pittsburgh compound B PET, and CSF measurements of Aβ and tau were significant predictors of cognitive decline and brain atrophy. All data are available at UCLA/LONI/ADNI, without embargo. ADNI-like projects started in Australia, Europe, Japan, and Korea. ADNI provides significant new information concerning the progression of AD. PMID:20451868

  4. Intrinsic functional component analysis via sparse representation on Alzheimer's disease neuroimaging initiative database.

    PubMed

    Jiang, Xi; Zhang, Xin; Zhu, Dajiang

    2014-10-01

    Alzheimer's disease (AD) is the most common type of dementia (accounting for 60% to 80%) and is the fifth leading cause of death for those people who are 65 or older. By 2050, one new case of AD in United States is expected to develop every 33 sec. Unfortunately, there is no available effective treatment that can stop or slow the death of neurons that causes AD symptoms. On the other hand, it is widely believed that AD starts before development of the associated symptoms, so its prestages, including mild cognitive impairment (MCI) or even significant memory concern (SMC), have received increasing attention, not only because of their potential as a precursor of AD, but also as a possible predictor of conversion to other neurodegenerative diseases. Although these prestages have been defined clinically, accurate/efficient diagnosis is still challenging. Moreover, brain functional abnormalities behind those alterations and conversions are still unclear. In this article, by developing novel sparse representations of whole-brain resting-state functional magnetic resonance imaging signals and by using the most updated Alzheimer's Disease Neuroimaging Initiative (ADNI) dataset, we successfully identified multiple functional components simultaneously, and which potentially represent those intrinsic functional networks involved in the resting-state activities. Interestingly, these identified functional components contain all the resting-state networks obtained from traditional independent-component analysis. Moreover, by using the features derived from those functional components, it yields high classification accuracy for both AD (94%) and MCI (92%) versus normal controls. Even for SMC we can still have 92% accuracy. PMID:24846640

  5. Intrinsic functional component analysis via sparse representation on Alzheimer's disease neuroimaging initiative database.

    PubMed

    Jiang, Xi; Zhang, Xin; Zhu, Dajiang

    2014-10-01

    Alzheimer's disease (AD) is the most common type of dementia (accounting for 60% to 80%) and is the fifth leading cause of death for those people who are 65 or older. By 2050, one new case of AD in United States is expected to develop every 33 sec. Unfortunately, there is no available effective treatment that can stop or slow the death of neurons that causes AD symptoms. On the other hand, it is widely believed that AD starts before development of the associated symptoms, so its prestages, including mild cognitive impairment (MCI) or even significant memory concern (SMC), have received increasing attention, not only because of their potential as a precursor of AD, but also as a possible predictor of conversion to other neurodegenerative diseases. Although these prestages have been defined clinically, accurate/efficient diagnosis is still challenging. Moreover, brain functional abnormalities behind those alterations and conversions are still unclear. In this article, by developing novel sparse representations of whole-brain resting-state functional magnetic resonance imaging signals and by using the most updated Alzheimer's Disease Neuroimaging Initiative (ADNI) dataset, we successfully identified multiple functional components simultaneously, and which potentially represent those intrinsic functional networks involved in the resting-state activities. Interestingly, these identified functional components contain all the resting-state networks obtained from traditional independent-component analysis. Moreover, by using the features derived from those functional components, it yields high classification accuracy for both AD (94%) and MCI (92%) versus normal controls. Even for SMC we can still have 92% accuracy.

  6. Intrinsic Functional Component Analysis via Sparse Representation on Alzheimer's Disease Neuroimaging Initiative Database

    PubMed Central

    Jiang, Xi; Zhang, Xin

    2014-01-01

    Abstract Alzheimer's disease (AD) is the most common type of dementia (accounting for 60% to 80%) and is the fifth leading cause of death for those people who are 65 or older. By 2050, one new case of AD in United States is expected to develop every 33 sec. Unfortunately, there is no available effective treatment that can stop or slow the death of neurons that causes AD symptoms. On the other hand, it is widely believed that AD starts before development of the associated symptoms, so its prestages, including mild cognitive impairment (MCI) or even significant memory concern (SMC), have received increasing attention, not only because of their potential as a precursor of AD, but also as a possible predictor of conversion to other neurodegenerative diseases. Although these prestages have been defined clinically, accurate/efficient diagnosis is still challenging. Moreover, brain functional abnormalities behind those alterations and conversions are still unclear. In this article, by developing novel sparse representations of whole-brain resting-state functional magnetic resonance imaging signals and by using the most updated Alzheimer's Disease Neuroimaging Initiative (ADNI) dataset, we successfully identified multiple functional components simultaneously, and which potentially represent those intrinsic functional networks involved in the resting-state activities. Interestingly, these identified functional components contain all the resting-state networks obtained from traditional independent-component analysis. Moreover, by using the features derived from those functional components, it yields high classification accuracy for both AD (94%) and MCI (92%) versus normal controls. Even for SMC we can still have 92% accuracy. PMID:24846640

  7. 2014 Update of the Alzheimer's Disease Neuroimaging Initiative: A review of papers published since its inception.

    PubMed

    Weiner, Michael W; Veitch, Dallas P; Aisen, Paul S; Beckett, Laurel A; Cairns, Nigel J; Cedarbaum, Jesse; Green, Robert C; Harvey, Danielle; Jack, Clifford R; Jagust, William; Luthman, Johan; Morris, John C; Petersen, Ronald C; Saykin, Andrew J; Shaw, Leslie; Shen, Li; Schwarz, Adam; Toga, Arthur W; Trojanowski, John Q

    2015-06-01

    The Alzheimer's Disease Neuroimaging Initiative (ADNI) is an ongoing, longitudinal, multicenter study designed to develop clinical, imaging, genetic, and biochemical biomarkers for the early detection and tracking of Alzheimer's disease (AD). The initial study, ADNI-1, enrolled 400 subjects with early mild cognitive impairment (MCI), 200 with early AD, and 200 cognitively normal elderly controls. ADNI-1 was extended by a 2-year Grand Opportunities grant in 2009 and by a competitive renewal, ADNI-2, which enrolled an additional 550 participants and will run until 2015. This article reviews all papers published since the inception of the initiative and summarizes the results to the end of 2013. The major accomplishments of ADNI have been as follows: (1) the development of standardized methods for clinical tests, magnetic resonance imaging (MRI), positron emission tomography (PET), and cerebrospinal fluid (CSF) biomarkers in a multicenter setting; (2) elucidation of the patterns and rates of change of imaging and CSF biomarker measurements in control subjects, MCI patients, and AD patients. CSF biomarkers are largely consistent with disease trajectories predicted by β-amyloid cascade (Hardy, J Alzheimer's Dis 2006;9(Suppl 3):151-3) and tau-mediated neurodegeneration hypotheses for AD, whereas brain atrophy and hypometabolism levels show predicted patterns but exhibit differing rates of change depending on region and disease severity; (3) the assessment of alternative methods of diagnostic categorization. Currently, the best classifiers select and combine optimum features from multiple modalities, including MRI, [(18)F]-fluorodeoxyglucose-PET, amyloid PET, CSF biomarkers, and clinical tests; (4) the development of blood biomarkers for AD as potentially noninvasive and low-cost alternatives to CSF biomarkers for AD diagnosis and the assessment of α-syn as an additional biomarker; (5) the development of methods for the early detection of AD. CSF biomarkers,

  8. 2014 Update of the Alzheimer's Disease Neuroimaging Initiative: A review of papers published since its inception.

    PubMed

    Weiner, Michael W; Veitch, Dallas P; Aisen, Paul S; Beckett, Laurel A; Cairns, Nigel J; Cedarbaum, Jesse; Green, Robert C; Harvey, Danielle; Jack, Clifford R; Jagust, William; Luthman, Johan; Morris, John C; Petersen, Ronald C; Saykin, Andrew J; Shaw, Leslie; Shen, Li; Schwarz, Adam; Toga, Arthur W; Trojanowski, John Q

    2015-06-01

    The Alzheimer's Disease Neuroimaging Initiative (ADNI) is an ongoing, longitudinal, multicenter study designed to develop clinical, imaging, genetic, and biochemical biomarkers for the early detection and tracking of Alzheimer's disease (AD). The initial study, ADNI-1, enrolled 400 subjects with early mild cognitive impairment (MCI), 200 with early AD, and 200 cognitively normal elderly controls. ADNI-1 was extended by a 2-year Grand Opportunities grant in 2009 and by a competitive renewal, ADNI-2, which enrolled an additional 550 participants and will run until 2015. This article reviews all papers published since the inception of the initiative and summarizes the results to the end of 2013. The major accomplishments of ADNI have been as follows: (1) the development of standardized methods for clinical tests, magnetic resonance imaging (MRI), positron emission tomography (PET), and cerebrospinal fluid (CSF) biomarkers in a multicenter setting; (2) elucidation of the patterns and rates of change of imaging and CSF biomarker measurements in control subjects, MCI patients, and AD patients. CSF biomarkers are largely consistent with disease trajectories predicted by β-amyloid cascade (Hardy, J Alzheimer's Dis 2006;9(Suppl 3):151-3) and tau-mediated neurodegeneration hypotheses for AD, whereas brain atrophy and hypometabolism levels show predicted patterns but exhibit differing rates of change depending on region and disease severity; (3) the assessment of alternative methods of diagnostic categorization. Currently, the best classifiers select and combine optimum features from multiple modalities, including MRI, [(18)F]-fluorodeoxyglucose-PET, amyloid PET, CSF biomarkers, and clinical tests; (4) the development of blood biomarkers for AD as potentially noninvasive and low-cost alternatives to CSF biomarkers for AD diagnosis and the assessment of α-syn as an additional biomarker; (5) the development of methods for the early detection of AD. CSF biomarkers,

  9. Predicting episodic memory performance using different biomarkers: results from Argentina-Alzheimer’s Disease Neuroimaging Initiative

    PubMed Central

    Russo, María Julieta; Cohen, Gabriela; Chrem Mendez, Patricio; Campos, Jorge; Nahas, Federico E; Surace, Ezequiel I; Vazquez, Silvia; Gustafson, Deborah; Guinjoan, Salvador; Allegri, Ricardo F; Sevlever, Gustavo

    2016-01-01

    Purpose Argentina-Alzheimer’s Disease Neuroimaging Initiative (Arg-ADNI) is the first ADNI study to be performed in Latin America at a medical center with the appropriate infrastructure. Our objective was to describe baseline characteristics and to examine whether biomarkers related to Alzheimer’s disease (AD) physiopathology were associated with worse memory performance. Patients and methods Fifteen controls and 28 mild cognitive impairment and 13 AD dementia subjects were included. For Arg-ADNI, all biomarker parameters and neuropsychological tests of ADNI-II were adopted. Results of positron emission tomography (PET) with fluorodeoxyglucose and 11C-Pittsburgh compound-B (PIB-PET) were available from all participants. Cerebrospinal fluid biomarker results were available from 39 subjects. Results A total of 56 participants were included and underwent baseline evaluation. The three groups were similar with respect to years of education and sex, and they differed in age (F=5.10, P=0.01). Mean scores for the baseline measurements of the neuropsychological evaluation differed significantly among the three groups at P<0.001, showing a continuum in their neuropsychological performance. No significant correlations were found between the principal measures (long-delay recall, C-Pittsburgh compound-B scan, left hippocampal volume, and APOEε4) and either age, sex, or education (P>0.1). Baseline amyloid deposition and left hippocampal volume separated the three diagnostic groups and correlated with the memory performance (P<0.001). Conclusion Cross-sectional analysis of baseline data revealed links between cognition, structural changes, and biomarkers. Follow-up of a larger and more representative cohort, particularly analyzing cerebrospinal fluid and brain biomarkers, will allow better characterization of AD in our country.

  10. Predicting episodic memory performance using different biomarkers: results from Argentina-Alzheimer’s Disease Neuroimaging Initiative

    PubMed Central

    Russo, María Julieta; Cohen, Gabriela; Chrem Mendez, Patricio; Campos, Jorge; Nahas, Federico E; Surace, Ezequiel I; Vazquez, Silvia; Gustafson, Deborah; Guinjoan, Salvador; Allegri, Ricardo F; Sevlever, Gustavo

    2016-01-01

    Purpose Argentina-Alzheimer’s Disease Neuroimaging Initiative (Arg-ADNI) is the first ADNI study to be performed in Latin America at a medical center with the appropriate infrastructure. Our objective was to describe baseline characteristics and to examine whether biomarkers related to Alzheimer’s disease (AD) physiopathology were associated with worse memory performance. Patients and methods Fifteen controls and 28 mild cognitive impairment and 13 AD dementia subjects were included. For Arg-ADNI, all biomarker parameters and neuropsychological tests of ADNI-II were adopted. Results of positron emission tomography (PET) with fluorodeoxyglucose and 11C-Pittsburgh compound-B (PIB-PET) were available from all participants. Cerebrospinal fluid biomarker results were available from 39 subjects. Results A total of 56 participants were included and underwent baseline evaluation. The three groups were similar with respect to years of education and sex, and they differed in age (F=5.10, P=0.01). Mean scores for the baseline measurements of the neuropsychological evaluation differed significantly among the three groups at P<0.001, showing a continuum in their neuropsychological performance. No significant correlations were found between the principal measures (long-delay recall, C-Pittsburgh compound-B scan, left hippocampal volume, and APOEε4) and either age, sex, or education (P>0.1). Baseline amyloid deposition and left hippocampal volume separated the three diagnostic groups and correlated with the memory performance (P<0.001). Conclusion Cross-sectional analysis of baseline data revealed links between cognition, structural changes, and biomarkers. Follow-up of a larger and more representative cohort, particularly analyzing cerebrospinal fluid and brain biomarkers, will allow better characterization of AD in our country. PMID:27695331

  11. The Alzheimer’s Disease Neuroimaging Initiative Informatics Core: A Decade in Review

    PubMed Central

    Toga, Arthur W.; Crawford, Karen L.

    2015-01-01

    The Informatics Core of the Alzheimer’s Diseases Neuroimaging Initiative (ADNI) has coordinated data integration and dissemination for a continually growing and complex dataset in which both data contributors and recipients span institutions, scientific disciplines and geographic boundaries. This article provides an update on the accomplishments and future plans. PMID:26194316

  12. The Alzheimer's Disease Neuroimaging Initiative: A review of papers published since its inception

    PubMed Central

    Weiner, Michael W.; Veitch, Dallas P.; Aisen, Paul S.; Beckett, Laurel A.; Cairns, Nigel J.; Green, Robert C.; Harvey, Danielle; Jack, Clifford R.; Jagust, William; Liu, Enchi; Morris, John C.; Petersen, Ronald C.; Saykin, Andrew J.; Schmidt, Mark E.; Shaw, Leslie; Shen, Li; Siuciak, Judith A.; Soares, Holly; Toga, Arthur W.; Trojanowski, John Q.

    2014-01-01

    The Alzheimer's Disease Neuroimaging Initiative (ADNI) is an ongoing, longitudinal, multicenter study designed to develop clinical, imaging, genetic, and biochemical biomarkers for the early detection and tracking of Alzheimer's disease (AD). The study aimed to enroll 400 subjects with early mild cognitive impairment (MCI), 200 subjects with early AD, and 200 normal control subjects; $67 million funding was provided by both the public and private sectors, including the National Institute on Aging, 13 pharmaceutical companies, and 2 foundations that provided support through the Foundation for the National Institutes of Health. This article reviews all papers published since the inception of the initiative and summarizes the results as of February 2011. The major accomplishments of ADNI have been as follows: (1) the development of standardized methods for clinical tests, magnetic resonance imaging (MRI), positron emission tomography (PET), and cerebrospinal fluid (CSF) biomarkers in a multicenter setting; (2) elucidation of the patterns and rates of change of imaging and CSF biomarker measurements in control subjects, MCI patients, and AD patients. CSF biomarkers are consistent with disease trajectories predicted by β-amyloid cascade (Hardy, J Alzheimers Dis 2006;9(Suppl 3):151–3) and tau-mediated neurodegeneration hypotheses for AD, whereas brain atrophy and hypometabolism levels show predicted patterns but exhibit differing rates of change depending on region and disease severity; (3) the assessment of alternative methods of diagnostic categorization. Currently, the best classifiers combine optimum features from multiple modalities, including MRI, [18F]-fluorodeoxyglucose-PET, CSF biomarkers, and clinical tests; (4) the development of methods for the early detection of AD. CSF biomarkers, β-amyloid 42 and tau, as well as amyloid PET may reflect the earliest steps in AD pathology in mildly symptomatic or even nonsymptomatic subjects, and are leading candidates

  13. The Alzheimer’s Disease Neuroimaging Initiative: A review of papers published since its inception

    PubMed Central

    Weiner, Michael W.; Veitch, Dallas P.; Aisen, Paul S.; Beckett, Laurel A.; Cairns, Nigel J.; Green, Robert C.; Harvey, Danielle; Jack, Clifford R.; Jagust, William; Liu, Enchi; Morris, John C.; Petersen, Ronald C.; Saykin, Andrew J.; Schmidt, Mark E.; Shaw, Leslie; Siuciak, Judith A.; Soares, Holly; Toga, Arthur W.; Trojanowski, John Q.

    2012-01-01

    The Alzheimer’s Disease Neuroimaging Initiative (ADNI) is an ongoing, longitudinal, multicenter study designed to develop clinical, imaging, genetic and biochemical biomarkers for the early detection and tracking of Alzheimer’s disease (AD). The study aimed to enroll 400 subjects with early mild cognitive impairment (MCI), 200 subjects with early AD and 200 normal controls and $67 million funding was provided by both the public and private sectors including the National Institutes on Aging, thirteen pharmaceutical companies and two Foundations that provided support through the Foundation for NIH (FNIH). This article reviews all papers published since the inception of the initiative and summarizes the results as of February, 2011. The major accomplishments of ADNI have been 1) the development of standardized methods for clinical, magnetic resonance imaging (MRI) and positron emission tomography (PET) and cerebrospinal fluid (CSF) biomarkers in a multi-center setting; 2) elucidation of the patterns and rates of change of imaging and CSF biomarker measurements in control, MCI and AD patients. CSF biomarkers are consistent with disease trajectories predicted by β amyloid (Aβ) cascade [1] and tau mediated neurodegeneration hypotheses for AD while brain atrophy and hypometabolism levels show predicted patterns but exhibit differing rates of change depending on region and disease severity; 3) the assessment of alternative methods of diagnostic categorization. Currently, the best classifiers combine optimum features from multiple modalities including MRI, FDG-PET, CSF biomarkers and clinical tests; 4) the development of methods for the early detection of AD. CSF biomarkers, Aβ42 and tau as well as amyloid PET may reflect the earliest steps in AD pathology in mildly or even non-symptomatic subjects and are leading candidates for the detection of AD in its preclinical stages; 5) the improvement of clinical trial efficiency through the identification of subjects most

  14. Update on the magnetic resonance imaging core of the Alzheimer's disease neuroimaging initiative.

    PubMed

    Jack, Clifford R; Bernstein, Matt A; Borowski, Bret J; Gunter, Jeffrey L; Fox, Nick C; Thompson, Paul M; Schuff, Norbert; Krueger, Gunnar; Killiany, Ronald J; Decarli, Charles S; Dale, Anders M; Carmichael, Owen W; Tosun, Duygu; Weiner, Michael W

    2010-05-01

    Functions of the Alzheimer's Disease Neuroimaging Initiative (ADNI) magnetic resonance imaging (MRI) core fall into three categories: (1) those of the central MRI core laboratory at Mayo Clinic, Rochester, Minnesota, needed to generate high quality MRI data in all subjects at each time point; (2) those of the funded ADNI MRI core imaging analysis groups responsible for analyzing the MRI data; and (3) the joint function of the entire MRI core in designing and problem solving MR image acquisition, pre-processing, and analyses methods. The primary objective of ADNI was and continues to be improving methods for clinical trials in Alzheimer's disease. Our approach to the present ("ADNI-GO") and future ("ADNI-2," if funded) MRI protocol will be to maintain MRI methodological consistency in the previously enrolled "ADNI-1" subjects who are followed up longitudinally in ADNI-GO and ADNI-2. We will modernize and expand the MRI protocol for all newly enrolled ADNI-GO and ADNI-2 subjects. All newly enrolled subjects will be scanned at 3T with a core set of three sequence types: 3D T1-weighted volume, FLAIR, and a long TE gradient echo volumetric acquisition for micro hemorrhage detection. In addition to this core ADNI-GO and ADNI-2 protocol, we will perform vendor-specific pilot sub-studies of arterial spin-labeling perfusion, resting state functional connectivity, and diffusion tensor imaging. One of these sequences will be added to the core protocol on systems from each MRI vendor. These experimental sub-studies are designed to demonstrate the feasibility of acquiring useful data in a multicenter (but single vendor) setting for these three emerging MRI applications.

  15. Alzheimer's Disease Neuroimaging Initiative biomarkers as quantitative phenotypes: Genetics core aims, progress, and plans.

    PubMed

    Saykin, Andrew J; Shen, Li; Foroud, Tatiana M; Potkin, Steven G; Swaminathan, Shanker; Kim, Sungeun; Risacher, Shannon L; Nho, Kwangsik; Huentelman, Matthew J; Craig, David W; Thompson, Paul M; Stein, Jason L; Moore, Jason H; Farrer, Lindsay A; Green, Robert C; Bertram, Lars; Jack, Clifford R; Weiner, Michael W

    2010-05-01

    The role of the Alzheimer's Disease Neuroimaging Initiative Genetics Core is to facilitate the investigation of genetic influences on disease onset and trajectory as reflected in structural, functional, and molecular imaging changes; fluid biomarkers; and cognitive status. Major goals include (1) blood sample processing, genotyping, and dissemination, (2) genome-wide association studies (GWAS) of longitudinal phenotypic data, and (3) providing a central resource, point of contact and planning group for genetics within the Alzheimer's Disease Neuroimaging Initiative. Genome-wide array data have been publicly released and updated, and several neuroimaging GWAS have recently been reported examining baseline magnetic resonance imaging measures as quantitative phenotypes. Other preliminary investigations include copy number variation in mild cognitive impairment and Alzheimer's disease and GWAS of baseline cerebrospinal fluid biomarkers and longitudinal changes on magnetic resonance imaging. Blood collection for RNA studies is a new direction. Genetic studies of longitudinal phenotypes hold promise for elucidating disease mechanisms and risk, development of therapeutic strategies, and refining selection criteria for clinical trials. PMID:20451875

  16. Alzheimer’s Disease Neuroimaging Initiative biomarkers as quantitative phenotypes: Genetics core aims, progress, and plans

    PubMed Central

    Saykin, Andrew J.; Shen, Li; Foroud, Tatiana M.; Potkin, Steven G.; Swaminathan, Shanker; Kim, Sungeun; Risacher, Shannon L.; Nho, Kwangsik; Huentelman, Matthew J.; Craig, David W.; Thompson, Paul M.; Stein, Jason L.; Moore, Jason H.; Farrer, Lindsay A.; Green, Robert C.; Bertram, Lars; Jack, Clifford R.; Weiner, Michael W.

    2010-01-01

    The role of the Alzheimer’s Disease Neuroimaging Initiative Genetics Core is to facilitate the investigation of genetic influences on disease onset and trajectory as reflected in structural, functional, and molecular imaging changes; fluid biomarkers; and cognitive status. Major goals include (1) blood sample processing, genotyping, and dissemination, (2) genome-wide association studies (GWAS) of longitudinal phenotypic data, and (3) providing a central resource, point of contact and planning group for genetics within Alzheimer’s Disease Neuroimaging Initiative. Genome-wide array data have been publicly released and updated, and several neuroimaging GWAS have recently been reported examining baseline magnetic resonance imaging measures as quantitative phenotypes. Other preliminary investigations include copy number variation in mild cognitive impairment and Alzheimer’s disease and GWAS of baseline cerebrospinal fluid biomarkers and longitudinal changes on magnetic resonance imaging. Blood collection for RNA studies is a new direction. Genetic studies of longitudinal phenotypes hold promise for elucidating disease mechanisms and risk, development of therapeutic strategies, and refining selection criteria for clinical trials. PMID:20451875

  17. Development and assessment of a composite score for memory in the Alzheimer’s Disease Neuroimaging Initiative (ADNI)

    PubMed Central

    Carle, Adam; Gibbons, Laura E.; Insel, Philip; Mackin, R. Scott; Gross, Alden; Jones, Richard N.; Mukherjee, Shubhabrata; Curtis, S. McKay; Harvey, Danielle; Weiner, Michael; Mungas, Dan

    2013-01-01

    We sought to develop and evaluate a composite memory score from the neuropsychological battery used in the Alzheimer’s Disease (AD) Neuroimaging Initiative (ADNI). We used modern psychometric approaches to analyze longitudinal Rey Auditory Verbal Learning Test (RAVLT, 2 versions), AD Assessment Schedule - Cognition (ADAS-Cog, 3 versions), Mini-Mental State Examination (MMSE), and Logical Memory data to develop ADNI-Mem, a composite memory score. We compared RAVLT and ADAS-Cog versions, and compared ADNI-Mem to AVLT recall sum scores, four ADAS-Cog-derived scores, the MMSE, and the Clinical Dementia Rating Sum of Boxes. We evaluated rates of decline in normal cognition, mild cognitive impairment (MCI), and AD, ability to predict conversion from MCI to AD, strength of association with selected imaging parameters, and ability to differentiate rates of decline between participants with and without AD cerebrospinal fluid (CSF) signatures. The second version of the RAVLT was harder than the first. The ADAS-Cog versions were of similar difficulty. ADNI-Mem was slightly better at detecting change than total RAVLT recall scores. It was as good as or better than all of the other scores at predicting conversion from MCI to AD. It was associated with all our selected imaging parameters for people with MCI and AD. Participants with MCI with an AD CSF signature had somewhat more rapid decline than did those without. This paper illustrates appropriate methods for addressing the different versions of word lists, and demonstrates the additional power to be gleaned with a psychometrically sound composite memory score. PMID:22782295

  18. The Alzheimer's disease neuroimaging initiative: perspectives of the Industry Scientific Advisory Board.

    PubMed

    Schmidt, Mark E; Siemers, Eric; Snyder, Peter J; Potter, William Z; Cole, Patricia; Soares, Holly

    2010-05-01

    The Industry Scientific Advisory Board (ISAB) consists of representatives from the private companies and nonprofit foundations participating as sponsors of Alzheimer's Disease Neuroimaging Initiative (ADNI). Currently 21 companies are represented including pharmaceutical, imaging, and biotech concerns, and two foundations including the Alzheimer's Association. ISAB members meet regularly by teleconference or face-to-face at ADNI meetings and participate in the ADNI Core groups, all administered and organized by the Foundation for the National Institutes of Health. ISAB 'deliverables' include dissemination of information to sponsors, assisting in scientific review of protocols and results, initiation and consideration of "add-on" studies and analyses, and generation of consensus positions on industry priorities and concerns. Although positioned as an advisory body, ISAB also actively contributes to the ADNI mission of identifying biomarkers of disease progression.

  19. Development and Evaluation of a Multiplexed Mass Spectrometry-Based Assay for Measuring Candidate Peptide Biomarkers in Alzheimer’s Disease Neuroimaging Initiative (ADNI) CSF

    PubMed Central

    Spellman, Daniel S.; Wildsmith, Kristin R.; Honigberg, Lee A.; Tuefferd, Marianne; Baker, David; Raghavan, Nandini; Nairn, Angus C.; Croteau, Pascal; Schirm, Michael; Allard, Rene; Lamontagne, Julie; Chelsky, Daniel; Hoffmann, Steven; Potter, William Z.

    2015-01-01

    Purpose We describe the outcome of the Biomarkers Consortium CSF Proteomics Project, a public-private partnership of government, academia, non-profit, and industry. The goal of this study was to evaluate a multiplexed mass spectrometry-based approach for the qualification of candidate Alzheimer’s Disease (AD) biomarkers using CSF samples from the AD Neuroimaging Initiative (ADNI). Experimental Design Reproducibility of sample processing, analytic variability, and ability to detect a variety of analytes of interest were thoroughly investigated. Multiple approaches to statistical analyses assessed whether panel analytes were associated with baseline pathology (MCI, AD) vs. Healthy Controls (CN) or associated with progression for MCI patients, and included: (i) univariate association analyses, (ii) univariate prediction models, (iii) exploratory multivariate analyses, and (iv) supervised multivariate analysis. Results A robust targeted mass spectrometry-based approach for the qualification of candidate AD biomarkers was developed. The results identified several peptides with potential diagnostic or predictive utility, with the most significant differences observed for the following peptides for differentiating (including peptides from Hemoglobin A (HBA), Hemoglobin B (HBB), and Superoxide dismutase (SODE)) or predicting (including peptides from Neuronal pentraxin-2 (NPTX2), Neurosecretory protein VGF (VGF), and Secretogranin-2 (SCG2)) progression vs. non-progression from mild cognitive impairment to AD. Conclusions and Clinical Relevance These data provide potential insights into the biology of CSF in AD and MCI progression and provide a novel tool for AD researchers and clinicians working to improve diagnostic accuracy, evaluation of treatment efficacy, and early diagnosis. PMID:25676562

  20. Genetic influence of apolipoprotein E4 genotype on hippocampal morphometry: An N = 725 surface-based Alzheimer's disease neuroimaging initiative study.

    PubMed

    Shi, Jie; Leporé, Natasha; Gutman, Boris A; Thompson, Paul M; Baxter, Leslie C; Caselli, Richard J; Wang, Yalin

    2014-08-01

    The apolipoprotein E (APOE) e4 allele is the most prevalent genetic risk factor for Alzheimer's disease (AD). Hippocampal volumes are generally smaller in AD patients carrying the e4 allele compared to e4 noncarriers. Here we examined the effect of APOE e4 on hippocampal morphometry in a large imaging database-the Alzheimer's Disease Neuroimaging Initiative (ADNI). We automatically segmented and constructed hippocampal surfaces from the baseline MR images of 725 subjects with known APOE genotype information including 167 with AD, 354 with mild cognitive impairment (MCI), and 204 normal controls. High-order correspondences between hippocampal surfaces were enforced across subjects with a novel inverse consistent surface fluid registration method. Multivariate statistics consisting of multivariate tensor-based morphometry (mTBM) and radial distance were computed for surface deformation analysis. Using Hotelling's T(2) test, we found significant morphological deformation in APOE e4 carriers relative to noncarriers in the entire cohort as well as in the nondemented (pooled MCI and control) subjects, affecting the left hippocampus more than the right, and this effect was more pronounced in e4 homozygotes than heterozygotes. Our findings are consistent with previous studies that showed e4 carriers exhibit accelerated hippocampal atrophy; we extend these findings to a novel measure of hippocampal morphometry. Hippocampal morphometry has significant potential as an imaging biomarker of early stage AD.

  1. ANIMA: A data-sharing initiative for neuroimaging meta-analyses.

    PubMed

    Reid, Andrew T; Bzdok, Danilo; Genon, Sarah; Langner, Robert; Müller, Veronika I; Eickhoff, Claudia R; Hoffstaedter, Felix; Cieslik, Edna-Clarisse; Fox, Peter T; Laird, Angela R; Amunts, Katrin; Caspers, Svenja; Eickhoff, Simon B

    2016-01-01

    Meta-analytic techniques allow cognitive neuroscientists to pool large amounts of data across many individual task-based functional neuroimaging experiments. These methods have been aided by the introduction of online databases such as Brainmap.org or Neurosynth.org, which collate peak activation coordinates obtained from thousands of published studies. Findings from meta-analytic studies typically include brain regions which are consistently activated across studies for specific contrasts, investigating cognitive or clinical hypotheses. These regions can be subsequently used as the basis for seed-based connectivity analysis, or formally compared to neuroimaging data in order to help interpret new findings. To facilitate such approaches, we have developed a new online repository of meta-analytic neuroimaging results, named the Archive of Neuroimaging Meta-analyses (ANIMA). The ANIMA platform consists of an intuitive online interface for querying, downloading, and contributing data from published meta-analytic studies. Additionally, to aid the process of organizing, visualizing, and working with these data, we present an open-source desktop application called Volume Viewer. Volume Viewer allows users to easily arrange imaging data into composite stacks, and save these sessions as individual files, which can also be uploaded to the ANIMA database. The application also allows users to perform basic functions, such as computing conjunctions between images, or extracting regions-of-interest or peak coordinates for further analysis. The introduction of this new resource will enhance the ability of researchers to both share their findings and incorporate existing meta-analytic results into their own research. PMID:26231246

  2. Vascular and Alzheimer's disease markers independently predict brain atrophy rate in Alzheimer's Disease Neuroimaging Initiative controls.

    PubMed

    Barnes, Josephine; Carmichael, Owen T; Leung, Kelvin K; Schwarz, Christopher; Ridgway, Gerard R; Bartlett, Jonathan W; Malone, Ian B; Schott, Jonathan M; Rossor, Martin N; Biessels, Geert Jan; DeCarli, Charlie; Fox, Nick C

    2013-08-01

    This study assessed relationships among white matter hyperintensities (WMH), cerebrospinal fluid (CSF), Alzheimer's disease (AD) pathology markers, and brain volume loss. Subjects included 197 controls, 331 individuals with mild cognitive impairment (MCI), and 146 individuals with AD with serial volumetric 1.5-T MRI. CSF Aβ1-42 (n = 351) and tau (n = 346) were measured. Brain volume change was quantified using the boundary shift integral (BSI). We assessed the association between baseline WMH volume and annualized BSI, adjusting for intracranial volume. We also performed multiple regression analyses in the CSF subset, assessing the relationships of WMH and Aβ1-42 and/or tau with BSI. WMH burden was positively associated with BSI in controls (p = 0.02) but not MCI or AD. In multivariable models, WMH (p = 0.003) and Aβ1-42 (p = 0.001) were independently associated with BSI in controls; in MCI Aβ1-42 (p < 0.001) and tau (p = 0.04) were associated with BSI. There was no evidence of independent effects of WMH or CSF measures on BSI in AD. These data support findings that vascular damage is associated with increased brain atrophy in the context of AD pathology in pre-dementia stages.

  3. Clinical neuroimaging

    SciTech Connect

    Theodore, W.H.

    1988-01-01

    This book contains chapters on neuroimaging. Included are the following chapters: diagnostic neuroimaging in stroke, position emission tomography in cerebrovascular disease: clinical applications, and neuroradiologic work-up of brain tumors.

  4. Genome-wide pathway analysis of memory impairment in the Alzheimer's Disease Neuroimaging Initiative (ADNI) cohort implicates gene candidates, canonical pathways, and networks.

    PubMed

    Ramanan, Vijay K; Kim, Sungeun; Holohan, Kelly; Shen, Li; Nho, Kwangsik; Risacher, Shannon L; Foroud, Tatiana M; Mukherjee, Shubhabrata; Crane, Paul K; Aisen, Paul S; Petersen, Ronald C; Weiner, Michael W; Saykin, Andrew J

    2012-12-01

    Memory deficits are prominent features of mild cognitive impairment (MCI) and Alzheimer's disease (AD). The genetic architecture underlying these memory deficits likely involves the combined effects of multiple genetic variants operative within numerous biological pathways. In order to identify functional pathways associated with memory impairment, we performed a pathway enrichment analysis on genome-wide association data from 742 Alzheimer's Disease Neuroimaging Initiative (ADNI) participants. A composite measure of memory was generated as the phenotype for this analysis by applying modern psychometric theory to item-level data from the ADNI neuropsychological test battery. Using the GSA-SNP software tool, we identified 27 canonical, expertly-curated pathways with enrichment (FDR-corrected p-value < 0.05) against this composite memory score. Processes classically understood to be involved in memory consolidation, such as neurotransmitter receptor-mediated calcium signaling and long-term potentiation, were highly represented among the enriched pathways. In addition, pathways related to cell adhesion, neuronal differentiation and guided outgrowth, and glucose- and inflammation-related signaling were also enriched. Among genes that were highly-represented in these enriched pathways, we found indications of coordinated relationships, including one large gene set that is subject to regulation by the SP1 transcription factor, and another set that displays co-localized expression in normal brain tissue along with known AD risk genes. These results 1) demonstrate that psychometrically-derived composite memory scores are an effective phenotype for genetic investigations of memory impairment and 2) highlight the promise of pathway analysis in elucidating key mechanistic targets for future studies and for therapeutic interventions. PMID:22865056

  5. Cognitive reserve and Aβ1-42 in mild cognitive impairment (Argentina-Alzheimer’s Disease Neuroimaging Initiative)

    PubMed Central

    Harris, Paula; Fernandez Suarez, Marcos; Surace, Ezequiel I; Chrem Méndez, Patricio; Martín, María Eugenia; Clarens, María Florencia; Tapajóz, Fernanda; Russo, Maria Julieta; Campos, Jorge; Guinjoan, Salvador M; Sevlever, Gustavo; Allegri, Ricardo F

    2015-01-01

    Background The purpose of this study was to investigate the relationship between cognitive reserve and concentration of Aβ1-42 in the cerebrospinal fluid (CSF) of patients with mild cognitive impairment, those with Alzheimer’s disease, and in control subjects. Methods Thirty-three participants from the Argentina-Alzheimer’s Disease Neuroimaging Initiative database completed a cognitive battery, the Cognitive Reserve Questionnaire (CRQ), and an Argentinian accentuation reading test (TAP-BA) as a measure of premorbid intelligence, and underwent lumbar puncture for CSF biomarker quantification. Results The CRQ significantly correlated with TAP-BA, education, and Aβ1-42. When considering Aβ1-42 levels, significant differences were found in CRQ scores; higher levels of CSF Aβ1-42 were associated with higher CRQ scores. Conclusion Reduced Aβ1-42 in CSF is considered as evidence of amyloid deposition in the brain. Previous results suggest that individuals with higher education, higher occupational attainment, and participation in leisure activities (cognitive reserve) have a reduced risk of developing Alzheimer’s disease. Our results support the notion that enhanced neural activity has a protective role in mild cognitive impairment, as evidenced by higher CSF Aβ1-42 levels in individuals with more cognitive reserve. PMID:26504392

  6. Neuropathologic assessment of participants in two multi-center longitudinal observational studies: the Alzheimer Disease Neuroimaging Initiative (ADNI) and the Dominantly Inherited Alzheimer Network (DIAN).

    PubMed

    Cairns, Nigel J; Perrin, Richard J; Franklin, Erin E; Carter, Deborah; Vincent, Benjamin; Xie, Mingqiang; Bateman, Randall J; Benzinger, Tammie; Friedrichsen, Karl; Brooks, William S; Halliday, Glenda M; McLean, Catriona; Ghetti, Bernardino; Morris, John C

    2015-08-01

    It has been hypothesized that the relatively rare autosomal dominant Alzheimer disease (ADAD) may be a useful model of the more frequent, sporadic, late-onset AD (LOAD). Individuals with ADAD have a predictable age at onset and the biomarker profile of ADAD participants in the preclinical stage may be used to predict disease progression and clinical onset. However, the extent to which the pathogenesis and neuropathology of ADAD overlaps with that of LOAD is equivocal. To address this uncertainty, two multicenter longitudinal observational studies, the Alzheimer Disease Neuroimaging Initiative (ADNI) and the Dominantly Inherited Alzheimer Network (DIAN), leveraged the expertise and resources of the existing Knight Alzheimer Disease Research Center (ADRC) at Washington University School of Medicine, St. Louis, Missouri, USA, to establish a Neuropathology Core (NPC). The ADNI/DIAN-NPC is systematically examining the brains of all participants who come to autopsy at the 59 ADNI sites in the USA and Canada and the 14 DIAN sites in the USA (eight), Australia (three), UK (one) and Germany (two). By 2014, 41 ADNI and 24 DIAN autopsies (involving nine participants and 15 family members) had been performed. The autopsy rate in the ADNI cohort in the most recent year was 93% (total since NPC inception: 70%). In summary, the ADNI/DIAN NPC has implemented a standard protocol for all sites to solicit permission for brain autopsy and to send brain tissue to the NPC for a standardized, uniform and state-of-the-art neuropathologic assessment. The benefit to ADNI and DIAN of the implementation of the NPC is very clear. The NPC provides final "gold standard" neuropathological diagnoses and data against which the antecedent observations and measurements of ADNI and DIAN can be compared.

  7. Soluble BACE-1 Activity and sAβPPβ Concentrations in Alzheimer's Disease and Age-Matched Healthy Control Cerebrospinal Fluid from the Alzheimer's Disease Neuroimaging Initiative-1 Baseline Cohort.

    PubMed

    Savage, Mary J; Holder, Daniel J; Wu, Guoxin; Kaplow, June; Siuciak, Judith A; Potter, William Z

    2015-01-01

    β-site amyloid precursor protein-cleaving enzyme 1 (BACE1) plays an important role in the development of Alzheimer's disease (AD), freeing the amyloid-β (Aβ) N-terminus from the amyloid-β protein precursor (AβPP), the first step in Aβ formation. Increased BACE1 activity in AD brain or cerebrospinal fluid (CSF) has been reported. Other studies, however, found either no change or a decrease with AD diagnosis in either BACE1 activity or sAβPPβ, the N-terminal secreted product of BACE1 (sBACE1) activity on AβPP. Here, sBACE1 enzymatic activity and secreted AβPPβ (sAβPPβ) were measured in Alzheimer's Disease Neuroimaging Initiative-1 (ADNI-1) baseline CSF samples and no statistically significant changes were found in either measure comparing healthy control, mild cognitively impaired, or AD individual samples. While CSF sBACE1 activity and sAβPPβ demonstrated a moderate yet significant degree of correlation with each other, there was no correlation of either analyte to CSF Aβ peptide ending at residue 42. Surprisingly, a stronger correlation was demonstrated between CSF sBACE1 activity and tau, which was comparable to that between CSF Aβ₄₂ and tau. Unlike for these latter two analytes, receiver-operator characteristic curves demonstrate that neither CSF sBACE1 activity nor sAβPPβ concentrations can be used to differentiate between healthy elderly and AD individuals.

  8. Soluble BACE-1 Activity and sAβPPβ Concentrations in Alzheimer's Disease and Age-Matched Healthy Control Cerebrospinal Fluid from the Alzheimer's Disease Neuroimaging Initiative-1 Baseline Cohort.

    PubMed

    Savage, Mary J; Holder, Daniel J; Wu, Guoxin; Kaplow, June; Siuciak, Judith A; Potter, William Z

    2015-01-01

    β-site amyloid precursor protein-cleaving enzyme 1 (BACE1) plays an important role in the development of Alzheimer's disease (AD), freeing the amyloid-β (Aβ) N-terminus from the amyloid-β protein precursor (AβPP), the first step in Aβ formation. Increased BACE1 activity in AD brain or cerebrospinal fluid (CSF) has been reported. Other studies, however, found either no change or a decrease with AD diagnosis in either BACE1 activity or sAβPPβ, the N-terminal secreted product of BACE1 (sBACE1) activity on AβPP. Here, sBACE1 enzymatic activity and secreted AβPPβ (sAβPPβ) were measured in Alzheimer's Disease Neuroimaging Initiative-1 (ADNI-1) baseline CSF samples and no statistically significant changes were found in either measure comparing healthy control, mild cognitively impaired, or AD individual samples. While CSF sBACE1 activity and sAβPPβ demonstrated a moderate yet significant degree of correlation with each other, there was no correlation of either analyte to CSF Aβ peptide ending at residue 42. Surprisingly, a stronger correlation was demonstrated between CSF sBACE1 activity and tau, which was comparable to that between CSF Aβ₄₂ and tau. Unlike for these latter two analytes, receiver-operator characteristic curves demonstrate that neither CSF sBACE1 activity nor sAβPPβ concentrations can be used to differentiate between healthy elderly and AD individuals. PMID:25790831

  9. Structural Neuroimaging Genetics Interactions in Alzheimer's Disease.

    PubMed

    Moon, Seok Woo; Dinov, Ivo D; Kim, Jaebum; Zamanyan, Alen; Hobel, Sam; Thompson, Paul M; Toga, Arthur W

    2015-01-01

    This article investigates late-onset cognitive impairment using neuroimaging and genetics biomarkers for Alzheimer's Disease Neuroimaging Initiative (ADNI) participants. Eight-hundred and eight ADNI subjects were identified and divided into three groups: 200 subjects with Alzheimer's disease (AD), 383 subjects with mild cognitive impairment (MCI), and 225 asymptomatic normal controls (NC). Their structural magnetic resonance imaging (MRI) data were parcellated using BrainParser, and the 80 most important neuroimaging biomarkers were extracted using the global shape analysis Pipeline workflow. Using Plink via the Pipeline environment, we obtained 80 SNPs highly-associated with the imaging biomarkers. In the AD cohort, rs2137962 was significantly associated bilaterally with changes in the hippocampi and the parahippocampal gyri, and rs1498853, rs288503, and rs288496 were associated with the left and right hippocampi, the right parahippocampal gyrus, and the left inferior temporal gyrus. In the MCI cohort, rs17028008 and rs17027976 were significantly associated with the right caudate and right fusiform gyrus, rs2075650 (TOMM40) was associated with the right caudate, and rs1334496 and rs4829605 were significantly associated with the right inferior temporal gyrus. In the NC cohort, Chromosome 15 [rs734854 (STOML1), rs11072463 (PML), rs4886844 (PML), and rs1052242 (PML)] was significantly associated with both hippocampi and both insular cortices, and rs4899412 (RGS6) was significantly associated with the caudate. We observed significant correlations between genetic and neuroimaging phenotypes in the 808 ADNI subjects. These results suggest that differences between AD, MCI, and NC cohorts may be examined by using powerful joint models of morphometric, imaging and genotypic data. PMID:26444770

  10. Effects of traumatic brain injury and posttraumatic stress disorder on Alzheimer's disease in veterans, using the Alzheimer's Disease Neuroimaging Initiative.

    PubMed

    Weiner, Michael W; Veitch, Dallas P; Hayes, Jacqueline; Neylan, Thomas; Grafman, Jordan; Aisen, Paul S; Petersen, Ronald C; Jack, Clifford; Jagust, William; Trojanowski, John Q; Shaw, Leslie M; Saykin, Andrew J; Green, Robert C; Harvey, Danielle; Toga, Arthur W; Friedl, Karl E; Pacifico, Anthony; Sheline, Yvette; Yaffe, Kristine; Mohlenoff, Brian

    2014-06-01

    Both traumatic brain injury (TBI) and posttraumatic stress disorder (PTSD) are common problems resulting from military service, and both have been associated with increased risk of cognitive decline and dementia resulting from Alzheimer's disease (AD) or other causes. This study aims to use imaging techniques and biomarker analysis to determine whether traumatic brain injury (TBI) and/or PTSD resulting from combat or other traumas increase the risk for AD and decrease cognitive reserve in Veteran subjects, after accounting for age. Using military and Department of Veterans Affairs records, 65 Vietnam War veterans with a history of moderate or severe TBI with or without PTSD, 65 with ongoing PTSD without TBI, and 65 control subjects are being enrolled in this study at 19 sites. The study aims to select subject groups that are comparable in age, gender, ethnicity, and education. Subjects with mild cognitive impairment (MCI) or dementia are being excluded. However, a new study just beginning, and similar in size, will study subjects with TBI, subjects with PTSD, and control subjects with MCI. Baseline measurements of cognition, function, blood, and cerebrospinal fluid biomarkers; magnetic resonance images (structural, diffusion tensor, and resting state blood-level oxygen dependent (BOLD) functional magnetic resonance imaging); and amyloid positron emission tomographic (PET) images with florbetapir are being obtained. One-year follow-up measurements will be collected for most of the baseline procedures, with the exception of the lumbar puncture, the PET imaging, and apolipoprotein E genotyping. To date, 19 subjects with TBI only, 46 with PTSD only, and 15 with TBI and PTSD have been recruited and referred to 13 clinics to undergo the study protocol. It is expected that cohorts will be fully recruited by October 2014. This study is a first step toward the design and statistical powering of an AD prevention trial using at-risk veterans as subjects, and provides the

  11. 76 FR 9329 - Efficiency Initiative Effort To Reduce Non-Value-Added Costs Imposed on Industry by Department of...

    Federal Register 2010, 2011, 2012, 2013, 2014

    2011-02-17

    ... Efficiency Initiative Effort To Reduce Non-Value-Added Costs Imposed on Industry by Department of Defense... overhead costs, but do not contribute to value added in systems and services delivered to the Department... information about some additional areas of non-value- added cost. Submissions should specifically...

  12. Neuroimaging in tuberculous meningitis.

    PubMed

    Garg, Ravindra Kumar; Malhotra, Hardeep Singh; Jain, Amita

    2016-01-01

    Tuberculous meningitis is a serious infection caused by Mycobacterium tuberculosis. Early diagnosis is the key to success of treatment. Neuroimaging plays a crucial role in the early and accurate diagnosis of tuberculous meningitis and its disabling complications. Magnetic resonance imaging is considered superior to computed tomography. Neuroimaging characteristics include leptomeningeal and basal cisternal enhancement, hydrocephalus, periventricular infarcts, and tuberculoma. Partially treated pyogenic meningitis, cryptococcal meningitis, viral encephalitis, carcinomatous, and lymphomatous meningitis may have many similar neuroimaging characteristics, and differentiation from tuberculous meningitis at times on the basis of neuroimaging characteristics becomes difficult. PMID:26954796

  13. Value-Added Predictors of Expressive and Receptive Language Growth in Initially Nonverbal Preschoolers with Autism Spectrum Disorders

    PubMed Central

    Watson, Linda R.; Lambert, Warren

    2015-01-01

    Eighty-seven preschoolers with autism spectrum disorders who were initially nonverbal (under 6 words in language sample and under 21 parent-reported words said) were assessed at five time points over 16 months. Statistical models that accounted for the intercorrelation among nine theoretically- and empirically-motivated predictors, as well as two background variables (i.e., cognitive impairment level, autism severity), were applied to identify value-added predictors of expressive and receptive spoken language growth and outcome. The results indicate that responding to joint attention, intentional communication, and parent linguistic responses were value-added predictors of both expressive and receptive spoken language growth. In addition, consonant inventory was a value-added predictor of expressive growth; early receptive vocabulary and autism severity were value-added predictors of receptive growth. PMID:25344152

  14. Neuroimaging of the Philadelphia Neurodevelopmental Cohort

    PubMed Central

    Satterthwaite, Theodore D.; Elliott, Mark A.; Ruparel, Kosha; Loughead, James; Prabhakaran, Karthik; Calkins, Monica E.; Hopson, Ryan; Jackson, Chad; Keefe, Jack; Riley, Marisa; Mensh, Frank D.; Sleiman, Patrick; Verma, Ragini; Davatzikos, Christos; Hakonarson, Hakon; Gur, Ruben C.; Gur, Raquel E.

    2013-01-01

    The Philadelphia Neurodevelopmental Cohort (PNC) is a large-scale, NIMH funded initiative to understand how brain maturation mediates cognitive development and vulnerability to psychiatric illness, and understand how genetics impacts this process. As part of this study, 1,445 adolescents ages 8–21 at enrollment underwent multimodal neuroimaging. Here, we highlight the conceptual basis for the effort, the study design, and measures available in the dataset. We focus on neuroimaging measures obtained, including T1-weighted structural neuroimaging, diffusion tensor imaging, perfusion neuroimaging using arterial spin labeling, functional imaging tasks of working memory and emotion identification, and resting state imaging of functional connectivity. Furthermore, we provide characteristics regarding the final sample acquired. Finally, we describe mechanisms in place for data sharing that will allow the PNC to become a freely available public resource to advance our understanding of normal and pathological brain development. PMID:23921101

  15. Neuroimaging of epilepsy.

    PubMed

    Cendes, Fernando; Theodore, William H; Brinkmann, Benjamin H; Sulc, Vlastimil; Cascino, Gregory D

    2016-01-01

    Imaging is pivotal in the evaluation and management of patients with seizure disorders. Elegant structural neuroimaging with magnetic resonance imaging (MRI) may assist in determining the etiology of focal epilepsy and demonstrating the anatomical changes associated with seizure activity. The high diagnostic yield of MRI to identify the common pathological findings in individuals with focal seizures including mesial temporal sclerosis, vascular anomalies, low-grade glial neoplasms and malformations of cortical development has been demonstrated. Positron emission tomography (PET) is the most commonly performed interictal functional neuroimaging technique that may reveal a focal hypometabolic region concordant with seizure onset. Single photon emission computed tomography (SPECT) studies may assist performance of ictal neuroimaging in patients with pharmacoresistant focal epilepsy being considered for neurosurgical treatment. This chapter highlights neuroimaging developments and innovations, and provides a comprehensive overview of the imaging strategies used to improve the care and management of people with epilepsy. PMID:27430454

  16. [Neuroimaging of frontotemporal dementia].

    PubMed

    Blesa, R

    2000-01-01

    With the development of neuroimaging, frontal lobe atrophy has been demonstrated with increased frequency, first with structural studies (computed tomography and magnetic resonance imaging), then with functional images (Single photon emission computed tomography and Positron emission tomography).

  17. Functional neuroimaging in psychiatry.

    PubMed Central

    Fu, C H; McGuire, P K

    1999-01-01

    Functional neuroimaging is one of the most powerful means available for investigating the pathophysiology of psychiatric disorders. In this review, we shall focus on the different ways that it can be employed to this end, describing the major findings in the field in the context of different methodological approaches. We will also discuss practical issues that are particular to studying psychiatric disorders and the potential contribution of functional neuroimaging to future psychiatric research. PMID:10466156

  18. Type 2 diabetes and cognitive impairment: contributions from neuroimaging.

    PubMed

    Ryan, John P; Fine, David F; Rosano, Caterina

    2014-03-01

    Type 2 diabetes mellitus (T2D) and Alzheimer disease (AD) are major public health burdens associated with aging. As the age of the population rapidly increases, a sheer increase in the incidence of these diseases is expected. Research has identified T2D as a risk factor for cognitive impairment and potentially AD, but the neurobiological pathways that are affected are only beginning to be understood. The rapid advances in neuroimaging in the past decade have added significant understanding to how T2D affects brain structure and function and possibly lead to AD. This article provides a review of studies that have utilized structural and functional neuroimaging to identify neural pathways that link T2D to impaired cognitive performance and potentially AD. A primary focus of this article is the potential for neuroimaging to assist in understanding the mechanistic pathways that may provide translational opportunities for clinical intervention.

  19. Neuroimaging and Fetal Alcohol Spectrum Disorders

    ERIC Educational Resources Information Center

    Norman, Andria L.; Crocker, Nicole; Mattson, Sarah N.; Riley, Edward P.

    2009-01-01

    The detrimental effects of prenatal alcohol exposure on the developing brain include structural brain anomalies as well as cognitive and behavioral deficits. Initial neuroimaging studies of fetal alcohol spectrum disorders (FASD) using magnetic resonance imaging (MRI) confirmed previous autopsy reports of overall reduction in brain volume and…

  20. Rapid self-organised initiation of ad hoc sensor networks close above the percolation threshold

    NASA Astrophysics Data System (ADS)

    Korsnes, Reinert

    2010-07-01

    This work shows potentials for rapid self-organisation of sensor networks where nodes collaborate to relay messages to a common data collecting unit (sink node). The study problem is, in the sense of graph theory, to find a shortest path tree spanning a weighted graph. This is a well-studied problem where for example Dijkstra’s algorithm provides a solution for non-negative edge weights. The present contribution shows by simulation examples that simple modifications of known distributed approaches here can provide significant improvements in performance. Phase transition phenomena, which are known to take place in networks close to percolation thresholds, may explain these observations. An initial method, which here serves as reference, assumes the sink node starts organisation of the network (tree) by transmitting a control message advertising its availability for its neighbours. These neighbours then advertise their current cost estimate for routing a message to the sink. A node which in this way receives a message implying an improved route to the sink, advertises its new finding and remembers which neighbouring node the message came from. This activity proceeds until there are no more improvements to advertise to neighbours. The result is a tree network for cost effective transmission of messages to the sink (root). This distributed approach has potential for simple improvements which are of interest when minimisation of storage and communication of network information are a concern. Fast organisation of the network takes place when the number k of connections for each node ( degree) is close above its critical value for global network percolation and at the same time there is a threshold for the nodes to decide to advertise network route updates.

  1. Neuroimaging and Psychopharmacology

    ERIC Educational Resources Information Center

    Semrud-Clikeman, Margaret; Pliszka, Steve R.

    2005-01-01

    This review presents the most recent research concerning neuroimaging in developmental disabilities. Changes in structure and activation have been found in children with ADHD and learning disabilities, following intervention. For the children with learning disabilities changes in activation have been found following intensive behavioral and…

  2. Neuroimaging and Aggression.

    ERIC Educational Resources Information Center

    Mills, Shari; Raine, Adrian

    1994-01-01

    Brain imaging research allows direct assessment of structural and functional brain abnormalities, and thereby provides an improved methodology for studying neurobiological factors predisposing to violent and aggressive behavior. This paper reviews 20 brain imaging studies using four different types of neuroimaging techniques that were conducted in…

  3. Neuroimaging in epilepsy

    PubMed Central

    Bano, Shahina; Yadav, Sachchida Nand; Chaudhary, Vikas; Garga, Umesh Chandra

    2011-01-01

    Epilepsy is the most common neurological disease worldwide and is second only to stroke in causing neurological morbidity. Neuroimaging plays a very important role in the diagnosis and treatment of patients with epilepsy. This review article highlights the specific role of various imaging modalities in patients with epilepsy, and their practical applications in the management of epileptic patients. PMID:21977082

  4. Adding Once-Daily Lixisenatide for Type 2 Diabetes Inadequately Controlled With Newly Initiated and Continuously Titrated Basal Insulin Glargine

    PubMed Central

    Riddle, Matthew C.; Forst, Thomas; Aronson, Ronnie; Sauque-Reyna, Leobardo; Souhami, Elisabeth; Silvestre, Louise; Ping, Lin; Rosenstock, Julio

    2013-01-01

    OBJECTIVE When oral therapy for type 2 diabetes is ineffective, adding basal insulin improves glycemic control. However, when glycated hemoglobin (HbA1c) remains elevated because of postprandial hyperglycemia, the next therapeutic step is controversial. We examined the efficacy and safety of lixisenatide in patients with HbA1c still elevated after initiation of insulin glargine. RESEARCH DESIGN AND METHODS This double-blind, parallel-group trial enrolled patients with HbA1c 7–10% despite oral therapy. Insulin glargine was added and systematically titrated during a 12-week run-in, after which candidates with fasting glucose ≤7.8 mmol/L and HbA1c 7–9% were randomized to lixisenatide 20 µg or placebo for 24 weeks while insulin titration continued. The primary end point was HbA1c change after randomization. RESULTS The randomized population (n = 446) had mean diabetes duration of 9.2 years, BMI 31.8 kg/m2, and daily glargine dosage of 44 units. HbA1c had decreased during run-in from 8.6 to 7.6%; adding lixisenatide further reduced HbA1c by 0.71 vs. 0.40% with placebo (least squares mean difference, –0.32%; 95% CI, –0.46 to –0.17; P < 0.0001). More participants attained HbA1c <7% with lixisenatide (56 vs. 39%; P < 0.0001). Lixisenatide reduced plasma glucose 2 h after a standardized breakfast (difference vs. placebo –3.2 mmol/L; P < 0.0001) and had a favorable effect on body weight (difference vs. placebo –0.89 kg; P = 0.0012). Nausea, vomiting, and symptomatic hypoglycemia <3.3 mmol/L were more common with lixisenatide. CONCLUSIONS Adding lixisenatide to insulin glargine improved overall and postprandial hyperglycemia and deserves consideration as an alternative to prandial insulin for patients not reaching HbA1c goals with recently initiated basal insulin. PMID:23564915

  5. Retrospective study on structural neuroimaging in first-episode psychosis

    PubMed Central

    Silva-dos-Santos, Amilcar; Talina, Miguel Cotrim

    2016-01-01

    Background. No consensus between guidelines exists regarding neuroimaging in first-episode psychosis. The purpose of this study is to assess anomalies found in structural neuroimaging exams (brain computed tomography (CT) and magnetic resonance imaging (MRI)) in the initial medical work-up of patients presenting first-episode psychosis. Methods. The study subjects were 32 patients aged 18–48 years (mean age: 29.6 years), consecutively admitted with first-episode psychosis diagnosis. Socio-demographic and clinical data and neuroimaging exams (CT and MRI) were retrospectively studied. Diagnostic assessments were made using the Operational Criteria Checklist +. Neuroimaging images (CT and MRI) and respective reports were analysed by an experienced consultant psychiatrist. Results. None of the patients had abnormalities in neuroimaging exams responsible for psychotic symptoms. Thirty-seven percent of patients had incidental brain findings not causally related to the psychosis (brain atrophy, arachnoid cyst, asymmetric lateral ventricles, dilated lateral ventricles, plagiocephaly and falx cerebri calcification). No further medical referral was needed for any of these patients. No significant differences regarding gender, age, diagnosis, duration of untreated psychosis, in-stay and cannabis use were found between patients who had neuroimaging abnormalities versus those without. Discussion. This study suggests that structural neuroimaging exams reveal scarce abnormalities in young patients with first-episode psychosis. Structural neuroimaging is especially useful in first-episode psychosis patients with neurological symptoms, atypical clinical picture and old age. PMID:27257547

  6. Retrospective study on structural neuroimaging in first-episode psychosis.

    PubMed

    Coentre, Ricardo; Silva-Dos-Santos, Amilcar; Talina, Miguel Cotrim

    2016-01-01

    Background. No consensus between guidelines exists regarding neuroimaging in first-episode psychosis. The purpose of this study is to assess anomalies found in structural neuroimaging exams (brain computed tomography (CT) and magnetic resonance imaging (MRI)) in the initial medical work-up of patients presenting first-episode psychosis. Methods. The study subjects were 32 patients aged 18-48 years (mean age: 29.6 years), consecutively admitted with first-episode psychosis diagnosis. Socio-demographic and clinical data and neuroimaging exams (CT and MRI) were retrospectively studied. Diagnostic assessments were made using the Operational Criteria Checklist +. Neuroimaging images (CT and MRI) and respective reports were analysed by an experienced consultant psychiatrist. Results. None of the patients had abnormalities in neuroimaging exams responsible for psychotic symptoms. Thirty-seven percent of patients had incidental brain findings not causally related to the psychosis (brain atrophy, arachnoid cyst, asymmetric lateral ventricles, dilated lateral ventricles, plagiocephaly and falx cerebri calcification). No further medical referral was needed for any of these patients. No significant differences regarding gender, age, diagnosis, duration of untreated psychosis, in-stay and cannabis use were found between patients who had neuroimaging abnormalities versus those without. Discussion. This study suggests that structural neuroimaging exams reveal scarce abnormalities in young patients with first-episode psychosis. Structural neuroimaging is especially useful in first-episode psychosis patients with neurological symptoms, atypical clinical picture and old age. PMID:27257547

  7. [Functional neuroimaging of addiction].

    PubMed

    Takahashi, Hidehiko

    2015-09-01

    Positron emission tomography studies investigating dopamine release by drug or reward demonstrated blunted dopamine release in relation to addiction to psychostimulants such as cocaine and amphetamine. However, recent studies reported that nicotine and gambling addiction showed opposite results. Several factors such as illness stage or neurotoxicity of substances could be considered for this discrepancy. Behavioral addiction such as gambling disorder is a good target of neuroimaging because it is free from overt neurotoxicity. However, even in gambling disorder, the results of fMRI studies investigating neural response to reward are mixed. Neuroimaging together with taking the various backgrounds of patients into account should contribute not only to a better understanding of the neurobiology of addiction but also to the development of more effective and individually tailored treatment strategies for addiction. PMID:26394506

  8. Early neuroimaging diagnosis of Alzheimer's disease

    NASA Astrophysics Data System (ADS)

    Jiao, Jianling; Liu, Timon C.; Li, Yan; Liu, Songhao

    2002-04-01

    Neuroimaging has played an important role in evaluating the Alzheimer's disease (AD) patients, and its uses are growing. Magnetic resonance imaging (MRI) may show the presence of cerebral infarcts and white matter disease. Single photon emission computed tomography (SPECT) and positron emission tomography (PET), which visualize such cerebral functions as glucose metabolism and blood flow, may provide positive evidence to support the diagnosis of AD. Electrical impedance tomography (EIT) is a recently developed technique which enables the internal impedance of an object to be imaged noninvasively.

  9. Neuroimaging in Dementia

    PubMed Central

    Vitali, Paolo; Migliaccio, Raffaella; Agosta, Federica; Rosen, Howard J.; Geschwind, Michael D.

    2009-01-01

    Although dementia is a clinical diagnosis, neuroimaging often is crucial for proper assessment. Magnetic resonance imaging (MRI) and computed tomography (CT) may identify nondegenerative and potentially treatable causes of dementia. Recent neuroimaging advances, such as the Pittsburgh Compound-B (PIB) ligand for positron emission tomography imaging in Alzheimer’s disease, will improve our ability to differentiate among the neurodegenerative dementias. High-resolution volumetric MRI has increased the capacity to identify the various forms of the frontotemporal lobar degeneration spectrum and some forms of parkinsonism or cerebellar neurodegenerative disorders, such as corticobasal degeneration, progressive supranuclear palsy, multiple system atrophy, and spinocerebellar ataxias. In many cases, the specific pattern of cortical and subcortical abnormalities on MRI has diagnostic utility. Finally, among the new MRI methods, diffusion-weighted MRI can help in the early diagnosis of Creutzfeldt-Jakob disease. Although only clinical assessment can lead to a diagnosis of dementia, neuroimaging is clearly an invaluable tool for the clinician in the differential diagnosis. PMID:18843575

  10. Systematic Redaction for Neuroimage Data

    PubMed Central

    Matlock, Matt; Schimke, Nakeisha; Kong, Liang; Macke, Stephen; Hale, John

    2013-01-01

    In neuroscience, collaboration and data sharing are undermined by concerns over the management of protected health information (PHI) and personal identifying information (PII) in neuroimage datasets. The HIPAA Privacy Rule mandates measures for the preservation of subject privacy in neuroimaging studies. Unfortunately for the researcher, the management of information privacy is a burdensome task. Wide scale data sharing of neuroimages is challenging for three primary reasons: (i) A dearth of tools to systematically expunge PHI/PII from neuroimage data sets, (ii) a facility for tracking patient identities in redacted datasets has not been produced, and (iii) a sanitization workflow remains conspicuously absent. This article describes the XNAT Redaction Toolkit—an integrated redaction workflow which extends a popular neuroimage data management toolkit to remove PHI/PII from neuroimages. Quickshear defacing is also presented as a complementary technique for deidentifying the image data itself. Together, these tools improve subject privacy through systematic removal of PII/PHI. PMID:24179597

  11. A review of β-amyloid neuroimaging in Alzheimer's disease

    PubMed Central

    Adlard, Paul A.; Tran, Bob A.; Finkelstein, David I.; Desmond, Patricia M.; Johnston, Leigh A.; Bush, Ashley I.; Egan, Gary F.

    2014-01-01

    Alzheimer's disease (AD) is the most common cause of dementia worldwide. As advancing age is the greatest risk factor for developing AD, the number of those afflicted is expected to increase markedly with the aging of the world's population. The inability to definitively diagnose AD until autopsy remains an impediment to establishing effective targeted treatments. Neuroimaging has enabled in vivo visualization of pathological changes in the brain associated with the disease, providing a greater understanding of its pathophysiological development and progression. However, neuroimaging biomarkers do not yet offer clear advantages over current clinical diagnostic criteria for them to be accepted into routine clinical use. Nonetheless, current insights from neuroimaging combined with the elucidation of biochemical and molecular processes in AD are informing the ongoing development of new imaging techniques and their application. Much of this research has been greatly assisted by the availability of transgenic mouse models of AD. In this review we summarize the main efforts of neuroimaging in AD in humans and in mouse models, with a specific focus on β-amyloid, and discuss the potential of new applications and novel approaches. PMID:25400539

  12. Neuroimaging of Cognition

    PubMed Central

    Dolan, R.J.

    2009-01-01

    Neuroimaging, particularly that based upon functional magnetic resonance (fMRI), has become a dominant tool in cognitive neuroscience. This review provides a personal and selective perspective on its past, present, and future. Two trends currently characterize the field that broadly reflect a pursuit of “where”- and “how”-type questions. The latter addresses basic mechanisms related to the expression of task-induced neural activity and is likely to be an increasingly important theme in the future. This trend entails an enhanced symbiosis among investigators pursuing similar questions in fields such as computational and theoretical neuroscience as well as through the detailed analysis of microcircuitry. PMID:18995825

  13. Data sharing in neuroimaging research

    PubMed Central

    Poline, Jean-Baptiste; Breeze, Janis L.; Ghosh, Satrajit; Gorgolewski, Krzysztof; Halchenko, Yaroslav O.; Hanke, Michael; Haselgrove, Christian; Helmer, Karl G.; Keator, David B.; Marcus, Daniel S.; Poldrack, Russell A.; Schwartz, Yannick; Ashburner, John; Kennedy, David N.

    2012-01-01

    Significant resources around the world have been invested in neuroimaging studies of brain function and disease. Easier access to this large body of work should have profound impact on research in cognitive neuroscience and psychiatry, leading to advances in the diagnosis and treatment of psychiatric and neurological disease. A trend toward increased sharing of neuroimaging data has emerged in recent years. Nevertheless, a number of barriers continue to impede momentum. Many researchers and institutions remain uncertain about how to share data or lack the tools and expertise to participate in data sharing. The use of electronic data capture (EDC) methods for neuroimaging greatly simplifies the task of data collection and has the potential to help standardize many aspects of data sharing. We review here the motivations for sharing neuroimaging data, the current data sharing landscape, and the sociological or technical barriers that still need to be addressed. The INCF Task Force on Neuroimaging Datasharing, in conjunction with several collaborative groups around the world, has started work on several tools to ease and eventually automate the practice of data sharing. It is hoped that such tools will allow researchers to easily share raw, processed, and derived neuroimaging data, with appropriate metadata and provenance records, and will improve the reproducibility of neuroimaging studies. By providing seamless integration of data sharing and analysis tools within a commodity research environment, the Task Force seeks to identify and minimize barriers to data sharing in the field of neuroimaging. PMID:22493576

  14. Recent Advances in Neuroimaging Biomarkers in Geriatric Psychiatry

    PubMed Central

    Khandai, Abhisek C.; Aizenstein, Howard J.

    2013-01-01

    Neuroimaging, both structural and functional, serve as useful adjuncts to clinical assessment, and can provide objective, reliable means of assessing disease presence and process in the aging population. In the following review we briefly explain current imaging methodologies. Then, we analyze recent developments in developing neuroimaging biomarkers for two highly prevalent disorders in the elderly population- Alzheimer's disease (AD) and late-life depression (LLD). In AD, efforts are focused on early diagnosis through in vivo visualization of disease pathophysiology. In LLD, recent imaging evidence supports the role of white matter ischemic changes in the pathogenesis of depression in the elderly, the “vascular hypothesis.” Finally, we discuss potential roles for neuroimaging biomarkers in geriatric psychiatry in the future. PMID:23636984

  15. Benefits of adding Small Financial Incentives or Optional Group Meetings to a Web-based Statewide Obesity Initiative

    PubMed Central

    Leahey, Tricia M.; Subak, Leslee L.; Fava, Joseph; Schembri, Michael; Thomas, Graham; Xu, Xiaomeng; Krupel, Katie; Kent, Kimberly; Boguszewski, Katherine; Kumar, Rajiv; Weinberg, Brad; Wing, Rena

    2014-01-01

    Objective To examine whether adding either small, variable financial incentives or optional group sessions improves weight losses in a community-based, Internet behavioral program. Design and methods Participants (N=268) from Shape Up Rhode Island 2012, a 3 month Web-based community wellness initiative, were randomized to: Shape Up+Internet behavioral program (SI), Shape Up+Internet program+Incentives (SII), or Shape Up+Internet program+Group sessions (SIG). Results At the end of the 3 month program, SII achieved significantly greater weight losses than SI (SII:6.4% [5.1-7.7]; SI:4.2% [3.0-5.6]; P=.03); weight losses in SIG were not significantly different from the other two conditions (SIG: 5.8% [4.5-7.1], P’s≥.10). However, at the 12 month no treatment follow-up visit, both SII and SIG had greater weight losses than SI (SII: 3.1% [1.8-4.4]; SIG: 4.5% [3.2-5.8]; SI: 1.2% [-0.1-2.6]; P’s≤.05). SII was the most cost-effective approach at both 3 (SII: $34/kg; SI: $34/kg; SIG: $87/kg) and 12 months (SII: $64/kg; SI: $140/kg; SIG: $113/kg). Conclusions Modest financial incentives enhance weight losses during a community campaign and both incentives and optional group meetings improved overall weight loss outcomes during the follow-up period. However, the use of the financial incentives is the most cost-effective approach. PMID:25384463

  16. Neuroimaging in ophthalmology

    PubMed Central

    Kim, James D.; Hashemi, Nafiseh; Gelman, Rachel; Lee, Andrew G.

    2012-01-01

    In the past three decades, there have been countless advances in imaging modalities that have revolutionized evaluation, management, and treatment of neuro-ophthalmic disorders. Non-invasive approaches for early detection and monitoring of treatments have decreased morbidity and mortality. Understanding of basic methods of imaging techniques and choice of imaging modalities in cases encountered in neuro-ophthalmology clinic is critical for proper evaluation of patients. Two main imaging modalities that are often used are computed tomography (CT) and magnetic resonance imaging (MRI). However, variations of these modalities and appropriate location of imaging must be considered in each clinical scenario. In this article, we review and summarize the best neuroimaging studies for specific neuro-ophthalmic indications and the diagnostic radiographic findings for important clinical entities. PMID:23961025

  17. Schizophrenia, neuroimaging and connectomics.

    PubMed

    Fornito, Alex; Zalesky, Andrew; Pantelis, Christos; Bullmore, Edward T

    2012-10-01

    Schizophrenia is frequently characterized as a disorder of brain connectivity. Neuroimaging has played a central role in supporting this view, with nearly two decades of research providing abundant evidence of structural and functional connectivity abnormalities in the disorder. In recent years, our understanding of how schizophrenia affects brain networks has been greatly advanced by attempts to map the complete set of inter-regional interactions comprising the brain's intricate web of connectivity; i.e., the human connectome. Imaging connectomics refers to the use of neuroimaging techniques to generate these maps which, combined with the application of graph theoretic methods, has enabled relatively comprehensive mapping of brain network connectivity and topology in unprecedented detail. Here, we review the application of these techniques to the study of schizophrenia, focusing principally on magnetic resonance imaging (MRI) research, while drawing attention to key methodological issues in the field. The published findings suggest that schizophrenia is associated with a widespread and possibly context-independent functional connectivity deficit, upon which are superimposed more circumscribed, context-dependent alterations associated with transient states of hyper- and/or hypo-connectivity. In some cases, these changes in inter-regional functional coupling dynamics can be related to measures of intra-regional dysfunction. Topological disturbances of functional brain networks in schizophrenia point to reduced local network connectivity and modular structure, as well as increased global integration and network robustness. Some, but not all, of these functional abnormalities appear to have an anatomical basis, though the relationship between the two is complex. By comprehensively mapping connectomic disturbances in patients with schizophrenia across the entire brain, this work has provided important insights into the highly distributed character of neural

  18. Neuroimaging Biomarkers for Psychosis

    PubMed Central

    Hager, Brandon M.

    2015-01-01

    Background Biomarkers provide clinicians with a predictable model for the diagnosis, treatment and follow-up of medical ailments. Psychiatry has lagged behind other areas of medicine in the identification of biomarkers for clinical diagnosis and treatment. In this review, we investigated the current state of neuroimaging as it pertains to biomarkers for psychosis. Methods We reviewed systematic reviews and meta-analyses of the structural (sMRI), functional (fMRI), diffusion-tensor (DTI), Positron emission tomography (PET) and spectroscopy (MRS) studies of subjects at-risk or those with an established schizophrenic illness. Only articles reporting effect-sizes and confidence intervals were included in an assessment of robustness. Results Out of the identified meta-analyses and systematic reviews, 21 studies met the inclusion criteria for assessment. There were 13 sMRI, 4 PET, 3 MRS, and 1 DTI studies. The search terms included in the current review encompassed familial high risk (FHR), clinical high risk (CHR), First episode (FES), Chronic (CSZ), schizophrenia spectrum disorders (SSD), and healthy controls (HC). Conclusions Currently, few neuroimaging biomarkers can be considered ready for diagnostic use in patients with psychosis. At least in part, this may be related to the challenges inherent in the current symptom-based approach to classifying these disorders. While available studies suggest a possible value of imaging biomarkers for monitoring disease progression, more systematic research is needed. To date, the best value of imaging data in psychoses has been to shed light on questions of disease pathophysiology, especially through the characterization of endophenotypes. PMID:25883891

  19. Neural modeling and functional neuroimaging.

    PubMed

    Horwitz, B; Sporns, O

    1994-01-01

    Two research areas that so far have had little interaction with one another are functional neuroimaging and computational neuroscience. The application of computational models and techniques to the inherently rich data sets generated by "standard" neurophysiological methods has proven useful for interpreting these data sets and for providing predictions and hypotheses for further experiments. We suggest that both theory- and data-driven computational modeling of neuronal systems can help to interpret data generated by functional neuroimaging methods, especially those used with human subjects. In this article, we point out four sets of questions, addressable by computational neuroscientists whose answere would be of value and interest to those who perform functional neuroimaging. The first set consist of determining the neurobiological substrate of the signals measured by functional neuroimaging. The second set concerns developing systems-level models of functional neuroimaging data. The third set of questions involves integrating functional neuroimaging data across modalities, with a particular emphasis on relating electromagnetic with hemodynamic data. The last set asks how one can relate systems-level models to those at the neuronal and neural ensemble levels. We feel that there are ample reasons to link functional neuroimaging and neural modeling, and that combining the results from the two disciplines will result in furthering our understanding of the central nervous system. © 1994 Wiley-Liss, Inc. This Article is a US Goverment work and, as such, is in the public domain in the United State of America.

  20. Cross-View Neuroimage Pattern Analysis in Alzheimer's Disease Staging

    PubMed Central

    Liu, Sidong; Cai, Weidong; Pujol, Sonia; Kikinis, Ron; Feng, Dagan D.

    2016-01-01

    The research on staging of pre-symptomatic and prodromal phase of neurological disorders, e.g., Alzheimer's disease (AD), is essential for prevention of dementia. New strategies for AD staging with a focus on early detection, are demanded to optimize potential efficacy of disease-modifying therapies that can halt or slow the disease progression. Recently, neuroimaging are increasingly used as additional research-based markers to detect AD onset and predict conversion of MCI and normal control (NC) to AD. Researchers have proposed a variety of neuroimaging biomarkers to characterize the patterns of the pathology of AD and MCI, and suggested that multi-view neuroimaging biomarkers could lead to better performance than single-view biomarkers in AD staging. However, it is still unclear what leads to such synergy and how to preserve or maximize. In an attempt to answer these questions, we proposed a cross-view pattern analysis framework for investigating the synergy between different neuroimaging biomarkers. We quantitatively analyzed nine types of biomarkers derived from FDG-PET and T1-MRI, and evaluated their performance in a task of classifying AD, MCI, and NC subjects obtained from the ADNI baseline cohort. The experiment results showed that these biomarkers could depict the pathology of AD from different perspectives, and output distinct patterns that are significantly associated with the disease progression. Most importantly, we found that these features could be separated into clusters, each depicting a particular aspect; and the inter-cluster features could always achieve better performance than the intra-cluster features in AD staging. PMID:26941639

  1. Impact of Common Variations in PLD3 on Neuroimaging Phenotypes in Non-demented Elders.

    PubMed

    Wang, Chong; Wang, Hui-Fu; Tan, Meng-Shan; Liu, Ying; Jiang, Teng; Zhang, Dao-Qiang; Tan, Lan; Yu, Jin-Tai

    2016-09-01

    Rare variants of phospholipase D3 (PLD3) have been identified as Alzheimer's disease (AD) susceptibility loci, whereas little is known about the potential role of common variants in the progression of AD. To examine the impact of genetic variations in PLD3 on neuroimaging phenotypes in a large non-demented population. A total of 261 normal cognition (NC) and 456 mild cognitive impairment (MCI) individuals from the Alzheimer's Disease Neuroimaging Initiative (ADNI) database are included in our analysis. Multiple linear regression models were applied to examine the association between four single-nucleotide polymorphisms (SNPs; rs7249146, rs4490097, rs12151243, and rs10407447) with the florbetapir retention on florbetapir 18F amyloid positron emission tomography (AV45-PET), the cerebral metabolic rate for glucose (CMRgl) on 18F-fluorodeoxyglucose PET (FDG-PET), and regional volume on magnetic resonance imaging (MRI) at baseline and in the cohort study. We did not detect any significant associations of PLD3 SNPs with florbetapir retention on AV45-PET. In the analysis of FDG-PET, rs10407447 was associated with the CMRgl in the left angular gyrus and bilateral posterior cingulate cortex in the MCI group. Regarding the MRI analysis, rs10407447 was also associated with bilateral inferior lateral ventricle and lateral ventricle volume in MCI group. The main findings of our study provide evidence that support the possible role of PLD3 common variants in influencing AD-related neuroimaging phenotypes. Nevertheless, further work is necessary to explain the functional mechanisms of differences and confirm the causal variants. PMID:26232066

  2. Traumatic brain injury, neuroimaging, and neurodegeneration

    PubMed Central

    Bigler, Erin D.

    2012-01-01

    Depending on severity, traumatic brain injury (TBI) induces immediate neuropathological effects that in the mildest form may be transient but as severity increases results in neural damage and degeneration. The first phase of neural degeneration is explainable by the primary acute and secondary neuropathological effects initiated by the injury; however, neuroimaging studies demonstrate a prolonged period of pathological changes that progressively occur even during the chronic phase. This review examines how neuroimaging may be used in TBI to understand (1) the dynamic changes that occur in brain development relevant to understanding the effects of TBI and how these relate to developmental stage when the brain is injured, (2) how TBI interferes with age-typical brain development and the effects of aging thereafter, and (3) how TBI results in greater frontotemporolimbic damage, results in cerebral atrophy, and is more disruptive to white matter neural connectivity. Neuroimaging quantification in TBI demonstrates degenerative effects from brain injury over time. An adverse synergistic influence of TBI with aging may predispose the brain injured individual for the development of neuropsychiatric and neurodegenerative disorders long after surviving the brain injury. PMID:23964217

  3. Traumatic brain injury, neuroimaging, and neurodegeneration.

    PubMed

    Bigler, Erin D

    2013-01-01

    Depending on severity, traumatic brain injury (TBI) induces immediate neuropathological effects that in the mildest form may be transient but as severity increases results in neural damage and degeneration. The first phase of neural degeneration is explainable by the primary acute and secondary neuropathological effects initiated by the injury; however, neuroimaging studies demonstrate a prolonged period of pathological changes that progressively occur even during the chronic phase. This review examines how neuroimaging may be used in TBI to understand (1) the dynamic changes that occur in brain development relevant to understanding the effects of TBI and how these relate to developmental stage when the brain is injured, (2) how TBI interferes with age-typical brain development and the effects of aging thereafter, and (3) how TBI results in greater frontotemporolimbic damage, results in cerebral atrophy, and is more disruptive to white matter neural connectivity. Neuroimaging quantification in TBI demonstrates degenerative effects from brain injury over time. An adverse synergistic influence of TBI with aging may predispose the brain injured individual for the development of neuropsychiatric and neurodegenerative disorders long after surviving the brain injury.

  4. Memory, consciousness and neuroimaging.

    PubMed Central

    Schacter, D L; Buckner, R L; Koutstaal, W

    1998-01-01

    Neuroimaging techniques that allow the assessment of memory performance in healthy human volunteers while simultaneously obtaining measurements of brain activity in vivo may offer new information on the neural correlates of particular forms of memory retrieval and their association with consciousness and intention. We consider evidence from studies with positron emission tomography and functional magnetic resonance imaging indicating that priming, a form of implicit retrieval, is associated with decreased activity in various cortical regions. We also consider evidence concerning the question of whether two components of explicit retrieval--intentional or effortful search and successful conscious recollection--are preferentially associated with increased activity in prefrontal and medial temporal regions, respectively. Last, we consider recent efforts to probe the relation between the phenomenological character of remembering and neural activity. In this instance we broaden our scope to include studies employing event-related potentials and consider evidence concerning the neural correlates of qualitatively different forms of memory, including memory that is specifically associated with a sense of self, and the recollection of particular temporal or perceptual features that might contribute to a rich and vivid experience of the past. PMID:9854258

  5. Neuroimaging of spine tumors.

    PubMed

    Pinter, Nandor K; Pfiffner, Thomas J; Mechtler, Laszlo L

    2016-01-01

    Intramedullary, intradural/extramedullary, and extradural spine tumors comprise a wide range of neoplasms with an even wider range of clinical symptoms and prognostic features. Magnetic resonance imaging (MRI), commonly used to evaluate the spine in patients presenting with pain, can further characterize lesions that may be encountered on other imaging studies, such as bone scintigraphy or computed tomography (CT). The advantage of the MRI is its multiplane capabilities, superior contrast agent resolution, and flexible protocols that play an important role in assessing tumor location, extent in directing biopsy, in planning proper therapy, and in evaluating therapeutic results. A multimodality approach can be used to fully characterize the lesion and the combination of information obtained from the different modalities usually narrows the diagnostic possibilities significantly. The diagnosis of spinal tumors is based on patient age, topographic features of the tumor, and lesion pattern, as seen at CT and MRI. The shift to high-end imaging incorporating diffusion-weighted imaging, diffusion tensor imaging, magnetic resonance spectroscopy, whole-body short tau inversion recovery, positron emission tomography, intraoperative and high-field MRI as part of the mainstream clinical imaging protocol has provided neurologists, neuro-oncologists, and neurosurgeons a window of opportunity to assess the biologic behavior of spine neoplasms. This chapter reviews neuroimaging of spine tumors, primary and secondary, discussing routine and newer modalities that can reduce the significant morbidity associated with these neoplasms. PMID:27430436

  6. Food addiction and neuroimaging.

    PubMed

    Zhang, Yi; von Deneen, Karen M; Tian, Jie; Gold, Mark S; Liu, Yijun

    2011-01-01

    Obesity has become a serious epidemic and one of the leading global health problems. However, much of the current debate has been fractious, and etiologies of obesity have been attributed to eating behavior (i.e. fast food consumption), personality, depression, addiction or genetics. One of the interesting new hypotheses for explaining the development of obesity involves a food addiction model, which suggests that food is not eaten as much for survival as pleasure and that hedonic overeating is relevant to both substance-related disorders and eating disorders. Accumulating evidence has shown that there are a number of shared neural and hormonal pathways as well as distinct differences in these pathways that may help researchers discover why certain individuals continue to overeat despite health and other consequences, and becomes more and more obese. Functional neuroimaging studies have further revealed that pleasant smelling, looking, and tasting food has reinforcing characteristics similar to drugs of abuse. Many of the brain changes reported for hedonic eating and obesity are also seen in various types of addictions. Most importantly, overeating and obesity may have an acquired drive similar to drug addiction with respect to motivation and incentive craving. In both cases, the desire and continued satisfaction occur after early and repeated exposure to stimuli. The acquired drive for eating food and relative weakness of the satiety signal would cause an imbalance between the drive and hunger/reward centers in the brain and their regulation. In the current paper, we first provide a summary of literature on food addition from eight different perspectives, and then we proposed a research paradigm that may allow screening of new pharmacological treatment on the basis of functional magnetic resonance imaging (fMRI).

  7. Neuroimaging findings in primary insomnia.

    PubMed

    O'Byrne, J N; Berman Rosa, M; Gouin, J-P; Dang-Vu, T T

    2014-10-01

    State-of-the-art neuroimaging techniques have accelerated progress in the study and understanding of sleep in humans. Neuroimaging studies in primary insomnia remain relatively few, considering the important prevalence of this disorder in the general population. This review examines the contribution of functional and structural neuroimaging to our current understanding of primary insomnia. Functional studies during sleep provided support for the hyperarousal theory of insomnia. Functional neuroimaging also revealed abnormalities in cognitive and emotional processing in primary insomnia. Results from structural studies suggest neuroanatomical alterations in primary insomnia, mostly in the hippocampus, anterior cingulate cortex and orbitofrontal cortex. However, these results are not well replicated across studies. A few magnetic resonance spectroscopy studies revealed abnormalities in neurotransmitter concentrations and bioenergetics in primary insomnia. The inconsistencies among neuroimaging findings on insomnia are likely due to clinical heterogeneity, differences in imaging and overall diversity of techniques and designs employed. Larger samples, replication, as well as innovative methodologies are necessary for the progression of this perplexing, yet promising area of research. PMID:25129873

  8. Neuroimaging findings in primary insomnia.

    PubMed

    O'Byrne, J N; Berman Rosa, M; Gouin, J-P; Dang-Vu, T T

    2014-10-01

    State-of-the-art neuroimaging techniques have accelerated progress in the study and understanding of sleep in humans. Neuroimaging studies in primary insomnia remain relatively few, considering the important prevalence of this disorder in the general population. This review examines the contribution of functional and structural neuroimaging to our current understanding of primary insomnia. Functional studies during sleep provided support for the hyperarousal theory of insomnia. Functional neuroimaging also revealed abnormalities in cognitive and emotional processing in primary insomnia. Results from structural studies suggest neuroanatomical alterations in primary insomnia, mostly in the hippocampus, anterior cingulate cortex and orbitofrontal cortex. However, these results are not well replicated across studies. A few magnetic resonance spectroscopy studies revealed abnormalities in neurotransmitter concentrations and bioenergetics in primary insomnia. The inconsistencies among neuroimaging findings on insomnia are likely due to clinical heterogeneity, differences in imaging and overall diversity of techniques and designs employed. Larger samples, replication, as well as innovative methodologies are necessary for the progression of this perplexing, yet promising area of research.

  9. Neuroimaging, culture, and forensic psychiatry.

    PubMed

    Aggarwal, Neil K

    2009-01-01

    The spread of neuroimaging technologies around the world has led to diverse practices of forensic psychiatry and the emergence of neuroethics and neurolaw. This article surveys the neuroethics and neurolegal literature on the use of forensic neuroimaging within the courtroom. Next, the related literature within medical anthropology and science and technology studies is reviewed to show how debates about forensic neuroimaging reflect cultural tensions about attitudes regarding the self, mental illness, and medical expertise. Finally, recommendations are offered on how forensic psychiatrists can add to this research, given their professional interface between law and medicine. At stake are the fundamental concerns that surround changing conceptions of the self, sickness, and expectations of medicine. PMID:19535562

  10. Value-Added Predictors of Expressive and Receptive Language Growth in Initially Nonverbal Preschoolers with Autism Spectrum Disorders

    ERIC Educational Resources Information Center

    Yoder, Paul; Watson, Linda R.; Lambert, Warren

    2015-01-01

    Eighty-seven preschoolers with autism spectrum disorders who were initially nonverbal (under 6 words in language sample and under 21 parent-reported words said) were assessed at five time points over 16 months. Statistical models that accounted for the intercorrelation among nine theoretically- and empirically-motivated predictors, as well as two…

  11. Neurodevelopmental Precursors and Consequences of Substance Use during Adolescence: Promises and Pitfalls of Longitudinal Neuroimaging Strategies.

    PubMed

    Fishbein, Diana H; Rose, Emma J; Darcey, Valerie L; Belcher, Annabelle M; VanMeter, John W

    2016-01-01

    Neurocognitive and emotional regulatory deficits in substance users are often attributed to misuse; however most studies do not include a substance-naïve baseline to justify that conclusion. The etiological literature suggests that pre-existing deficits may contribute to the onset and escalation of use that are then exacerbated by subsequent use. To address this, there is burgeoning interest in conducting prospective, longitudinal neuroimaging studies to isolate neurodevelopmental precursors and consequences of adolescent substance misuse, as reflected in recent initiatives such as the NIH-led Adolescent Brain Cognitive Development (ABCD) study and the National Consortium on Alcohol and Neurodevelopment (NCANDA). To distinguish neurodevelopmental precursors from the consequences of adolescent substance use specifically, prospective, longitudinal neuroimaging studies with substance-naïve pre-adolescents are needed. The exemplar described in this article-i.e., the ongoing Adolescent Development Study (ADS)-used a targeted recruitment strategy to bolster the numbers of pre-adolescent individuals who were at increased risk of substance use (i.e., "high-risk") in a sample that was relatively small for longitudinal studies of similar phenomena, but historically large for neuroimaging (i.e., N = 135; 11-13 years of age). At baseline participants underwent MRI testing and a large complement of cognitive and behavioral assessments along with genetics, stress physiology and interviews. The study methods include repeating these measures at three time points (i.e., baseline/Wave 1, Wave 2 and Wave 3), 18 months apart. In this article, rather than outlining specific study outcomes, we describe the breadth of the numerous complexities and challenges involved in conducting this type of prospective, longitudinal neuroimaging study and "lessons learned" for subsequent efforts are discussed. While these types of large longitudinal neuroimaging studies present a number of

  12. Neurodevelopmental Precursors and Consequences of Substance Use during Adolescence: Promises and Pitfalls of Longitudinal Neuroimaging Strategies

    PubMed Central

    Fishbein, Diana H.; Rose, Emma J.; Darcey, Valerie L.; Belcher, Annabelle M.; VanMeter, John W.

    2016-01-01

    Neurocognitive and emotional regulatory deficits in substance users are often attributed to misuse; however most studies do not include a substance-naïve baseline to justify that conclusion. The etiological literature suggests that pre-existing deficits may contribute to the onset and escalation of use that are then exacerbated by subsequent use. To address this, there is burgeoning interest in conducting prospective, longitudinal neuroimaging studies to isolate neurodevelopmental precursors and consequences of adolescent substance misuse, as reflected in recent initiatives such as the NIH-led Adolescent Brain Cognitive Development (ABCD) study and the National Consortium on Alcohol and Neurodevelopment (NCANDA). To distinguish neurodevelopmental precursors from the consequences of adolescent substance use specifically, prospective, longitudinal neuroimaging studies with substance-naïve pre-adolescents are needed. The exemplar described in this article—i.e., the ongoing Adolescent Development Study (ADS)—used a targeted recruitment strategy to bolster the numbers of pre-adolescent individuals who were at increased risk of substance use (i.e., “high-risk”) in a sample that was relatively small for longitudinal studies of similar phenomena, but historically large for neuroimaging (i.e., N = 135; 11–13 years of age). At baseline participants underwent MRI testing and a large complement of cognitive and behavioral assessments along with genetics, stress physiology and interviews. The study methods include repeating these measures at three time points (i.e., baseline/Wave 1, Wave 2 and Wave 3), 18 months apart. In this article, rather than outlining specific study outcomes, we describe the breadth of the numerous complexities and challenges involved in conducting this type of prospective, longitudinal neuroimaging study and “lessons learned” for subsequent efforts are discussed. While these types of large longitudinal neuroimaging studies present a

  13. Neurodevelopmental Precursors and Consequences of Substance Use during Adolescence: Promises and Pitfalls of Longitudinal Neuroimaging Strategies.

    PubMed

    Fishbein, Diana H; Rose, Emma J; Darcey, Valerie L; Belcher, Annabelle M; VanMeter, John W

    2016-01-01

    Neurocognitive and emotional regulatory deficits in substance users are often attributed to misuse; however most studies do not include a substance-naïve baseline to justify that conclusion. The etiological literature suggests that pre-existing deficits may contribute to the onset and escalation of use that are then exacerbated by subsequent use. To address this, there is burgeoning interest in conducting prospective, longitudinal neuroimaging studies to isolate neurodevelopmental precursors and consequences of adolescent substance misuse, as reflected in recent initiatives such as the NIH-led Adolescent Brain Cognitive Development (ABCD) study and the National Consortium on Alcohol and Neurodevelopment (NCANDA). To distinguish neurodevelopmental precursors from the consequences of adolescent substance use specifically, prospective, longitudinal neuroimaging studies with substance-naïve pre-adolescents are needed. The exemplar described in this article-i.e., the ongoing Adolescent Development Study (ADS)-used a targeted recruitment strategy to bolster the numbers of pre-adolescent individuals who were at increased risk of substance use (i.e., "high-risk") in a sample that was relatively small for longitudinal studies of similar phenomena, but historically large for neuroimaging (i.e., N = 135; 11-13 years of age). At baseline participants underwent MRI testing and a large complement of cognitive and behavioral assessments along with genetics, stress physiology and interviews. The study methods include repeating these measures at three time points (i.e., baseline/Wave 1, Wave 2 and Wave 3), 18 months apart. In this article, rather than outlining specific study outcomes, we describe the breadth of the numerous complexities and challenges involved in conducting this type of prospective, longitudinal neuroimaging study and "lessons learned" for subsequent efforts are discussed. While these types of large longitudinal neuroimaging studies present a number of

  14. The Co-evolution of Neuroimaging and Psychiatric Neurosurgery.

    PubMed

    Dyster, Timothy G; Mikell, Charles B; Sheth, Sameer A

    2016-01-01

    The role of neuroimaging in psychiatric neurosurgery has evolved significantly throughout the field's history. Psychiatric neurosurgery initially developed without the benefit of information provided by modern imaging modalities, and thus lesion targets were selected based on contemporary theories of frontal lobe dysfunction in psychiatric disease. However, by the end of the 20th century, the availability of structural and functional magnetic resonance imaging (fMRI) allowed for the development of mechanistic theories attempting to explain the anatamofunctional basis of these disorders, as well as the efficacy of stereotactic neuromodulatory treatments. Neuroimaging now plays a central and ever-expanding role in the neurosurgical management of psychiatric disorders, by influencing the determination of surgical candidates, allowing individualized surgical targeting and planning, and identifying network-level changes in the brain following surgery. In this review, we aim to describe the coevolution of psychiatric neurosurgery and neuroimaging, including ways in which neuroimaging has proved useful in elucidating the therapeutic mechanisms of neuromodulatory procedures. We focus on ablative over stimulation-based procedures given their historical precedence and the greater opportunity they afford for post-operative re-imaging, but also discuss important contributions from the deep brain stimulation (DBS) literature. We conclude with a discussion of how neuroimaging will transition the field of psychiatric neurosurgery into the era of precision medicine. PMID:27445706

  15. The Co-evolution of Neuroimaging and Psychiatric Neurosurgery

    PubMed Central

    Dyster, Timothy G.; Mikell, Charles B.; Sheth, Sameer A.

    2016-01-01

    The role of neuroimaging in psychiatric neurosurgery has evolved significantly throughout the field’s history. Psychiatric neurosurgery initially developed without the benefit of information provided by modern imaging modalities, and thus lesion targets were selected based on contemporary theories of frontal lobe dysfunction in psychiatric disease. However, by the end of the 20th century, the availability of structural and functional magnetic resonance imaging (fMRI) allowed for the development of mechanistic theories attempting to explain the anatamofunctional basis of these disorders, as well as the efficacy of stereotactic neuromodulatory treatments. Neuroimaging now plays a central and ever-expanding role in the neurosurgical management of psychiatric disorders, by influencing the determination of surgical candidates, allowing individualized surgical targeting and planning, and identifying network-level changes in the brain following surgery. In this review, we aim to describe the coevolution of psychiatric neurosurgery and neuroimaging, including ways in which neuroimaging has proved useful in elucidating the therapeutic mechanisms of neuromodulatory procedures. We focus on ablative over stimulation-based procedures given their historical precedence and the greater opportunity they afford for post-operative re-imaging, but also discuss important contributions from the deep brain stimulation (DBS) literature. We conclude with a discussion of how neuroimaging will transition the field of psychiatric neurosurgery into the era of precision medicine. PMID:27445706

  16. Multiple testing for neuroimaging via hidden Markov random field.

    PubMed

    Shu, Hai; Nan, Bin; Koeppe, Robert

    2015-09-01

    Traditional voxel-level multiple testing procedures in neuroimaging, mostly p-value based, often ignore the spatial correlations among neighboring voxels and thus suffer from substantial loss of power. We extend the local-significance-index based procedure originally developed for the hidden Markov chain models, which aims to minimize the false nondiscovery rate subject to a constraint on the false discovery rate, to three-dimensional neuroimaging data using a hidden Markov random field model. A generalized expectation-maximization algorithm for maximizing the penalized likelihood is proposed for estimating the model parameters. Extensive simulations show that the proposed approach is more powerful than conventional false discovery rate procedures. We apply the method to the comparison between mild cognitive impairment, a disease status with increased risk of developing Alzheimer's or another dementia, and normal controls in the FDG-PET imaging study of the Alzheimer's Disease Neuroimaging Initiative.

  17. Multiple testing for neuroimaging via hidden Markov random field.

    PubMed

    Shu, Hai; Nan, Bin; Koeppe, Robert

    2015-09-01

    Traditional voxel-level multiple testing procedures in neuroimaging, mostly p-value based, often ignore the spatial correlations among neighboring voxels and thus suffer from substantial loss of power. We extend the local-significance-index based procedure originally developed for the hidden Markov chain models, which aims to minimize the false nondiscovery rate subject to a constraint on the false discovery rate, to three-dimensional neuroimaging data using a hidden Markov random field model. A generalized expectation-maximization algorithm for maximizing the penalized likelihood is proposed for estimating the model parameters. Extensive simulations show that the proposed approach is more powerful than conventional false discovery rate procedures. We apply the method to the comparison between mild cognitive impairment, a disease status with increased risk of developing Alzheimer's or another dementia, and normal controls in the FDG-PET imaging study of the Alzheimer's Disease Neuroimaging Initiative. PMID:26012881

  18. Advances in neuroimaging in frontotemporal dementia.

    PubMed

    Gordon, Elizabeth; Rohrer, Jonathan D; Fox, Nick C

    2016-08-01

    Frontotemporal dementia (FTD) is a clinically and neuroanatomically heterogeneous neurodegenerative disorder with multiple underlying genetic and pathological causes. Whilst initial neuroimaging studies highlighted the presence of frontal and temporal lobe atrophy or hypometabolism as the unifying feature in patients with FTD, more detailed studies have revealed diverse patterns across individuals, with variable frontal or temporal predominance, differing degrees of asymmetry, and the involvement of other cortical areas including the insula and cingulate, as well as subcortical structures such as the basal ganglia and thalamus. Recent advances in novel imaging modalities including diffusion tensor imaging, resting-state functional magnetic resonance imaging and molecular positron emission tomography imaging allow the possibility of investigating alterations in structural and functional connectivity and the visualisation of pathological protein deposition. This review will cover the major imaging modalities currently used in research and clinical practice, focusing on the key insights they have provided into FTD, including the onset and evolution of pathological changes and also importantly their utility as biomarkers for disease detection and staging, differential diagnosis and measurement of disease progression. Validating neuroimaging biomarkers that are able to accomplish these tasks will be crucial for the ultimate goal of powering upcoming clinical trials by correctly stratifying patient enrolment and providing sensitive markers for evaluating the effects and efficacy of disease-modifying therapies. This review describes the key insights provided by research into the major neuroimaging modalities currently used in research and clinical practice, including what they tell us about the onset and evolution of FTD and how they may be used as biomarkers for disease detection and staging, differential diagnosis and measurement of disease progression. This article is

  19. Neuroimaging evaluation in refractory epilepsy

    PubMed Central

    Granados, Ana M; Orejuela, Juan F

    2015-01-01

    Purpose To describe the application of neuroimaging analysis, compared to neuropsychological tests and video-electroencephalogram, for the evaluation of refractory epilepsy in a reference centre in Cali, Colombia. Methods Between March 2013 and November 2014, 29 patients, 19 men and 10 women, aged 9–65 years and with refractory epilepsy, were assessed by structural and functional magnetic resonance imaging while performing tasks related to language, verbal and non-verbal memory. Also, volumetric evaluation was performed. A 1.5 Tesla magnetic resonance imaging scanner was used in all cases. Results Neuroimaging evaluation identified 13 patients with mesial temporal sclerosis. The remaining patients were classified as: 10 patients with neoplastic masses, two patients with cortical atrophy, two patients with scarring lesions and two patients with non-structural aetiology. Among patients with mesial temporal sclerosis, comparison between techniques for lateralising the epileptogenic foci was made; the κ index between functional magnetic resonance imaging and hippocampi volumetry was κ = 1.00, agreement between neuroimaging and video-electroencephalogram was good (κ = 0.78) and comparison with a neuropsychological test was mild (κ = 0.24). Conclusions Neuroimaging studies allow the assessment of functional and structural damage related to epileptogenic lesions and foci, and are helpful to select surgical treatment, conduct intraoperative neuronavigation techniques, predict surgical deficits and evaluate patient recovery. PMID:26427897

  20. Neuroimaging of HIV Associated Neurocognitive Disorders (HAND)

    PubMed Central

    Ances, Beau M.; Hammoud, Dima A.

    2014-01-01

    Purpose of review HIV enters the brain after initial infection, and with time can lead to HIV associated neurocognitive disorders (HAND). While the introduction of combination antiretroviral therapy (cART) has reduced the more severe forms of HAND, milder forms are still highly prevalent. The “gold standard” for HAND diagnosis remains detailed neuropsychological performance (NP) testing but additional biomarkers (including neuroimaging) may assist in early detection of HAND. Recent findings We review the application of recently developed non-invasive magnetic resonance imaging (MRI) and positron emission tomography (PET) techniques in HIV+ individuals. In particular, magnetic resonance spectroscopy (MRS) may be more sensitive than conventional MRI alone in detecting HIV associated changes. Diffusion tensor imaging (DTI) has become increasingly popular for assessing changes in white matter structural integrity due to HIV. Both functional MRI and PET have been limitedly performed but could provide keys for characterizing neuropathophysiologic changes due to HIV. Summary It is hoped that continued progress will allow novel neuroimaging methods to be included in future HAND management guidelines. PMID:25250553

  1. Neuroimaging for psychotherapy research: Current trends

    PubMed Central

    WEINGARTEN, CAROL P.; STRAUMAN, TIMOTHY J.

    2014-01-01

    Objective This article reviews neuroimaging studies that inform psychotherapy research. An introduction to neuroimaging methods is provided as background for the increasingly sophisticated breadth of methods and findings appearing in psychotherapy research. Method We compiled and assessed a comprehensive list of neuroimaging studies of psychotherapy outcome, along with selected examples of other types of studies that also are relevant to psychotherapy research. We emphasized magnetic resonance imaging (MRI) since it is the dominant neuroimaging modality in psychological research. Results We summarize findings from neuroimaging studies of psychotherapy outcome, including treatment for depression, obsessive-compulsive disorder (OCD), and schizophrenia. Conclusions The increasing use of neuroimaging methods in the study of psychotherapy continues to refine our understanding of both outcome and process. We suggest possible directions for future neuroimaging studies in psychotherapy research. PMID:24527694

  2. Quantitative Neuroimaging Software for Clinical Assessment of Hippocampal Volumes on MR Imaging

    PubMed Central

    Ahdidan, Jamila; Raji, Cyrus A.; DeYoe, Edgar A.; Mathis, Jedidiah; Noe, Karsten Ø.; Rimestad, Jens; Kjeldsen, Thomas K.; Mosegaard, Jesper; Becker, James T.; Lopez, Oscar

    2015-01-01

    Background: Multiple neurological disorders including Alzheimer’s disease (AD), mesial temporal sclerosis, and mild traumatic brain injury manifest with volume loss on brain MRI. Subtle volume loss is particularly seen early in AD. While prior research has demonstrated the value of this additional information from quantitative neuroimaging, very few applications have been approved for clinical use. Here we describe a US FDA cleared software program, NeuroreaderTM, for assessment of clinical hippocampal volume on brain MRI. Objective: To present the validation of hippocampal volumetrics on a clinical software program. Method: Subjects were drawn (n = 99) from the Alzheimer Disease Neuroimaging Initiative study. Volumetric brain MR imaging was acquired in both 1.5 T (n = 59) and 3.0 T (n = 40) scanners in participants with manual hippocampal segmentation. Fully automated hippocampal segmentation and measurement was done using a multiple atlas approach. The Dice Similarity Coefficient (DSC) measured the level of spatial overlap between NeuroreaderTM and gold standard manual segmentation from 0 to 1 with 0 denoting no overlap and 1 representing complete agreement. DSC comparisons between 1.5 T and 3.0 T scanners were done using standard independent samples T-tests. Results: In the bilateral hippocampus, mean DSC was 0.87 with a range of 0.78–0.91 (right hippocampus) and 0.76–0.91 (left hippocampus). Automated segmentation agreement with manual segmentation was essentially equivalent at 1.5 T (DSC = 0.879) versus 3.0 T (DSC = 0.872). Conclusion: This work provides a description and validation of a software program that can be applied in measuring hippocampal volume, a biomarker that is frequently abnormal in AD and other neurological disorders. PMID:26484924

  3. Imago Mundi, Imago AD, Imago ADNI

    PubMed Central

    2014-01-01

    Since the launch in 2003 of the Alzheimer’s Disease Neuroimaging Initiative (ADNI) in the USA, ever growing, similarly oriented consortia have been organized and assembled around the world. The various accomplishments of ADNI have contributed substantially to a better understanding of the underlying physiopathology of aging and Alzheimer’s disease (AD). These accomplishments are basically predicated in the trinity of multimodality, standardization and sharing. This multimodality approach can now better identify those subjects with AD-specific traits that are more likely to present cognitive decline in the near future and that might represent the best candidates for smaller but more efficient therapeutic trials – trials that, through gained and shared knowledge, can be more focused on a specific target or a specific stage of the disease process. In summary, data generated from ADNI have helped elucidate some of the pathophysiological mechanisms underpinning aging and AD pathology, while contributing to the international effort in setting the groundwork for biomarker discovery and establishing standards for early diagnosis of AD. PMID:25478022

  4. Atypical neuroimaging in Wilson's disease.

    PubMed

    Patell, Rushad; Dosi, Rupal; Joshi, Harshal K; Storz, Dennis

    2014-06-06

    Wilson's disease is a rare metabolic disease involving copper metabolism. Neuroimaging plays an important part in evaluation of patients with a neuropsychiatric presentation. We present a case of a 14-year-old girl with atypical confluent white matter disease and cystic degeneration on MRI, with a rapidly progressive course, who succumbed to complications despite treatment with trientine. Wilson's disease should be considered as a differential for leucoencephalopathy in young patients with progressive neurological disease for its early recognition and optimum outcome.

  5. Understanding the impact of TV commercials: electrical neuroimaging.

    PubMed

    Vecchiato, Giovanni; Kong, Wanzeng; Maglione, Anton Giulio; Wei, Daming

    2012-01-01

    Today, there is a greater interest in the marketing world in using neuroimaging tools to evaluate the efficacy of TV commercials. This field of research is known as neuromarketing. In this article, we illustrate some applications of electrical neuroimaging, a discipline that uses electroencephalography (EEG) and intensive signal processing techniques for the evaluation of marketing stimuli. We also show how the proper usage of these methodologies can provide information related to memorization and attention while people are watching marketing-relevant stimuli. We note that temporal and frequency patterns of EEG signals are able to provide possible descriptors that convey information about the cognitive process in subjects observing commercial advertisements (ads). Such information could be unobtainable through common tools used in standard marketing research. Evidence of this research shows how EEG methodologies could be employed to better design new products that marketers are going to promote and to analyze the global impact of video commercials already broadcast on TV.

  6. Understanding the impact of TV commercials: electrical neuroimaging.

    PubMed

    Vecchiato, Giovanni; Kong, Wanzeng; Maglione, Anton Giulio; Wei, Daming

    2012-01-01

    Today, there is a greater interest in the marketing world in using neuroimaging tools to evaluate the efficacy of TV commercials. This field of research is known as neuromarketing. In this article, we illustrate some applications of electrical neuroimaging, a discipline that uses electroencephalography (EEG) and intensive signal processing techniques for the evaluation of marketing stimuli. We also show how the proper usage of these methodologies can provide information related to memorization and attention while people are watching marketing-relevant stimuli. We note that temporal and frequency patterns of EEG signals are able to provide possible descriptors that convey information about the cognitive process in subjects observing commercial advertisements (ads). Such information could be unobtainable through common tools used in standard marketing research. Evidence of this research shows how EEG methodologies could be employed to better design new products that marketers are going to promote and to analyze the global impact of video commercials already broadcast on TV. PMID:22678840

  7. Cytarabine added to interferon improves the cost-effectiveness of initial therapy for patients with early chronic phase chronic myelogenous leukemia.

    PubMed

    Beck, J R; Guilhot, J; Giles, F J; Aoki, N; Wirt, D P; Guilhot, F

    2001-03-01

    The French Chronic Myeloid Leukemia Study Group prospective randomized study results indicate that the addition of cytarabine to alpha interferon (IFN-alpha) increases the rate of major cytogenetic response and prolongs survival in patients with early chronic phase chronic myelogenous leukemia (CML). The French group study design permitted a single crossover to include or discontinue cytarabine or interferon. Endpoints were overall survival, complete hematologic remission (CHR) at six months, and major cytogenetic response at 12 months. We modified a published Markov model that compared IFN-alpha alone to IFN-alpha plus cytarabine and included the possibility of crossover as in the French study. The model permits allogeneic and autologous stem cell transplantation (SCT), and follows cytogenetic response and acceleration of CML through death. Treatment response, toxicity, and survival are drawn from the French Chronic Myeloid Leukemia Study Group population of 810 patients on an intention-to-treat model. Survivals are extended to 62 months based on currently available follow-up. Costs from a United States oncology specialty institution, and state utilities from previous research and a quality-adjusted Time Without Symptoms or Toxicity analysis of the subject study were discounted at 3% per annum. At the median cohort age of 50, cytarabine offers 21 months of added median survival to IFN-alpha, which itself is superior to conventional chemotherapy by 21 months. Cost-effectiveness estimates for cytarabine added to IFN-alpha range from $7,000 per quality-adjusted life year (QALY) to $35,000 per QALY, under all plausible assumptions superior to IFN-alpha alone. The model is sensitive to the quality of life on therapy, as well as to remission rate with additive cytarabine, although the cost-effectiveness calculations are robust over the entire range of clinical assumptions. Based on data from the French study, cytarabine added to IFN-alpha substantially improves the cost

  8. Initial measurements of CO2 concentrations (1530 to 1940 AD) in air occluded in the GISP 2 Ice Core from central Greenland

    NASA Astrophysics Data System (ADS)

    Wahlen, M.; Allen, D.; Deck, B.; Herchenroder, A.

    Initial measurements of CO2 in the air of bubbles in the GISP 2 (Greenland Ice Sheet Project 2) ice core were performed using a dry extraction technique and tunable diode laser absorption spectroscopy. The record spans the years 1530 to 1940, and includes part of the little ice age. Absolute dating of the air was obtained from the location of the 14CO2 bomb peak in the bubble air, relative dating from the seasonal variations of H218O and electro-conductivity. The results for preindustrial times indicate constant atmospheric CO2 levels of 280±5 ppmv between 1530 and 1810 AD. Thereafter the concentrations rise rather abruptly. The record smoothly connects to the direct atmospheric observations from Mauna Loa.

  9. The Usefulness of Biological and Neuroimaging Markers for the Diagnosis of Early-Onset Alzheimer's Disease

    PubMed Central

    Padovani, Alessandro; Gilberti, Nicola; Borroni, Barbara

    2011-01-01

    The recent proposed criteria for Alzheimer's Disease (AD) have strongly claimed the usefulness of biological and neuroimaging markers for early identification AD. Cerebrospinal fluid (CSF) Tau/Abeta ratio, hippocampal atrophy, posterior cingulate, and neocortical associative area hypometabolism, or amyloid burden evaluated by PiB compound, held the premises to increase diagnostic accuracy in the preclinical disease stages. Despite many efforts to identify subjects at risk of developing AD, less attention has been paid to presenile AD diagnosis. A few data are already available in early onset AD, mainly obtained in cases of monogenic disorder. In this paper, we discuss the current literature on the role of biological and neuroimaging markers in presenile AD. PMID:21559247

  10. The usefulness of biological and neuroimaging markers for the diagnosis of early-onset Alzheimer's disease.

    PubMed

    Padovani, Alessandro; Gilberti, Nicola; Borroni, Barbara

    2011-02-21

    The recent proposed criteria for Alzheimer's Disease (AD) have strongly claimed the usefulness of biological and neuroimaging markers for early identification AD. Cerebrospinal fluid (CSF) Tau/Abeta ratio, hippocampal atrophy, posterior cingulate, and neocortical associative area hypometabolism, or amyloid burden evaluated by PiB compound, held the premises to increase diagnostic accuracy in the preclinical disease stages. Despite many efforts to identify subjects at risk of developing AD, less attention has been paid to presenile AD diagnosis. A few data are already available in early onset AD, mainly obtained in cases of monogenic disorder. In this paper, we discuss the current literature on the role of biological and neuroimaging markers in presenile AD.

  11. Neuroimaging Endophenotypes in Autism Spectrum Disorder

    PubMed Central

    Mahajan, Rajneesh; Mostofsky, Stewart H.

    2015-01-01

    Autism spectrum disorder (ASD) is a neurodevelopmental disorder that has a strong genetic basis, and is heterogeneous in its etiopathogenesis and clinical presentation. Neuroimaging studies, in concert with neuropathological and clinical research, have been instrumental in delineating trajectories of development in children with ASD. Structural neuroimaging has revealed ASD to be a disorder with general and regional brain enlargement, especially in the frontotemporal cortices, while functional neuroimaging studies have highlighted diminished connectivity, especially between frontal-posterior regions. The diverse and specific neuroimaging findings may represent potential neuroendophenotypes, and may offer opportunities to further understand the etiopathogenesis of ASD, predict treatment response and lead to the development of new therapies. PMID:26234701

  12. Structural Neuroimaging of Geriatric Depression

    PubMed Central

    Benjamin, Sophiya; Steffens, David C

    2013-01-01

    There is a large literature on the neuroanatomy of late-life depression which continues to grow with the discovery of novel structural imaging techniques along with innovative methods to analyze the images. Such advances have helped identify specific areas as well characteristic lesions in the brain and changes in the chemical composition in these regions that might be important in the pathophysiology of this complex disease. In this article we review the relevant findings by each structural neuroimaging technique. When validated across many studies, such findings can serve as neuroanatomic markers that can help generate rational hypotheses for future studies to further our understanding of geriatric depression. PMID:21536166

  13. Neuroimaging Week: A Novel, Engaging, and Effective Curriculum for Teaching Neuroimaging to Junior Psychiatric Residents

    ERIC Educational Resources Information Center

    Downar, Jonathan; Krizova, Adriana; Ghaffar, Omar; Zaretsky, Ari

    2010-01-01

    Objective: Neuroimaging techniques are increasingly important in psychiatric research and clinical practice, but few postgraduate psychiatry programs offer formal training in neuroimaging. To address this need, the authors developed a course to prepare psychiatric residents to use neuroimaging techniques effectively in independent practice.…

  14. A simple tool for neuroimaging data sharing.

    PubMed

    Haselgrove, Christian; Poline, Jean-Baptiste; Kennedy, David N

    2014-01-01

    Data sharing is becoming increasingly common, but despite encouragement and facilitation by funding agencies, journals, and some research efforts, most neuroimaging data acquired today is still not shared due to political, financial, social, and technical barriers to sharing data that remain. In particular, technical solutions are few for researchers that are not a part of larger efforts with dedicated sharing infrastructures, and social barriers such as the time commitment required to share can keep data from becoming publicly available. We present a system for sharing neuroimaging data, designed to be simple to use and to provide benefit to the data provider. The system consists of a server at the International Neuroinformatics Coordinating Facility (INCF) and user tools for uploading data to the server. The primary design principle for the user tools is ease of use: the user identifies a directory containing Digital Imaging and Communications in Medicine (DICOM) data, provides their INCF Portal authentication, and provides identifiers for the subject and imaging session. The user tool anonymizes the data and sends it to the server. The server then runs quality control routines on the data, and the data and the quality control reports are made public. The user retains control of the data and may change the sharing policy as they need. The result is that in a few minutes of the user's time, DICOM data can be anonymized and made publicly available, and an initial quality control assessment can be performed on the data. The system is currently functional, and user tools and access to the public image database are available at http://xnat.incf.org/. PMID:24904398

  15. A simple tool for neuroimaging data sharing

    PubMed Central

    Haselgrove, Christian; Poline, Jean-Baptiste; Kennedy, David N.

    2014-01-01

    Data sharing is becoming increasingly common, but despite encouragement and facilitation by funding agencies, journals, and some research efforts, most neuroimaging data acquired today is still not shared due to political, financial, social, and technical barriers to sharing data that remain. In particular, technical solutions are few for researchers that are not a part of larger efforts with dedicated sharing infrastructures, and social barriers such as the time commitment required to share can keep data from becoming publicly available. We present a system for sharing neuroimaging data, designed to be simple to use and to provide benefit to the data provider. The system consists of a server at the International Neuroinformatics Coordinating Facility (INCF) and user tools for uploading data to the server. The primary design principle for the user tools is ease of use: the user identifies a directory containing Digital Imaging and Communications in Medicine (DICOM) data, provides their INCF Portal authentication, and provides identifiers for the subject and imaging session. The user tool anonymizes the data and sends it to the server. The server then runs quality control routines on the data, and the data and the quality control reports are made public. The user retains control of the data and may change the sharing policy as they need. The result is that in a few minutes of the user’s time, DICOM data can be anonymized and made publicly available, and an initial quality control assessment can be performed on the data. The system is currently functional, and user tools and access to the public image database are available at http://xnat.incf.org/. PMID:24904398

  16. Neuroimaging.

    PubMed

    Pope, Whitney B; Djoukhadar, Ibrahim; Jackson, Alan

    2016-01-01

    Imaging is integral to the management of patients with brain tumors. Conventional structural imaging provides exquisite anatomic detail but remains limited in the evaluation of molecular characteristics of intracranial neoplasms. Quantitative and physiologic biomarkers derived from advanced imaging techniques have been increasingly utilized as problem-solving tools to identify glioma grade and assess response to therapy. This chapter provides a comprehensive overview of the imaging strategies used in the clinical assessment of patients with gliomas and describes how novel imaging biomarkers have the potential to improve patient management. PMID:26948347

  17. Commentary: Applications of functional neuroimaging to civil litigation of mild traumatic brain injury.

    PubMed

    Granacher, Robert P

    2008-01-01

    The current definition of mild traumatic brain injury (MTBI) is in flux. Presently, there are at least three working definitions of this disorder in the United States, with no clear consensus. Functional neuroimaging, such as single photon emission computed tomography (SPECT) and positron emission tomography (PET), initially showed promise in their ability to improve the diagnostic credibility of MTBI. Over the past decade, that promise has not been fulfilled and there is a paucity of quality studies or standards for the application of functional neuroimaging to traumatic brain injury, particularly in litigation. The legal profession is ahead of the science in this matter. The emergence of neurolaw is driving a growing use of functional neuroimaging, as a sole imaging modality, used by lawyers in an attempt to prove MTBI at trial. The medical literature on functional neuroimaging and its applications to MTBI is weak scientifically, sparse in quality publications, lacking in well-designed controlled studies, and currently does not meet the complete standards of Daubert v. Merrell Dow Pharmaceuticals, Inc., for introduction of scientific evidence at trial. At the present time, there is a clear lack of clinical correlation between functional neuroimaging of MTBI and behavioral, neuropsychological, or structural neuroimaging deficits. The use of SPECT or PET, without concurrent clinical correlation with structural neuroimaging (CT or MRI), is not recommended to be offered as evidence of MTBI in litigation.

  18. Neuroimaging and plasticity in schizophrenia.

    PubMed

    Meyer-Lindenberg, Andreas; Tost, Heike

    2014-01-01

    Schizophrenia is a frequent and highly heritable brain disorder that typically manifests around or after puberty and has a fluctuating course. Multiple lines of evidence point to a neurodevelopmental origin of the illness and suggest that its (post) pubertal manifestation is related to genetic and environmental risk factors that interfere with the structural and functional reorganization of neural networks at this time. Longitudinal structural neuroimaging studies point to a progressive reduction in gray matter volume in many brain regions in schizophrenia. It has been proposed that these neuroimaging observations reflect an enduring disturbance of experience-dependent synaptic plasticity arising from developmental abnormalities in key neural circuits implicated in schizophrenia, including dorsolateral prefrontal cortex and hippocampal formation. Recent work has identified genetic variants linked to neural plasticity that are associated with changes in these circuits. Furthermore, non-invasive interventions such as transcranial magnetic stimulation have been shown to impact some of these systems-level intermediate phenotypes, suggesting a modifiability of these core pathophysiological processes of schizophrenia that may be exploited by therapy. PMID:23902983

  19. Neuroimaging and plasticity in schizophrenia.

    PubMed

    Meyer-Lindenberg, Andreas; Tost, Heike

    2014-01-01

    Schizophrenia is a frequent and highly heritable brain disorder that typically manifests around or after puberty and has a fluctuating course. Multiple lines of evidence point to a neurodevelopmental origin of the illness and suggest that its (post) pubertal manifestation is related to genetic and environmental risk factors that interfere with the structural and functional reorganization of neural networks at this time. Longitudinal structural neuroimaging studies point to a progressive reduction in gray matter volume in many brain regions in schizophrenia. It has been proposed that these neuroimaging observations reflect an enduring disturbance of experience-dependent synaptic plasticity arising from developmental abnormalities in key neural circuits implicated in schizophrenia, including dorsolateral prefrontal cortex and hippocampal formation. Recent work has identified genetic variants linked to neural plasticity that are associated with changes in these circuits. Furthermore, non-invasive interventions such as transcranial magnetic stimulation have been shown to impact some of these systems-level intermediate phenotypes, suggesting a modifiability of these core pathophysiological processes of schizophrenia that may be exploited by therapy.

  20. What's new in neuroimaging methods?

    PubMed Central

    Bandettini, Peter A.

    2009-01-01

    The rapid advancement of neuroimaging methodology and availability has transformed neuroscience research. The answers to many questions that we ask about how the brain is organized depend on the quality of data that we are able to obtain about the locations, dynamics, fluctuations, magnitudes, and types of brain activity and structural changes. In this review, an attempt is made to take a snapshot of the cutting edge of a small component of the very rapidly evolving field of neuroimaging. For each area covered, a brief context is provided along with a summary of a few of the current developments and issues. Then, several outstanding papers, published in the past year or so, are described, providing an example of the directions in which each area is progressing. The areas covered include functional MRI (fMRI), voxel based morphometry (VBM), diffusion tensor imaging (DTI), electroencephalography (EEG), magnetoencephalography (MEG), optical imaging, and positron emission tomography (PET). More detail is included on fMRI, as subsections include: functional MRI interpretation, new functional MRI contrasts, MRI technology, MRI paradigms and processing, and endogenous oscillations in functional MRI. PMID:19338512

  1. Neuroimaging of Freezing of Gait

    PubMed Central

    Fasano, Alfonso; Herman, Talia; Tessitore, Alessandro; Strafella, Antonio P.; Bohnen, Nicolaas I.

    2015-01-01

    Abstract Functional brain imaging techniques appear ideally suited to explore the pathophysiology of freezing of gait (FOG). In the last two decades, techniques based on magnetic resonance or nuclear medicine imaging have found a number of structural changes and functional disconnections between subcortical and cortical regions of the locomotor network in patients with FOG. FOG seems to be related in part to disruptions in the “executive-attention” network along with regional tissue loss including the premotor area, inferior frontal gyrus, precentral gyrus, the parietal and occipital areas involved in visuospatial functions of the right hemisphere. Several subcortical structures have been also involved in the etiology of FOG, principally the caudate nucleus and the locomotor centers in the brainstem. Maladaptive neural compensation may present transiently in the presence of acute conflicting motor, cognitive or emotional stimulus processing, thus causing acute network overload and resulting in episodic impairment of stepping. In this review we will summarize the state of the art of neuroimaging research for FOG. We will also discuss the limitations of current approaches and delineate the next steps of neuroimaging research to unravel the pathophysiology of this mysterious motor phenomenon. PMID:25757831

  2. Neuroimaging of lipid storage disorders.

    PubMed

    Rieger, Deborah; Auerbach, Sarah; Robinson, Paul; Gropman, Andrea

    2013-01-01

    Lipid storage diseases, also known as the lipidoses, are a group of inherited metabolic disorders in which there is lipid accumulation in various cell types, including the central nervous system, because of the deficiency of a variety of enzymes. Over time, excessive storage can cause permanent cellular and tissue damage. The brain is particularly sensitive to lipid storage as the contents of the central nervous system must occupy uniform volume, and any increases in fluids or deposits will lead to pressure changes and interference with normal neurological function. In addition to primary lipid storage diseases, lysosomal storage diseases include the mucolipidoses (in which excessive amounts of lipids and carbohydrates are stored in the cells and tissues) and the mucopolysaccharidoses (in which abnormal glycosylated proteins cannot be broken down because of enzyme deficiency). Neurological dysfunction can be a manifestation of these conditions due to substrate deposition as well. This review will explore the modalities of neuroimaging that may have particular relevance to the study of the lipid storage disorder and their impact on elucidating aspects of brain function. First, the techniques will be reviewed. Next, the neuropathology of a few selected lipid storage disorders will be reviewed and the use of neuroimaging to define disease characteristics discussed in further detail. Examples of studies using these techniques will be discussed in the text.

  3. [Network analyses in neuroimaging studies].

    PubMed

    Hirano, Shigeki; Yamada, Makiko

    2013-06-01

    Neurons are anatomically and physiologically connected to each other, and these connections are involved in various neuronal functions. Multiple important neural networks involved in neurodegenerative diseases can be detected using network analyses in functional neuroimaging. First, the basic methods and theories of voxel-based network analyses, such as principal component analysis, independent component analysis, and seed-based analysis, are described. Disease- and symptom-specific brain networks have been identified using glucose metabolism images in patients with Parkinson's disease. These networks enable us to objectively evaluate individual patients and serve as diagnostic tools as well as biomarkers for therapeutic interventions. Many functional MRI studies have shown that "hub" brain regions, such as the posterior cingulate cortex and medial prefrontal cortex, are deactivated by externally driven cognitive tasks; such brain regions form the "default mode network." Recent studies have shown that this default mode network is disrupted from the preclinical phase of Alzheimer's disease and is associated with amyloid deposition in the brain. Some recent studies have shown that the default mode network is also impaired in Parkinson's disease, whereas other studies have shown inconsistent results. These incongruent results could be due to the heterogeneous pharmacological status, differences in mesocortical dopaminergic impairment status, and concomitant amyloid deposition. Future neuroimaging network analysis studies will reveal novel and interesting findings that will uncover the pathomechanisms of neurological and psychiatric disorders. PMID:23735528

  4. Neuroimaging of Cognitive Load in Instructional Multimedia

    ERIC Educational Resources Information Center

    Whelan, Robert R.

    2007-01-01

    This paper reviews research literature on cognitive load measurement in learning and neuroimaging, and describes a mapping between the main elements of cognitive load theory and findings in functional neuroanatomy. It is argued that these findings may lead to the improved measurement of cognitive load using neuroimaging. The paper describes how…

  5. Neuroimaging and Research into Second Language Acquisition

    ERIC Educational Resources Information Center

    Sabourin, Laura

    2009-01-01

    Neuroimaging techniques are becoming not only more and more sophisticated but are also coming to be increasingly accessible to researchers. One thing that one should take note of is the potential of neuroimaging research within second language acquisition (SLA) to contribute to issues pertaining to the plasticity of the adult brain and to general…

  6. Neuroimaging and Genetic Risk for Alzheimer’s Disease and Addiction-Related Degenerative Brain Disorders

    PubMed Central

    Jahanshad, Neda; Leonardo, Cassandra D.; Thompson, Paul M.

    2014-01-01

    Neuroimaging offers a powerful means to assess the trajectory of brain degeneration in a variety of disorders, including Alzheimer’s disease (AD). Here we describe how multimodal imaging can be used to study the changing brain during the different stages of AD. We integrate findings from a range of studies using magnetic resonance imaging (MRI), positron emission tomography (PET), functional MRI (fMRI) and diffusion weighted imaging (DWI). Neuroimaging reveals how risk genes for degenerative disorders affect the brain, including several recently discovered genetic variants that may disrupt brain connectivity. We review some recent neuroimaging studies of genetic polymorphisms associated with increased risk for late-onset Alzheimer’s disease (LOAD). Some genetic variants that increase risk for drug addiction may overlap with those associated with degenerative brain disorders. These common associations offer new insight into mechanisms underlying neurodegeneration and addictive behaviors, and may offer new leads for treating them before severe and irreversible neurological symptoms appear. PMID:24142306

  7. Neuroimaging and genetic risk for Alzheimer's disease and addiction-related degenerative brain disorders.

    PubMed

    Roussotte, Florence F; Daianu, Madelaine; Jahanshad, Neda; Leonardo, Cassandra D; Thompson, Paul M

    2014-06-01

    Neuroimaging offers a powerful means to assess the trajectory of brain degeneration in a variety of disorders, including Alzheimer's disease (AD). Here we describe how multi-modal imaging can be used to study the changing brain during the different stages of AD. We integrate findings from a range of studies using magnetic resonance imaging (MRI), positron emission tomography (PET), functional MRI (fMRI) and diffusion weighted imaging (DWI). Neuroimaging reveals how risk genes for degenerative disorders affect the brain, including several recently discovered genetic variants that may disrupt brain connectivity. We review some recent neuroimaging studies of genetic polymorphisms associated with increased risk for late-onset Alzheimer's disease (LOAD). Some genetic variants that increase risk for drug addiction may overlap with those associated with degenerative brain disorders. These common associations offer new insight into mechanisms underlying neurodegeneration and addictive behaviors, and may offer new leads for treating them before severe and irreversible neurological symptoms appear.

  8. Clinical use of amyloid-positron emission tomography neuroimaging: Practical and bioethical considerations.

    PubMed

    Witte, Michael M; Foster, Norman L; Fleisher, Adam S; Williams, Monique M; Quaid, Kimberly; Wasserman, Michael; Hunt, Gail; Roberts, J Scott; Rabinovici, Gil D; Levenson, James L; Hake, Ann Marie; Hunter, Craig A; Van Campen, Luann E; Pontecorvo, Michael J; Hochstetler, Helen M; Tabas, Linda B; Trzepacz, Paula T

    2015-09-01

    Until recently, estimation of β-amyloid plaque density as a key element for identifying Alzheimer's disease (AD) pathology as the cause of cognitive impairment was only possible at autopsy. Now with amyloid-positron emission tomography (amyloid-PET) neuroimaging, this AD hallmark can be detected antemortem. Practitioners and patients need to better understand potential diagnostic benefits and limitations of amyloid-PET and the complex practical, ethical, and social implications surrounding this new technology. To complement the practical considerations, Eli Lilly and Company sponsored a Bioethics Advisory Board to discuss ethical issues that might arise from clinical use of amyloid-PET neuroimaging with patients being evaluated for causes of cognitive decline. To best address the multifaceted issues associated with amyloid-PET neuroimaging, we recommend this technology be used only by experienced imaging and treating physicians in appropriately selected patients and only in the context of a comprehensive clinical evaluation with adequate explanations before and after the scan. PMID:27239516

  9. Neuroimaging in Psychiatry: From Bench to Bedside

    PubMed Central

    Linden, David E. J.; Fallgatter, Andreas J.

    2009-01-01

    This perspective considers the present and the future role of different neuroimaging techniques in the field of psychiatry. After identifying shortcomings of the mainly symptom-focussed diagnostic processes and treatment decisions in modern psychiatry, we suggest topics where neuroimaging methods have the potential to help. These include better understanding of the pathophysiology, improved diagnoses, assistance in therapeutic decisions and the supervision of treatment success by direct assessment of improvement in disease-related brain functions. These different questions are illustrated by examples from neuroimaging studies, with a focus on severe mental and neuropsychiatric illnesses such as schizophrenia and depression. Despite all reservations addressed in the article, we are optimistic that neuroimaging has a huge potential with regard to the above-mentioned questions. We expect that neuroimaging will play an increasing role in the future refinement of the diagnostic process and aid in the development of new therapies in the field of psychiatry. PMID:20087437

  10. CATI: A Large Distributed Infrastructure for the Neuroimaging of Cohorts.

    PubMed

    Operto, Grégory; Chupin, Marie; Batrancourt, Bénédicte; Habert, Marie-Odile; Colliot, Olivier; Benali, Habib; Poupon, Cyril; Champseix, Catherine; Delmaire, Christine; Marie, Sullivan; Rivière, Denis; Pélégrini-Issac, Mélanie; Perlbarg, Vincent; Trebossen, Régine; Bottlaender, Michel; Frouin, Vincent; Grigis, Antoine; Orfanos, Dimitri Papadopoulos; Dary, Hugo; Fillon, Ludovic; Azouani, Chabha; Bouyahia, Ali; Fischer, Clara; Edward, Lydie; Bouin, Mathilde; Thoprakarn, Urielle; Li, Jinpeng; Makkaoui, Leila; Poret, Sylvain; Dufouil, Carole; Bouteloup, Vincent; Chételat, Gaël; Dubois, Bruno; Lehéricy, Stéphane; Mangin, Jean-François; Cointepas, Yann

    2016-07-01

    This paper provides an overview of CATI, a platform dedicated to multicenter neuroimaging. Initiated by the French Alzheimer's plan (2008-2012), CATI is a research project called on to provide service to other projects like an industrial partner. Its core mission is to support the neuroimaging of large populations, providing concrete solutions to the increasing complexity involved in such projects by bringing together a service infrastructure, the know-how of its expert academic teams and a large-scale, harmonized network of imaging facilities. CATI aims to make data sharing across studies easier and promotes sharing as much as possible. In the last 4 years, CATI has assisted the clinical community by taking charge of 35 projects so far and has emerged as a recognized actor at the national and international levels.

  11. Visual attention and the neuroimage bias.

    PubMed

    Baker, D A; Schweitzer, N J; Risko, Evan F; Ware, Jillian M

    2013-01-01

    Several highly-cited experiments have presented evidence suggesting that neuroimages may unduly bias laypeople's judgments of scientific research. This finding has been especially worrisome to the legal community in which neuroimage techniques may be used to produce evidence of a person's mental state. However, a more recent body of work that has looked directly at the independent impact of neuroimages on layperson decision-making (both in legal and more general arenas), and has failed to find evidence of bias. To help resolve these conflicting findings, this research uses eye tracking technology to provide a measure of attention to different visual representations of neuroscientific data. Finding an effect of neuroimages on the distribution of attention would provide a potential mechanism for the influence of neuroimages on higher-level decisions. In the present experiment, a sample of laypeople viewed a vignette that briefly described a court case in which the defendant's actions might have been explained by a neurological defect. Accompanying these vignettes was either an MRI image of the defendant's brain, or a bar graph depicting levels of brain activity-two competing visualizations that have been the focus of much of the previous research on the neuroimage bias. We found that, while laypeople differentially attended to neuroimagery relative to the bar graph, this did not translate into differential judgments in a way that would support the idea of a neuroimage bias.

  12. Evolving Evidence for the Value of Neuroimaging Methods and Biological Markers in Subjects Categorized with Subjective Cognitive Decline.

    PubMed

    Lista, Simone; Molinuevo, Jose L; Cavedo, Enrica; Rami, Lorena; Amouyel, Philippe; Teipel, Stefan J; Garaci, Francesco; Toschi, Nicola; Habert, Marie-Odile; Blennow, Kaj; Zetterberg, Henrik; O'Bryant, Sid E; Johnson, Leigh; Galluzzi, Samantha; Bokde, Arun L W; Broich, Karl; Herholz, Karl; Bakardjian, Hovagim; Dubois, Bruno; Jessen, Frank; Carrillo, Maria C; Aisen, Paul S; Hampel, Harald

    2015-09-24

    There is evolving evidence that individuals categorized with subjective cognitive decline (SCD) are potentially at higher risk for developing objective and progressive cognitive impairment compared to cognitively healthy individuals without apparent subjective complaints. Interestingly, SCD, during advancing preclinical Alzheimer's disease (AD), may denote very early, subtle cognitive decline that cannot be identified using established standardized tests of cognitive performance. The substantial heterogeneity of existing SCD-related research data has led the Subjective Cognitive Decline Initiative (SCD-I) to accomplish an international consensus on the definition of a conceptual research framework on SCD in preclinical AD. In the area of biological markers, the cerebrospinal fluid signature of AD has been reported to be more prevalent in subjects with SCD compared to healthy controls; moreover, there is a pronounced atrophy, as demonstrated by magnetic resonance imaging, and an increased hypometabolism, as revealed by positron emission tomography, in characteristic brain regions affected by AD. In addition, SCD individuals carrying an apolipoprotein ɛ4 allele are more likely to display AD-phenotypic alterations. The urgent requirement to detect and diagnose AD as early as possible has led to the critical examination of the diagnostic power of biological markers, neurophysiology, and neuroimaging methods for AD-related risk and clinical progression in individuals defined with SCD. Observational studies on the predictive value of SCD for developing AD may potentially be of practical value, and an evidence-based, validated, qualified, and fully operationalized concept may inform clinical diagnostic practice and guide earlier designs in future therapy trials. PMID:26402088

  13. Neuroimaging in Alcohol and Drug Dependence

    PubMed Central

    Niciu, Mark J.

    2014-01-01

    Neuroimaging, including PET, MRI, and MRS, is a powerful approach to the study of brain function. This article reviews neuroimaging findings related to alcohol and other drugs of abuse that have been published since 2011. Uses of neuroimaging are to characterize patients to determine who will fare better in treatment and to investigate the reasons underlying the effect on outcomes. Neuroimaging is also used to characterize the acute and chronic effects of substances on the brain and how those effects are related to dependence, relapse, and other drug effects. The data can be used to provide encouraging information for patients, as several studies have shown that long-term abstinence is associated with at least partial normalization of neurological abnormalities. PMID:24678450

  14. Statistical Approaches to Functional Neuroimaging Data

    PubMed Central

    DuBois Bowman, F; Guo, Ying; Derado, Gordana

    2007-01-01

    Synopsis The field of statistics makes valuable contributions to functional neuroimaging research by establishing procedures for the design and conduct of neuroimaging experiements and by providing tools for objectively quantifying and measuring the strength of scientific evidence provided by the data. Two common functional neuroimaging research objecitves include detecting brain regions that reveal task-related alterations in measured brain activity (activations) and identifying highly correlated brain regions that exhibit similar patterns of activity over time (functional connectivity). In this article, we highlight various statistical procedures for analyzing data from activation studies and from functional connectivity studies, focusing on functional magnetic resonance imaging (fMRI) and positron emission tomography (PET) data. We also discuss emerging statistical methods for prediction using fMRI and PET data, which stand to increase the translational significance of functional neuroimaging data to clinical practice. PMID:17983962

  15. Visual Systems for Interactive Exploration and Mining of Large-Scale Neuroimaging Data Archives

    PubMed Central

    Bowman, Ian; Joshi, Shantanu H.; Van Horn, John D.

    2012-01-01

    While technological advancements in neuroimaging scanner engineering have improved the efficiency of data acquisition, electronic data capture methods will likewise significantly expedite the populating of large-scale neuroimaging databases. As they do and these archives grow in size, a particular challenge lies in examining and interacting with the information that these resources contain through the development of compelling, user-driven approaches for data exploration and mining. In this article, we introduce the informatics visualization for neuroimaging (INVIZIAN) framework for the graphical rendering of, and dynamic interaction with the contents of large-scale neuroimaging data sets. We describe the rationale behind INVIZIAN, detail its development, and demonstrate its usage in examining a collection of over 900 T1-anatomical magnetic resonance imaging (MRI) image volumes from across a diverse set of clinical neuroimaging studies drawn from a leading neuroimaging database. Using a collection of cortical surface metrics and means for examining brain similarity, INVIZIAN graphically displays brain surfaces as points in a coordinate space and enables classification of clusters of neuroanatomically similar MRI images and data mining. As an initial step toward addressing the need for such user-friendly tools, INVIZIAN provides a highly unique means to interact with large quantities of electronic brain imaging archives in ways suitable for hypothesis generation and data mining. PMID:22536181

  16. Visual systems for interactive exploration and mining of large-scale neuroimaging data archives.

    PubMed

    Bowman, Ian; Joshi, Shantanu H; Van Horn, John D

    2012-01-01

    While technological advancements in neuroimaging scanner engineering have improved the efficiency of data acquisition, electronic data capture methods will likewise significantly expedite the populating of large-scale neuroimaging databases. As they do and these archives grow in size, a particular challenge lies in examining and interacting with the information that these resources contain through the development of compelling, user-driven approaches for data exploration and mining. In this article, we introduce the informatics visualization for neuroimaging (INVIZIAN) framework for the graphical rendering of, and dynamic interaction with the contents of large-scale neuroimaging data sets. We describe the rationale behind INVIZIAN, detail its development, and demonstrate its usage in examining a collection of over 900 T1-anatomical magnetic resonance imaging (MRI) image volumes from across a diverse set of clinical neuroimaging studies drawn from a leading neuroimaging database. Using a collection of cortical surface metrics and means for examining brain similarity, INVIZIAN graphically displays brain surfaces as points in a coordinate space and enables classification of clusters of neuroanatomically similar MRI images and data mining. As an initial step toward addressing the need for such user-friendly tools, INVIZIAN provides a highly unique means to interact with large quantities of electronic brain imaging archives in ways suitable for hypothesis generation and data mining.

  17. Ethics of neuroimaging after serious brain injury

    PubMed Central

    2014-01-01

    Background Patient outcome after serious brain injury is highly variable. Following a period of coma, some patients recover while others progress into a vegetative state (unresponsive wakefulness syndrome) or minimally conscious state. In both cases, assessment is difficult and misdiagnosis may be as high as 43%. Recent advances in neuroimaging suggest a solution. Both functional magnetic resonance imaging and electroencephalography have been used to detect residual cognitive function in vegetative and minimally conscious patients. Neuroimaging may improve diagnosis and prognostication. These techniques are beginning to be applied to comatose patients soon after injury. Evidence of preserved cognitive function may predict recovery, and this information would help families and health providers. Complex ethical issues arise due to the vulnerability of patients and families, difficulties interpreting negative results, restriction of communication to “yes” or “no” answers, and cost. We seek to investigate ethical issues in the use of neuroimaging in behaviorally nonresponsive patients who have suffered serious brain injury. The objectives of this research are to: (1) create an approach to capacity assessment using neuroimaging; (2) develop an ethics of welfare framework to guide considerations of quality of life; (3) explore the impact of neuroimaging on families; and, (4) analyze the ethics of the use of neuroimaging in comatose patients. Methods/Design Our research program encompasses four projects and uses a mixed methods approach. Project 1 asks whether decision making capacity can be assessed in behaviorally nonresponsive patients. We will specify cognitive functions required for capacity and detail their assessment. Further, we will develop and pilot a series of scenarios and questions suitable for assessing capacity. Project 2 examines the ethics of welfare as a guide for neuroimaging. It grounds an obligation to explore patients’ interests, and we

  18. Biochemical and neuroimaging studies in subjective cognitive decline: progress and perspectives.

    PubMed

    Sun, Yu; Yang, Fu-Chi; Lin, Ching-Po; Han, Ying

    2015-10-01

    Neurodegeneration due to Alzheimer's disease (AD) can progress over decades before dementia becomes apparent. Indeed, patients with mild cognitive impairment (MCI) already demonstrate significant lesion loads. In most cases, MCI is preceded by subjective cognitive decline (SCD), which is applied to individuals who have self-reported memory-related complaints and has been associated with a higher risk of future cognitive decline and conversion to dementia. Based on the schema of a well-received model of biomarker dynamics in AD pathogenesis, it has been postulated that SCD symptoms may result from compensatory changes in response to β-amyloid accumulation and neurodegeneration. Although SCD is considered a prodromal stage of MCI, it is also a common manifestation in old age, independent of AD, and the predictive value of SCD for AD pathology remains controversial. Here, we provide a review focused on the contributions of cross-sectional and longitudinal analogical studies of biomarkers and neuroimaging evidence in disentangling under what conditions SCD may be attributable to AD pathology. In conclusion, there is promising evidence indicating that clinicians should be able to differentiate pre-AD SCD based on the presence of pathophysiological biomarkers in cerebrospinal fluid (CSF) and neuroimaging. However, this neuroimaging approach is still at an immature stage without an established rubric of standards. A substantial amount of work remains in terms of replicating recent findings and validating the clinical utility of identifying SCD.

  19. Developments in functional neuroimaging techniques

    SciTech Connect

    Aine, C.J.

    1995-03-01

    A recent review of neuroimaging techniques indicates that new developments have primarily occurred in the area of data acquisition hardware/software technology. For example, new pulse sequences on standard clinical imagers and high-powered, rapidly oscillating magnetic field gradients used in echo planar imaging (EPI) have advanced MRI into the functional imaging arena. Significant developments in tomograph design have also been achieved for monitoring the distribution of positron-emitting radioactive tracers in the body (PET). Detector sizes, which pose a limit on spatial resolution, have become smaller (e.g., 3--5 mm wide) and a new emphasis on volumetric imaging has emerged which affords greater sensitivity for determining locations of positron annihilations and permits smaller doses to be utilized. Electromagnetic techniques have also witnessed growth in the ability to acquire data from the whole head simultaneously. EEG techniques have increased their electrode coverage (e.g., 128 channels rather than 16 or 32) and new whole-head systems are now in use for MEG. But the real challenge now is in the design and implementation of more sophisticated analyses to effectively handle the tremendous amount of physiological/anatomical data that can be acquired. Furthermore, such analyses will be necessary for integrating data across techniques in order to provide a truly comprehensive understanding of the functional organization of the human brain.

  20. Alzheimer's Disease Cerebrospinal Fluid and Neuroimaging Biomarkers: Diagnostic Accuracy and Relationship to Drug Efficacy.

    PubMed

    Khan, Tapan K; Alkon, Daniel L

    2015-01-01

    Widely researched Alzheimer's disease (AD) biomarkers include in vivo brain imaging with PET and MRI, imaging of amyloid plaques, and biochemical assays of Aβ 1 - 42, total tau, and phosphorylated tau (p-tau-181) in cerebrospinal fluid (CSF). In this review, we critically evaluate these biomarkers and discuss their clinical utility for the differential diagnosis of AD. Current AD biomarker tests are either highly invasive (requiring CSF collection) or expensive and labor-intensive (neuroimaging), making them unsuitable for use in the primary care, clinical office-based setting, or to assess drug efficacy in clinical trials. In addition, CSF and neuroimaging biomarkers continue to face challenges in achieving required sensitivity and specificity and minimizing center-to-center variability (for CSF-Aβ 1 - 42 biomarkers CV = 26.5% ; http://www.alzforum.org/news/conference-coverage/paris-standardization-hurdle-spinal-fluid-imaging-markers). Although potentially useful for selecting patient populations for inclusion in AD clinical trials, the utility of CSF biomarkers and neuroimaging techniques as surrogate endpoints of drug efficacy needs to be validated. Recent trials of β- and γ-secretase inhibitors and Aβ immunization-based therapies in AD showed no significant cognitive improvements, despite changes in CSF and neuroimaging biomarkers. As we learn more about the dysfunctional cellular and molecular signaling processes that occur in AD, and how these processes are manifested in tissues outside of the brain, new peripheral biomarkers may also be validated as non-invasive tests to diagnose preclinical and clinical AD. PMID:26402622

  1. Source counting in MEG neuroimaging

    NASA Astrophysics Data System (ADS)

    Lei, Tianhu; Dell, John; Magee, Ralphy; Roberts, Timothy P. L.

    2009-02-01

    Magnetoencephalography (MEG) is a multi-channel, functional imaging technique. It measures the magnetic field produced by the primary electric currents inside the brain via a sensor array composed of a large number of superconducting quantum interference devices. The measurements are then used to estimate the locations, strengths, and orientations of these electric currents. This magnetic source imaging technique encompasses a great variety of signal processing and modeling techniques which include Inverse problem, MUltiple SIgnal Classification (MUSIC), Beamforming (BF), and Independent Component Analysis (ICA) method. A key problem with Inverse problem, MUSIC and ICA methods is that the number of sources must be detected a priori. Although BF method scans the source space on a point-to-point basis, the selection of peaks as sources, however, is finally made by subjective thresholding. In practice expert data analysts often select results based on physiological plausibility. This paper presents an eigenstructure approach for the source number detection in MEG neuroimaging. By sorting eigenvalues of the estimated covariance matrix of the acquired MEG data, the measured data space is partitioned into the signal and noise subspaces. The partition is implemented by utilizing information theoretic criteria. The order of the signal subspace gives an estimate of the number of sources. The approach does not refer to any model or hypothesis, hence, is an entirely data-led operation. It possesses clear physical interpretation and efficient computation procedure. The theoretical derivation of this method and the results obtained by using the real MEG data are included to demonstrates their agreement and the promise of the proposed approach.

  2. Hairy AdS solitons

    NASA Astrophysics Data System (ADS)

    Anabalón, Andrés; Astefanesei, Dumitru; Choque, David

    2016-11-01

    We construct exact hairy AdS soliton solutions in Einstein-dilaton gravity theory. We examine their thermodynamic properties and discuss the role of these solutions for the existence of first order phase transitions for hairy black holes. The negative energy density associated to hairy AdS solitons can be interpreted as the Casimir energy that is generated in the dual filed theory when the fermions are antiperiodic on the compact coordinate.

  3. The RUMBA software: tools for neuroimaging data analysis.

    PubMed

    Bly, Benjamin Martin; Rebbechi, Donovan; Hanson, Stephen Jose; Grasso, Giorgio

    2004-01-01

    The enormous scale and complexity of data sets in functional neuroimaging makes it crucial to have well-designed and flexible software for image processing, modeling, and statistical analysis. At present, researchers must choose between general purpose scientific computing environments (e.g., Splus and Matlab), and specialized human brain mapping packages that implement particular analysis strategies (e.g., AFNI, SPM, VoxBo, FSL or FIASCO). For the vast majority of users in Human Brain Mapping and Cognitive Neuroscience, general purpose computing environments provide an insufficient framework for a complex data-analysis regime. On the other hand, the operational particulars of more specialized neuroimaging analysis packages are difficult or impossible to modify and provide little transparency or flexibility to the user for approaches other than massively multiple comparisons based on inferential statistics derived from linear models. In order to address these problems, we have developed open-source software that allows a wide array of data analysis procedures. The RUMBA software includes programming tools that simplify the development of novel methods, and accommodates data in several standard image formats. A scripting interface, along with programming libraries, defines a number of useful analytic procedures, and provides an interface to data analysis procedures. The software also supports a graphical functional programming environment for implementing data analysis streams based on modular functional components. With these features, the RUMBA software provides researchers programmability, reusability, modular analysis tools, novel data analysis streams, and an analysis environment in which multiple approaches can be contrasted and compared. The RUMBA software retains the flexibility of general scientific computing environments while adding a framework in which both experts and novices can develop and adapt neuroimaging-specific analyses.

  4. Structural Neuroimaging of the Medial Temporal Lobe in Alzheimer's Disease Clinical Trials.

    PubMed

    Menéndez-González, Manuel; de Celis Alonso, Benito; Salas-Pacheco, José; Arias-Carrión, Oscar

    2015-01-01

    Atrophy in the medial temporal lobe (MTA) is being used as a criterion to support a diagnosis of Alzheimer's disease (AD). There are several structural neuroimaging approaches for quantifying MTA, including semiquantitative visual rating scales, volumetry (3D), planimetry (2D), and linear measures (1D). Current applications of structural neuroimaging in Alzheimer's disease clinical trials (ADCTs) incorporate it as a tool for improving the selection of subjects for enrollment or for stratification, for tracking disease progression, or providing evidence of target engagement for new therapeutic agents. It may also be used as a surrogate marker, providing evidence of disease-modifying effects. However, despite the widespread use of volumetric magnetic resonance imaging (MRI) in ADCTs, there are some important challenges and limitations, such as difficulties in the interpretation of results, limitations in translating results into clinical practice, and reproducibility issues, among others. Solutions to these issues may arise from other methodologies that are able to link the results of volumetric MRI from trials with conventional MRIs performed in routine clinical practice (linear or planimetric methods). Also of potential benefit are automated volumetry, using indices for comparing the relative rate of atrophy of different regions instead of absolute rates of atrophy, and combining structural neuroimaging with other biomarkers. In this review, authors present the existing structural neuroimaging approaches for MTA quantification. They then discuss solutions to the limitations of the different techniques as well as the current challenges of the field. Finally, they discuss how the current advances in AD neuroimaging can help AD diagnosis. PMID:26402089

  5. Methodological Approaches in Developmental Neuroimaging Studies

    PubMed Central

    Luna, Beatriz; Velanova, Katerina; Geier, Charles F.

    2010-01-01

    Pediatric neuroimaging is increasingly providing insights into the neural basis of cognitive development. Indeed, we have now arrived at a stage where we can begin to identify optimal methodological and statistical approaches to the acquisition and analysis of developmental imaging data. In this article, we describe a number of these approaches and how their selection impacts the ability to examine and interpret developmental effects. We describe preferred approaches to task selection, definition of age groups, selection of fMRI designs, definition of regions of interest (ROI), optimal baseline measures, and treatment of timecourse data. Consideration of these aspects of developmental neuroimaging reveals that unlike single-group neuroimaging studies, developmental studies pose unique challenges that impact study planning, task design, data analysis, and the interpretation of findings. PMID:20496377

  6. Neuroimaging Studies of Language Production and Comprehension

    PubMed Central

    Gernsbacher, Morton Ann; Kaschak, Michael P.

    2014-01-01

    The 1990s were dubbed the “Decade of the Brain.” During this time there was a marked increase in the amount of neuroimaging work observing how the brain accomplishes many tasks, including the processing of language. In this chapter we review the past 15 years of neuroimaging research on language production and comprehension. The findings of these studies indicate that the processing involved in language use occurs in diffuse brain regions. These regions include Broca’s and Wernicke’s areas, primary auditory and visual cortex, and frontal regions in the left hemisphere, as well as in the right hemisphere homologues to these regions. We conclude the chapter by discussing the future of neuroimaging research into language production and comprehension. PMID:12359916

  7. Neuroimaging Coordination Dynamics in the Sport Sciences

    PubMed Central

    Jantzen, Kelly J.; Oullier, Olivier; Kelso, J.A. Scott

    2008-01-01

    Key methodological issues for designing, analyzing, and interpreting neuroimaging experiments are presented from the perspective of the framework of Coordination Dynamics. To this end, a brief overview of Coordination Dynamics is introduced, including the main concepts of control parameters and collective variables, theoretical modeling, novel experimental paradigms, and cardinal empirical findings. Basic conceptual and methodological issues for the design and implementation of coordination experiments in the context of neuroimaging are discussed. The paper concludes with a presentation of neuroimaging findings central to understanding the neural basis of coordination and addresses their relevance for the sport sciences. The latter include but are not restricted to learning and practice-related issues, the role of mental imagery, and the recovery of function following brain injury. PMID:18602998

  8. Neuroimaging of dementia in 2013: what radiologists need to know.

    PubMed

    Haller, Sven; Garibotto, Valentina; Kövari, Enikö; Bouras, Constantin; Xekardaki, Aikaterini; Rodriguez, Cristelle; Lazarczyk, Maciej Jakub; Giannakopoulos, Panteleimon; Lovblad, Karl-Olof

    2013-12-01

    The structural and functional neuroimaging of dementia have substantially evolved over the last few years. The most common forms of dementia, Alzheimer disease (AD), Lewy body dementia (LBD) and fronto-temporal lobar degeneration (FTLD), have distinct patterns of cortical atrophy and hypometabolism that evolve over time, as reviewed in the first part of this article. The second part discusses unspecific white matter alterations on T2-weighted and fluid-attenuated inversion recovery (FLAIR) images as well as cerebral microbleeds, which often occur during normal aging and may affect cognition. The third part summarises molecular neuroimaging biomarkers recently developed to visualise amyloid deposits, tau protein deposits and neurotransmitter systems. The fourth section reviews the utility of advanced image analysis techniques as predictive biomarkers of cognitive decline in individuals with early symptoms compatible with mild cognitive impairment (MCI). As only about half of MCI cases will progress to clinically overt dementia, whereas the other half remain stable or might even improve, the discrimination of stable versus progressive MCI is of paramount importance for both individual patient treatment and patient selection for clinical trials. The fifth and final part discusses the inter-individual variation in the neurocognitive reserve, which is a potential constraint for all proposed methods.

  9. Value Added?

    ERIC Educational Resources Information Center

    UCLA IDEA, 2012

    2012-01-01

    Value added measures (VAM) uses changes in student test scores to determine how much "value" an individual teacher has "added" to student growth during the school year. Some policymakers, school districts, and educational advocates have applauded VAM as a straightforward measure of teacher effectiveness: the better a teacher, the better students…

  10. Model-based neuroimaging for cognitive computing.

    PubMed

    Poznanski, Roman R

    2009-09-01

    The continuity of the mind is suggested to mean the continuous spatiotemporal dynamics arising from the electrochemical signature of the neocortex: (i) globally through volume transmission in the gray matter as fields of neural activity, and (ii) locally through extrasynaptic signaling between fine distal dendrites of cortical neurons. If the continuity of dynamical systems across spatiotemporal scales defines a stream of consciousness then intentional metarepresentations as templates of dynamic continuity allow qualia to be semantically mapped during neuroimaging of specific cognitive tasks. When interfaced with a computer, such model-based neuroimaging requiring new mathematics of the brain will begin to decipher higher cognitive operations not possible with existing brain-machine interfaces.

  11. The Kraepelinian dichotomy viewed by neuroimaging.

    PubMed

    d'Albis, Marc-Antoine; Houenou, Josselin

    2015-03-01

    The Kraepelinian dichotomy between schizophrenia (SZ) and bipolar disorder (BD) is being challenged by recent epidemiological and biological studies. We performed a comparative review of neuroimaging features in both conditions at several scales: whole-brain and regional volumes, brain activity, connectivity, and networks. Structural volumetric neuroimaging studies suggest a common pattern of volume decreases, but networks studies reveal a clearer distinction between BD and SZ with an altered connectivity generalized to all brain networks in SZ and restricted to limbic, paralimbic, and interhemispheric networks in BD.

  12. Associations between Verbal Learning Slope and Neuroimaging Markers across the Cognitive Aging Spectrum.

    PubMed

    Gifford, Katherine A; Phillips, Jeffrey S; Samuels, Lauren R; Lane, Elizabeth M; Bell, Susan P; Liu, Dandan; Hohman, Timothy J; Romano, Raymond R; Fritzsche, Laura R; Lu, Zengqi; Jefferson, Angela L

    2015-07-01

    A symptom of mild cognitive impairment (MCI) and Alzheimer's disease (AD) is a flat learning profile. Learning slope calculation methods vary, and the optimal method for capturing neuroanatomical changes associated with MCI and early AD pathology is unclear. This study cross-sectionally compared four different learning slope measures from the Rey Auditory Verbal Learning Test (simple slope, regression-based slope, two-slope method, peak slope) to structural neuroimaging markers of early AD neurodegeneration (hippocampal volume, cortical thickness in parahippocampal gyrus, precuneus, and lateral prefrontal cortex) across the cognitive aging spectrum [normal control (NC); (n=198; age=76±5), MCI (n=370; age=75±7), and AD (n=171; age=76±7)] in ADNI. Within diagnostic group, general linear models related slope methods individually to neuroimaging variables, adjusting for age, sex, education, and APOE4 status. Among MCI, better learning performance on simple slope, regression-based slope, and late slope (Trial 2-5) from the two-slope method related to larger parahippocampal thickness (all p-values<.01) and hippocampal volume (p<.01). Better regression-based slope (p<.01) and late slope (p<.01) were related to larger ventrolateral prefrontal cortex in MCI. No significant associations emerged between any slope and neuroimaging variables for NC (p-values ≥.05) or AD (p-values ≥.02). Better learning performances related to larger medial temporal lobe (i.e., hippocampal volume, parahippocampal gyrus thickness) and ventrolateral prefrontal cortex in MCI only. Regression-based and late slope were most highly correlated with neuroimaging markers and explained more variance above and beyond other common memory indices, such as total learning. Simple slope may offer an acceptable alternative given its ease of calculation.

  13. Associations between Verbal Learning Slope and Neuroimaging Markers across the Cognitive Aging Spectrum.

    PubMed

    Gifford, Katherine A; Phillips, Jeffrey S; Samuels, Lauren R; Lane, Elizabeth M; Bell, Susan P; Liu, Dandan; Hohman, Timothy J; Romano, Raymond R; Fritzsche, Laura R; Lu, Zengqi; Jefferson, Angela L

    2015-07-01

    A symptom of mild cognitive impairment (MCI) and Alzheimer's disease (AD) is a flat learning profile. Learning slope calculation methods vary, and the optimal method for capturing neuroanatomical changes associated with MCI and early AD pathology is unclear. This study cross-sectionally compared four different learning slope measures from the Rey Auditory Verbal Learning Test (simple slope, regression-based slope, two-slope method, peak slope) to structural neuroimaging markers of early AD neurodegeneration (hippocampal volume, cortical thickness in parahippocampal gyrus, precuneus, and lateral prefrontal cortex) across the cognitive aging spectrum [normal control (NC); (n=198; age=76±5), MCI (n=370; age=75±7), and AD (n=171; age=76±7)] in ADNI. Within diagnostic group, general linear models related slope methods individually to neuroimaging variables, adjusting for age, sex, education, and APOE4 status. Among MCI, better learning performance on simple slope, regression-based slope, and late slope (Trial 2-5) from the two-slope method related to larger parahippocampal thickness (all p-values<.01) and hippocampal volume (p<.01). Better regression-based slope (p<.01) and late slope (p<.01) were related to larger ventrolateral prefrontal cortex in MCI. No significant associations emerged between any slope and neuroimaging variables for NC (p-values ≥.05) or AD (p-values ≥.02). Better learning performances related to larger medial temporal lobe (i.e., hippocampal volume, parahippocampal gyrus thickness) and ventrolateral prefrontal cortex in MCI only. Regression-based and late slope were most highly correlated with neuroimaging markers and explained more variance above and beyond other common memory indices, such as total learning. Simple slope may offer an acceptable alternative given its ease of calculation. PMID:26219209

  14. Neuroimaging of Central Sensitivity Syndromes: Key Insights from the Scientific Literature.

    PubMed

    Walitt, Brian; Ceko, Marta; Gracely, John L; Gracely, Richard H

    2016-01-01

    Central sensitivity syndromes are characterized by distressing symptoms, such as pain and fatigue, in the absence of clinically obvious pathology. The scientific underpinnings of these disorders are not currently known. Modern neuroimaging techniques promise new insights into mechanisms mediating these postulated syndromes. We review the results of neuroimaging applied to five central sensitivity syndromes: fibromyalgia, chronic fatigue syndrome, irritable bowel syndrome, temporomandibular joint disorder, and vulvodynia syndrome. Neuroimaging studies of basal metabolism, anatomic constitution, molecular constituents, evoked neural activity, and treatment effect are compared across all of these syndromes. Evoked sensory paradigms reveal sensory augmentation to both painful and nonpainful stimulation. This is a transformative observation for these syndromes, which were historically considered to be completely of hysterical or feigned in origin. However, whether sensory augmentation represents the cause of these syndromes, a predisposing factor, an endophenotype, or an epiphenomenon cannot be discerned from the current literature. Further, the result from cross-sectional neuroimaging studies of basal activity, anatomy, and molecular constituency are extremely heterogeneous within and between the syndromes. A defining neuroimaging "signature" cannot be discerned for any of the particular syndromes or for an over-arching central sensitization mechanism common to all of the syndromes. Several issues confound initial attempts to meaningfully measure treatment effects in these syndromes. At this time, the existence of "central sensitivity syndromes" is based more soundly on clinical and epidemiological evidence. A coherent picture of a "central sensitization" mechanism that bridges across all of these syndromes does not emerge from the existing scientific evidence. PMID:26717948

  15. Ethics Analysis of Neuroimaging in Alzheimer’s Disease

    PubMed Central

    Illes, J.; Rosen, A.; Greicius, M.; Racine, E.

    2009-01-01

    This article focuses on the prospects and ethics of using neuroimaging to predict Alzheimer’s disease (AD). It is motivated by consideration of the historical roles of science in medicine and society, and considerations specifically contemporary of capabilities in imaging and aging, and the benefits and hope they bring. A general consensus is that combinations of imaging methods will ultimately be most fruitful in predicting disease. Their roll-out into translational practice will not be free of complexity, however, as culture and values differ in terms of what defines benefit and risk, who will benefit and who is at risk, what methods must be in place to assure the maximum safety, comfort, and protection of subjects and patients, and educational and policy needs. Proactive planning for the ethical and societal implications of predicting diseases of the aging brain is critical and will benefit all stakeholders— researchers, patients and families, health care providers, and policy makers. PMID:17413029

  16. Neuroimaging studies of social cognition in schizophrenia.

    PubMed

    Fujiwara, Hironobu; Yassin, Walid; Murai, Toshiya

    2015-05-01

    Impaired social cognition is considered a core contributor to unfavorable psychosocial functioning in schizophrenia. Rather than being a unitary process, social cognition is a collection of multifaceted processes that recruit multiple brain structures, thus structural and functional neuroimaging techniques are ideal methodologies for revealing the underlying pathophysiology of impaired social cognition. Many neuroimaging studies have suggested that in addition to white-matter deficits, schizophrenia is associated with decreased gray-matter volume in multiple brain areas, especially fronto-temporal and limbic regions. However, few schizophrenia studies have examined associations between brain abnormalities and social cognitive disabilities. During the last decade, we have investigated structural brain abnormalities in schizophrenia using high-resolution magnetic resonance imaging, and our findings have been confirmed by us and others. By assessing different types of social cognitive abilities, structural abnormalities in multiple brain regions have been found to be associated with disabilities in social cognition, such as recognition of facial emotion, theory of mind, and empathy. These structural deficits have also been associated with alexithymia and quality of life in ways that are closely related to the social cognitive disabilities found in schizophrenia. Here, we overview a series of neuroimaging studies from our laboratory that exemplify current research into this topic, and discuss how it can be further tackled using recent advances in neuroimaging technology. PMID:25418865

  17. Neuroimaging studies of social cognition in schizophrenia.

    PubMed

    Fujiwara, Hironobu; Yassin, Walid; Murai, Toshiya

    2015-05-01

    Impaired social cognition is considered a core contributor to unfavorable psychosocial functioning in schizophrenia. Rather than being a unitary process, social cognition is a collection of multifaceted processes that recruit multiple brain structures, thus structural and functional neuroimaging techniques are ideal methodologies for revealing the underlying pathophysiology of impaired social cognition. Many neuroimaging studies have suggested that in addition to white-matter deficits, schizophrenia is associated with decreased gray-matter volume in multiple brain areas, especially fronto-temporal and limbic regions. However, few schizophrenia studies have examined associations between brain abnormalities and social cognitive disabilities. During the last decade, we have investigated structural brain abnormalities in schizophrenia using high-resolution magnetic resonance imaging, and our findings have been confirmed by us and others. By assessing different types of social cognitive abilities, structural abnormalities in multiple brain regions have been found to be associated with disabilities in social cognition, such as recognition of facial emotion, theory of mind, and empathy. These structural deficits have also been associated with alexithymia and quality of life in ways that are closely related to the social cognitive disabilities found in schizophrenia. Here, we overview a series of neuroimaging studies from our laboratory that exemplify current research into this topic, and discuss how it can be further tackled using recent advances in neuroimaging technology.

  18. Functional Neuroimaging Studies of Written Sentence Comprehension

    ERIC Educational Resources Information Center

    Caplan, David

    2004-01-01

    Sentences convey relationships between the meanings of words, such as who is accomplishing an action or receiving it. Functional neuroimaging based on positron-emission tomography and functional magnetic resonance imaging has been used to identify areas of the brain involved in structuring sentences and determining aspects of meaning associated…

  19. Neuromarketing: the hope and hype of neuroimaging in business.

    PubMed

    Ariely, Dan; Berns, Gregory S

    2010-04-01

    The application of neuroimaging methods to product marketing - neuromarketing - has recently gained considerable popularity. We propose that there are two main reasons for this trend. First, the possibility that neuroimaging will become cheaper and faster than other marketing methods; and second, the hope that neuroimaging will provide marketers with information that is not obtainable through conventional marketing methods. Although neuroimaging is unlikely to be cheaper than other tools in the near future, there is growing evidence that it may provide hidden information about the consumer experience. The most promising application of neuroimaging methods to marketing may come before a product is even released - when it is just an idea being developed.

  20. Neuromarketing: the hope and hype of neuroimaging in business.

    PubMed

    Ariely, Dan; Berns, Gregory S

    2010-04-01

    The application of neuroimaging methods to product marketing - neuromarketing - has recently gained considerable popularity. We propose that there are two main reasons for this trend. First, the possibility that neuroimaging will become cheaper and faster than other marketing methods; and second, the hope that neuroimaging will provide marketers with information that is not obtainable through conventional marketing methods. Although neuroimaging is unlikely to be cheaper than other tools in the near future, there is growing evidence that it may provide hidden information about the consumer experience. The most promising application of neuroimaging methods to marketing may come before a product is even released - when it is just an idea being developed. PMID:20197790

  1. Neuroimaging biomarkers for early drug development in schizophrenia.

    PubMed

    Tregellas, Jason R

    2014-07-15

    Given the relative inability of currently available antipsychotic treatments to adequately provide sustained recovery and improve quality of life for patients with schizophrenia, new treatment strategies are urgently needed. One way to improve the therapeutic development process may be an increased use of biomarkers in early clinical trials. Reliable biomarkers that reflect aspects of disease pathophysiology can be used to determine if potential treatment strategies are engaging their desired biological targets. This review evaluates three potential neuroimaging biomarkers: hippocampal hyperactivity, gamma-band deficits, and default network abnormalities. These deficits have been widely replicated in the illness, correlate with measures of positive symptoms, are consistent with models of disease pathology, and have shown initial promise as biomarkers of biological response in early studies of potential treatment strategies. Two key features of these deficits, and a guiding rationale for the focus of this review, are that the deficits are not dependent upon patients' performance of specific cognitive tasks and they have analogues in animal models of schizophrenia, greatly increasing their appeal for use as biomarkers. Using neuroimaging biomarkers such as those proposed here to establish early in the therapeutic development process if treatment strategies are having their intended biological effect in humans may facilitate development of new treatments for schizophrenia. PMID:24094513

  2. Neuroimaging Biomarkers for Early Drug Development in Schizophrenia

    PubMed Central

    Tregellas, Jason R.

    2013-01-01

    Given the relative inability of currently available antipsychotic treatments to adequately provide sustained recovery and improve quality of life for patients with schizophrenia, new treatment strategies are urgently needed. One way to improve the therapeutic development process may be an increased use of biomarkers in early clinical trials. Reliable biomarkers that reflect aspects of disease pathophysiology can be used to determine if potential treatment strategies are engaging their desired biological targets. This review evaluates three potential neuroimaging biomarkers: hippocampal hyperactivity, gamma-band deficits and default network abnormalities. These deficits have been widely replicated in the illness, correlate with measures of positive symptoms, are consistent with models of disease pathology, and have shown initial promise as biomarkers of biological response in early studies of potential treatment strategies. Two key features of these deficits, and a guiding rational for the focus of this review, is that the deficits are not dependent upon patients' performance of specific cognitive tasks, and have analogues in animal models of schizophrenia, greatly increasing their appeal for use as biomarkers. Using neuroimaging biomarkers such as those proposed here to establish early in the therapeutic development process if treatment strategies are having their intended biological effect in humans may facilitate development of new treatments for schizophrenia. PMID:24094513

  3. Multi-source feature learning for joint analysis of incomplete multiple heterogeneous neuroimaging data.

    PubMed

    Yuan, Lei; Wang, Yalin; Thompson, Paul M; Narayan, Vaibhav A; Ye, Jieping

    2012-07-01

    Analysis of incomplete data is a big challenge when integrating large-scale brain imaging datasets from different imaging modalities. In the Alzheimer's Disease Neuroimaging Initiative (ADNI), for example, over half of the subjects lack cerebrospinal fluid (CSF) measurements; an independent half of the subjects do not have fluorodeoxyglucose positron emission tomography (FDG-PET) scans; many lack proteomics measurements. Traditionally, subjects with missing measures are discarded, resulting in a severe loss of available information. In this paper, we address this problem by proposing an incomplete Multi-Source Feature (iMSF) learning method where all the samples (with at least one available data source) can be used. To illustrate the proposed approach, we classify patients from the ADNI study into groups with Alzheimer's disease (AD), mild cognitive impairment (MCI) and normal controls, based on the multi-modality data. At baseline, ADNI's 780 participants (172AD, 397 MCI, 211 NC), have at least one of four data types: magnetic resonance imaging (MRI), FDG-PET, CSF and proteomics. These data are used to test our algorithm. Depending on the problem being solved, we divide our samples according to the availability of data sources, and we learn shared sets of features with state-of-the-art sparse learning methods. To build a practical and robust system, we construct a classifier ensemble by combining our method with four other methods for missing value estimation. Comprehensive experiments with various parameters show that our proposed iMSF method and the ensemble model yield stable and promising results.

  4. Computational analyses of arteriovenous malformations in neuroimaging.

    PubMed

    Di Ieva, Antonio; Boukadoum, Mounir; Lahmiri, Salim; Cusimano, Michael D

    2015-01-01

    Computational models have been investigated for the analysis of the physiopathology and morphology of arteriovenous malformation (AVM) in recent years. Special emphasis has been given to image fusion in multimodal imaging and 3-dimensional rendering of the AVM, with the aim to improve the visualization of the lesion (for diagnostic purposes) and the selection of the nidus (for therapeutic aims, like the selection of the region of interest for the gamma knife radiosurgery plan). Searching for new diagnostic and prognostic neuroimaging biomarkers, fractal-based computational models have been proposed for describing and quantifying the angioarchitecture of the nidus. Computational modeling in the AVM field offers promising tools of analysis and requires a strict collaboration among neurosurgeons, neuroradiologists, clinicians, computer scientists, and engineers. We present here some updated state-of-the-art exemplary cases in the field, focusing on recent neuroimaging computational modeling with clinical relevance, which might offer useful clinical tools for the management of AVMs in the future.

  5. Deep learning for neuroimaging: a validation study

    PubMed Central

    Plis, Sergey M.; Hjelm, Devon R.; Salakhutdinov, Ruslan; Allen, Elena A.; Bockholt, Henry J.; Long, Jeffrey D.; Johnson, Hans J.; Paulsen, Jane S.; Turner, Jessica A.; Calhoun, Vince D.

    2014-01-01

    Deep learning methods have recently made notable advances in the tasks of classification and representation learning. These tasks are important for brain imaging and neuroscience discovery, making the methods attractive for porting to a neuroimager's toolbox. Success of these methods is, in part, explained by the flexibility of deep learning models. However, this flexibility makes the process of porting to new areas a difficult parameter optimization problem. In this work we demonstrate our results (and feasible parameter ranges) in application of deep learning methods to structural and functional brain imaging data. These methods include deep belief networks and their building block the restricted Boltzmann machine. We also describe a novel constraint-based approach to visualizing high dimensional data. We use it to analyze the effect of parameter choices on data transformations. Our results show that deep learning methods are able to learn physiologically important representations and detect latent relations in neuroimaging data. PMID:25191215

  6. Neuroimage evidence and the insanity defense.

    PubMed

    Schweitzer, N J; Saks, Michael J

    2011-01-01

    The introduction of neuroscientific evidence in criminal trials has given rise to fears that neuroimagery presented by an expert witness might inordinately influence jurors' evaluations of the defendant. In this experiment, a diverse sample of 1,170 community members from throughout the U.S. evaluated a written mock trial in which psychological, neuropsychological, neuroscientific, and neuroimage-based expert evidence was presented in support of a not guilty by reason of insanity (NGRI) defense. No evidence of an independent influence of neuroimagery was found. Overall, neuroscience-based evidence was found to be more persuasive than psychological and anecdotal family history evidence. These effects were consistent across different insanity standards. Despite the non-influence of neuroimagery, however, jurors who were not provided with a neuroimage indicated that they believed neuroimagery would have been the most helpful kind of evidence in their evaluations of the defendant.

  7. Fetal Alcohol Spectrum Disorders: Recent Neuroimaging Findings.

    PubMed

    Moore, Eileen M; Migliorini, Robyn; Infante, M Alejandra; Riley, Edward P

    2014-09-01

    Since the identification of Fetal Alcohol Syndrome over 40 years ago, much has been learned about the detrimental effects of prenatal alcohol exposure on the developing brain. This review highlights recent neuroimaging studies, within the context of previous work. Structural magnetic resonance imaging has described morphological differences in the brain and their relationships to cognitive deficits and measures of facial dysmorphology. Diffusion tensor imaging has elaborated on the relationship between white matter microstructure and behavior. Atypical neuromaturation across childhood and adolescence has been observed in longitudinal neuroimaging studies. Functional imaging has revealed differences in neural activation patterns underlying sensory processing, cognition and behavioral deficits. A recent functional connectivity analysis demonstrates reductions in global network efficiency. Despite this progress much remains unknown about the impact of prenatal alcohol exposure on the brain, and continued research efforts are essential. PMID:25346882

  8. Sports concussions and aging: a neuroimaging investigation.

    PubMed

    Tremblay, Sebastien; De Beaumont, Louis; Henry, Luke C; Boulanger, Yvan; Evans, Alan C; Bourgouin, Pierre; Poirier, Judes; Théoret, Hugo; Lassonde, Maryse

    2013-05-01

    Recent epidemiological and experimental studies suggest a link between cognitive decline in late adulthood and sports concussions sustained in early adulthood. In order to provide the first in vivo neuroanatomical evidence of this relation, the present study probes the neuroimaging profile of former athletes with concussions in relation to cognition. Former athletes who sustained their last sports concussion >3 decades prior to testing were compared with those with no history of traumatic brain injury. Participants underwent quantitative neuroimaging (optimized voxel-based morphometry [VBM], hippocampal volume, and cortical thickness), proton magnetic resonance spectroscopy ((1)H MRS; medial temporal lobes and prefrontal cortices), and neuropsychological testing, and they were genotyped for APOE polymorphisms. Relative to controls, former athletes with concussions exhibited: 1) Abnormal enlargement of the lateral ventricles, 2) cortical thinning in regions more vulnerable to the aging process, 3) various neurometabolic anomalies found across regions of interest, 4) episodic memory and verbal fluency decline. The cognitive deficits correlated with neuroimaging findings in concussed participants. This study unveiled brain anomalies in otherwise healthy former athletes with concussions and associated those manifestations to the long-term detrimental effects of sports concussion on cognitive function. Findings from this study highlight patterns of decline often associated with abnormal aging.

  9. Advanced Neuroimaging in Traumatic Brain Injury

    PubMed Central

    Edlow, Brian L.; Wu, Ona

    2013-01-01

    Advances in structural and functional neuroimaging have occurred at a rapid pace over the past two decades. Novel techniques for measuring cerebral blood flow, metabolism, white matter connectivity, and neural network activation have great potential to improve the accuracy of diagnosis and prognosis for patients with traumatic brain injury (TBI), while also providing biomarkers to guide the development of new therapies. Several of these advanced imaging modalities are currently being implemented into clinical practice, whereas others require further development and validation. Ultimately, for advanced neuroimaging techniques to reach their full potential and improve clinical care for the many civilians and military personnel affected by TBI, it is critical for clinicians to understand the applications and methodological limitations of each technique. In this review, we examine recent advances in structural and functional neuroimaging and the potential applications of these techniques to the clinical care of patients with TBI. We also discuss pitfalls and confounders that should be considered when interpreting data from each technique. Finally, given the vast amounts of advanced imaging data that will soon be available to clinicians, we discuss strategies for optimizing data integration, visualization and interpretation. PMID:23361483

  10. Testable Hypotheses for Unbalanced Neuroimaging Data

    PubMed Central

    McFarquhar, Martyn

    2016-01-01

    Unbalanced group-level models are common in neuroimaging. Typically, data for these models come from factorial experiments. As such, analyses typically take the form of an analysis of variance (ANOVA) within the framework of the general linear model (GLM). Although ANOVA theory is well established for the balanced case, in unbalanced designs there are multiple ways of decomposing the sums-of-squares of the data. This leads to several methods of forming test statistics when the model contains multiple factors and interactions. Although the Type I–III sums of squares have a long history of debate in the statistical literature, there has seemingly been no consideration of this aspect of the GLM in neuroimaging. In this paper we present an exposition of these different forms of hypotheses for the neuroimaging researcher, discussing their derivation as estimable functions of ANOVA models, and discussing the relative merits of each. Finally, we demonstrate how the different hypothesis tests can be implemented using contrasts in analysis software, presenting examples in SPM and FSL. PMID:27378839

  11. Neuropsychiatric deep brain stimulation for translational neuroimaging.

    PubMed

    Höflich, Anna; Savli, Markus; Comasco, Erika; Moser, Ulrike; Novak, Klaus; Kasper, Siegfried; Lanzenberger, Rupert

    2013-10-01

    From a neuroimaging point of view, deep brain stimulation (DBS) in psychiatric disorders represents a unique source of information to probe results gained in functional, structural and molecular neuroimaging studies in vivo. However, the implementation has, up to now, been restricted by the heterogeneity of the data reported in DBS studies. The aim of the present study was therefore to provide a comprehensive and standardized database of currently used DBS targets in selected psychiatric disorders (obsessive-compulsive disorder (OCD), treatment-resistant depression (TRD), Gilles de la Tourette syndrome (GTS)) to enable topological comparisons between neuroimaging results and stimulation areas. A systematic literature research was performed and all peer-reviewed publications until the year 2012 were included. Literature research yielded a total of 84 peer-reviewed studies including about 296 psychiatric patients. The individual stimulation data of 37 of these studies meeting the inclusion criteria which included a total of 202 patients (63 OCD, 89 TRD, 50 GTS) was translated into MNI stereotactic space with respect to AC origin in order to identify key targets. The created database can be used to compare DBS target areas in MNI stereotactic coordinates with: 1) activation patterns in functional brain imaging (fMRI, phfMRI, PET, MET, EEG); 2) brain connectivity data (e.g., MR-based DTI/tractography, functional and effective connectivity); 3) quantitative molecular distribution data (e.g., neuroreceptor PET, post-mortem neuroreceptor mapping); 4) structural data (e.g., VBM for neuroplastic changes). Vice versa, the structural, functional and molecular data may provide a rationale to define new DBS targets and adjust/fine-tune currently used targets in DBS based on this overview in stereotactic coordinates. Furthermore, the availability of DBS data in stereotactic space may facilitate the investigation and interpretation of treatment effects and side effect of DBS by

  12. Neuroimaging and Drug Taking in Primates Abbreviated title: Neuroimaging and Drug taking

    PubMed Central

    Murnane, Kevin S.; Howell, Leonard L.

    2011-01-01

    Rationale Neuroimaging techniques have led to significant advances in our understanding of the neurobiology of drug-taking and the treatment of drug addiction in humans. Neuroimaging approaches provide a powerful translational approach that can link findings from humans and laboratory animals. Objective This review describes the utility of neuroimaging toward understanding the neurobiological basis of drug taking, and documents the close concordance that can be achieved among neuroimaging, neurochemical and behavioral endpoints. Results The study of drug interactions with dopamine and serotonin transporters in vivo has identified pharmacological mechanisms of action associated with the abuse liability of stimulants. Neuroimaging has identified the extended limbic system, including the prefrontal cortex and anterior cingulate, as important neuronal circuitry that underlies drug taking. The ability to conduct within-subject, longitudinal assessments of brain chemistry and neuronal function has enhanced our efforts to document long-term changes in dopamine D2 receptors, monoamine transporters, and prefrontal metabolism due to chronic drug exposure. Dysregulation of dopamine function and brain metabolic changes in areas involved in reward circuitry have been linked to drug-taking behavior, cognitive impairment and treatment response. Conclusions Experimental designs employing neuroimaging should consider well-documented determinants of drug taking, including pharmacokinetic considerations, subject history and environmental variables. Methodological issues to consider include limited molecular probes, lack of neurochemical specificity in brain activation studies, and the potential influence of anesthetics in animal studies. Nevertheless, these integrative approaches should have important implications for understanding drug-taking behavior and the treatment of drug addiction. PMID:21360099

  13. Cleavage of Eukaryotic Translation Initiation Factor 4G by Exogenously Added Hybrid Proteins Containing Poliovirus 2Apro in HeLa Cells: Effects on Gene Expression

    PubMed Central

    Novoa, Isabel; Carrasco, Luis

    1999-01-01

    Efficient cleavage of both forms of eukaryotic initiation factor 4G (eIF4G-1 and eIF4G-2) has been achieved in HeLa cells by incubation with hybrid proteins containing poliovirus 2Apro. Entry of these proteins into cells is promoted by adenovirus particles. Substantial levels of ongoing translation on preexisting cellular mRNAs still continue for several hours after eIF4G degradation. Treatment of control HeLa cells with hypertonic medium causes an inhibition of translation that is reversed upon restoration of cells to normal medium. Protein synthesis is not restored in cells lacking intact eIF4G after hypertonic treatment. Notably, induction of synthesis of heat shock proteins still occurs in cells pretreated with poliovirus 2Apro, suggesting that transcription and translation of these mRNAs takes place even in the presence of cleaved eIF4G. Finally, the synthesis of luciferase was examined in a HeLa cell line bearing the luciferase gene under control of a tetracycline-regulated promoter. Transcription of the luciferase gene and transport of the mRNA to the cytoplasm occurs at control levels in eIF4G-deficient cells. However, luciferase synthesis is strongly inhibited in these cells. These findings indicate that intact eIF4G is necessary for the translation of mRNAs not engaged in translation with the exception of heat shock mRNAs but is not necessary for the translation of mRNAs that are being translated. PMID:10082510

  14. Neuroimaging Study Designs, Computational Analyses and Data Provenance Using the LONI Pipeline

    PubMed Central

    Dinov, Ivo; Lozev, Kamen; Petrosyan, Petros; Liu, Zhizhong; Eggert, Paul; Pierce, Jonathan; Zamanyan, Alen; Chakrapani, Shruthi; Van Horn, John; Parker, D. Stott; Magsipoc, Rico; Leung, Kelvin; Gutman, Boris; Woods, Roger; Toga, Arthur

    2010-01-01

    Modern computational neuroscience employs diverse software tools and multidisciplinary expertise to analyze heterogeneous brain data. The classical problems of gathering meaningful data, fitting specific models, and discovering appropriate analysis and visualization tools give way to a new class of computational challenges—management of large and incongruous data, integration and interoperability of computational resources, and data provenance. We designed, implemented and validated a new paradigm for addressing these challenges in the neuroimaging field. Our solution is based on the LONI Pipeline environment [3], [4], a graphical workflow environment for constructing and executing complex data processing protocols. We developed study-design, database and visual language programming functionalities within the LONI Pipeline that enable the construction of complete, elaborate and robust graphical workflows for analyzing neuroimaging and other data. These workflows facilitate open sharing and communication of data and metadata, concrete processing protocols, result validation, and study replication among different investigators and research groups. The LONI Pipeline features include distributed grid-enabled infrastructure, virtualized execution environment, efficient integration, data provenance, validation and distribution of new computational tools, automated data format conversion, and an intuitive graphical user interface. We demonstrate the new LONI Pipeline features using large scale neuroimaging studies based on data from the International Consortium for Brain Mapping [5] and the Alzheimer's Disease Neuroimaging Initiative [6]. User guides, forums, instructions and downloads of the LONI Pipeline environment are available at http://pipeline.loni.ucla.edu. PMID:20927408

  15. Finding a balance between "value added" and feeling valued: revising models of care. The human factor of implementing a quality improvement initiative using Lean methodology within the healthcare sector.

    PubMed

    Deans, Rachel; Wade, Shawna

    2011-01-01

    Growing demand from clients waiting to access vital services in a healthcare sector under economic constraint, coupled with the pressure for ongoing improvement within a multi-faceted organization, can have a significant impact on the front-line staff, who are essential to the successful implementation of any quality improvement initiative. The Lean methodology is a management system for continuous improvement based on the Toyota Production System; it focuses on two main themes: respect for people and the elimination of waste or non-value-added activities. Within the Lean process, value-added is used to describe any activity that contributes directly to satisfying the needs of the client, and non-value-added refers to any activity that takes time, space or resources but does not contribute directly to satisfying client needs. Through the revision of existing models of service delivery, the authors' organization has made an impact on increasing access to care and has supported successful engagement of staff in the process, while ensuring that the focus remains on the central needs of clients and families accessing services. While the performance metrics continue to exhibit respectable results for this strategic priority, further gains are expected over the next 18-24 months.

  16. DIS in AdS

    SciTech Connect

    Albacete, Javier L.; Kovchegov, Yuri V.; Taliotis, Anastasios

    2009-03-23

    We calculate the total cross section for the scattering of a quark-anti-quark dipole on a large nucleus at high energy for a strongly coupled N = 4 super Yang-Mills theory using AdS/CFT correspondence. We model the nucleus by a metric of a shock wave in AdS{sub 5}. We then calculate the expectation value of the Wilson loop (the dipole) by finding the extrema of the Nambu-Goto action for an open string attached to the quark and antiquark lines of the loop in the background of an AdS{sub 5} shock wave. We find two physically meaningful extremal string configurations. For both solutions we obtain the forward scattering amplitude N for the quark dipole-nucleus scattering. We study the onset of unitarity with increasing center-of-mass energy and transverse size of the dipole: we observe that for both solutions the saturation scale Q{sub s} is independent of energy/Bjorken-x and depends on the atomic number of the nucleus as Q{sub s}{approx}A{sup 1/3}. Finally we observe that while one of the solutions we found corresponds to the pomeron intercept of {alpha}{sub P} = 2 found earlier in the literature, when extended to higher energy or larger dipole sizes it violates the black disk limit. The other solution we found respects the black disk limit and yields the pomeron intercept of {alpha}{sub P} = 1.5. We thus conjecture that the right pomeron intercept in gauge theories at strong coupling may be {alpha}{sub P} = 1.5.

  17. LSTGEE: longitudinal analysis of neuroimaging data

    NASA Astrophysics Data System (ADS)

    Li, Yimei; Zhu, Hongtu; Chen, Yasheng; An, Hongyu; Gilmore, John; Lin, Weili; Shen, Dinggang

    2009-02-01

    Longitudinal imaging studies are essential to understanding the neural development of neuropsychiatric disorders, substance use disorders, and normal brain. Using appropriate image processing and statistical tools to analyze the imaging, behavioral, and clinical data is critical for optimally exploring and interpreting the findings from those imaging studies. However, the existing imaging processing and statistical methods for analyzing imaging longitudinal measures are primarily developed for cross-sectional neuroimaging studies. The simple use of these cross-sectional tools to longitudinal imaging studies will significantly decrease the statistical power of longitudinal studies in detecting subtle changes of imaging measures and the causal role of time-dependent covariate in disease process. The main objective of this paper is to develop longitudinal statistics toolbox, called LSTGEE, for the analysis of neuroimaging data from longitudinal studies. We develop generalized estimating equations for jointly modeling imaging measures with behavioral and clinical variables from longitudinal studies. We develop a test procedure based on a score test statistic and a resampling method to test linear hypotheses of unknown parameters, such as associations between brain structure and function and covariates of interest, such as IQ, age, gene, diagnostic groups, and severity of disease. We demonstrate the application of our statistical methods to the detection of the changes of the fractional anisotropy across time in a longitudinal neonate study. Particularly, our results demonstrate that the use of longitudinal statistics can dramatically increase the statistical power in detecting the changes of neuroimaging measures. The proposed approach can be applied to longitudinal data with multiple outcomes and accommodate incomplete and unbalanced data, i.e., subjects with different number of measurements.

  18. Atypical neuroimaging in Wilson’s disease

    PubMed Central

    Patell, Rushad; Dosi, Rupal; Joshi, Harshal K; Storz, Dennis

    2014-01-01

    Wilson's disease is a rare metabolic disease involving copper metabolism. Neuroimaging plays an important part in evaluation of patients with a neuropsychiatric presentation. We present a case of a 14-year-old girl with atypical confluent white matter disease and cystic degeneration on MRI, with a rapidly progressive course, who succumbed to complications despite treatment with trientine. Wilson's disease should be considered as a differential for leucoencephalopathy in young patients with progressive neurological disease for its early recognition and optimum outcome. PMID:24907221

  19. Neuroimaging Features of San Luis Valley Syndrome

    PubMed Central

    Whitehead, Matthew T.; Lee, Bonmyong

    2015-01-01

    A 14-month-old Hispanic female with a history of double-outlet right ventricle and developmental delay in the setting of recombinant chromosome 8 syndrome was referred for neurologic imaging. Brain MR revealed multiple abnormalities primarily affecting midline structures, including commissural dysgenesis, vermian and brainstem hypoplasia/dysplasia, an interhypothalamic adhesion, and an epidermoid between the frontal lobes that enlarged over time. Spine MR demonstrated hypoplastic C1 and C2 posterior elements, scoliosis, and a borderline low conus medullaris position. Presented herein is the first illustration of neuroimaging findings from a patient with San Luis Valley syndrome. PMID:26425383

  20. Practical management of heterogeneous neuroimaging metadata by global neuroimaging data repositories.

    PubMed

    Neu, Scott C; Crawford, Karen L; Toga, Arthur W

    2012-01-01

    Rapidly evolving neuroimaging techniques are producing unprecedented quantities of digital data at the same time that many research studies are evolving into global, multi-disciplinary collaborations between geographically distributed scientists. While networked computers have made it almost trivial to transmit data across long distances, collecting and analyzing this data requires extensive metadata if the data is to be maximally shared. Though it is typically straightforward to encode text and numerical values into files and send content between different locations, it is often difficult to attach context and implicit assumptions to the content. As the number of and geographic separation between data contributors grows to national and global scales, the heterogeneity of the collected metadata increases and conformance to a single standardization becomes implausible. Neuroimaging data repositories must then not only accumulate data but must also consolidate disparate metadata into an integrated view. In this article, using specific examples from our experiences, we demonstrate how standardization alone cannot achieve full integration of neuroimaging data from multiple heterogeneous sources and why a fundamental change in the architecture of neuroimaging data repositories is needed instead. PMID:22470336

  1. Multi-Modal Neuroimaging Feature Learning for Multi-Class Diagnosis of Alzheimer’s Disease

    PubMed Central

    Liu, Siqi; Liu, Sidong; Cai, Weidong; Che, Hangyu; Pujol, Sonia; Kikinis, Ron; Feng, Dagan; Fulham, Michael J.

    2015-01-01

    The accurate diagnosis of Alzheimers disease (AD) is essential for patient care and will be increasingly important as disease modifying agents become available, early in the course of the disease. Although studies have applied machine learning methods for the computer aided diagnosis (CAD) of AD, a bottleneck in the diagnostic performance was shown in previous methods, due to the lacking of efficient strategies for representing neuroimaging biomarkers. In this study, we designed a novel diagnostic framework with deep learning architecture to aid the diagnosis of AD. This framework uses a zero-masking strategy for data fusion to extract complementary information from multiple data modalities. Compared to the previous state-of-the-art workflows, our method is capable of fusing multi-modal neuroimaging features in one setting and has the potential to require less labelled data. A performance gain was achieved in both binary classification and multi-class classification of AD. The advantages and limitations of the proposed framework are discussed. PMID:25423647

  2. Neuroimaging of Central Sensitivity Syndromes: Key Insights from the Scientific Literature

    PubMed Central

    Walitt, Brian; Čeko, Marta; Gracely, John L.; Gracely, Richard H.

    2016-01-01

    Central sensitivity syndromes are characterized by distressing symptoms, such as pain and fatigue, in the absence of clinically obvious pathology. The scientific underpinnings of these disorders are not currently known. Modern neuroimaging techniques promise new insights into mechanisms mediating these postulated syndromes. We review the results of neuroimaging applied to five central sensitivity syndromes: fibromyalgia, chronic fatigue syndrome, irritable bowel syndrome, temporomandibular joint disorder, and vulvodynia syndrome. Neuroimaging studies of basal metabolism, anatomic constitution, molecular constituents, evoked neural activity, and treatment effect are compared across all of these syndromes. Evoked sensory paradigms reveal sensory augmentation to both painful and non-painful stimulation. This is a transformative observation for these syndromes, which were historically considered to be completely of hysterical or feigned in origin. However, whether sensory augmentation represents the cause of these syndromes, a predisposing factor, an endophenotype, or an epiphenomenon cannot be discerned from the current literature. Further, the result from cross-sectional neuroimaging studies of basal activity, anatomy, and molecular constituency are extremely heterogeneous within and between the syndromes. A defining neuroimaging “signature” cannot be discerned for any of the particular syndromes or for an over-arching central sensitization mechanism common to all of the syndromes. Several issues confound initial attempts to meaningfully measure treatment effects in these syndromes. At this time, the existence of “central sensitivity syndromes” is based more soundly on clinical and epidemiological evidence. A coherent picture of a “central sensitization” mechanism that bridges across all of these syndromes does not emerge from the existing scientific evidence. PMID:26717948

  3. Fast Optimal Transport Averaging of Neuroimaging Data.

    PubMed

    Gramfort, A; Peyré, G; Cuturi, M

    2015-01-01

    Knowing how the Human brain is anatomically and functionally organized at the level of a group of healthy individuals or patients is the primary goal of neuroimaging research. Yet computing an average of brain imaging data defined over a voxel grid or a triangulation remains a challenge. Data are large, the geometry of the brain is complex and the between subjects variability leads to spatially or temporally non-overlapping effects of interest. To address the problem of variability, data are commonly smoothed before performing a linear group averaging. In this work we build on ideas originally introduced by Kantorovich to propose a new algorithm that can average efficiently non-normalized data defined over arbitrary discrete domains using transportation metrics. We show how Kantorovich means can be linked to Wasserstein barycenters in order to take advantage of the entropic smoothing approach used by. It leads to a smooth convex optimization problem and an algorithm with strong convergence guarantees. We illustrate the versatility of this tool and its empirical behavior on functional neuroimaging data, functional MRI and magnetoencephalography (MEG) source estimates, defined on voxel grids and triangulations of the folded cortical surface. PMID:26221679

  4. Speeding up Permutation Testing in Neuroimaging.

    PubMed

    Hinrichs, Chris; Ithapu, Vamsi K; Sun, Qinyuan; Johnson, Sterling C; Singh, Vikas

    2013-01-01

    Multiple hypothesis testing is a significant problem in nearly all neuroimaging studies. In order to correct for this phenomena, we require a reliable estimate of the Family-Wise Error Rate (FWER). The well known Bonferroni correction method, while simple to implement, is quite conservative, and can substantially under-power a study because it ignores dependencies between test statistics. Permutation testing, on the other hand, is an exact, non-parametric method of estimating the FWER for a given α-threshold, but for acceptably low thresholds the computational burden can be prohibitive. In this paper, we show that permutation testing in fact amounts to populating the columns of a very large matrix P. By analyzing the spectrum of this matrix, under certain conditions, we see that P has a low-rank plus a low-variance residual decomposition which makes it suitable for highly sub-sampled - on the order of 0.5% - matrix completion methods. Based on this observation, we propose a novel permutation testing methodology which offers a large speedup, without sacrificing the fidelity of the estimated FWER. Our evaluations on four different neuroimaging datasets show that a computational speedup factor of roughly 50× can be achieved while recovering the FWER distribution up to very high accuracy. Further, we show that the estimated α-threshold is also recovered faithfully, and is stable. PMID:25309108

  5. Reproducibility of neuroimaging analyses across operating systems

    PubMed Central

    Glatard, Tristan; Lewis, Lindsay B.; Ferreira da Silva, Rafael; Adalat, Reza; Beck, Natacha; Lepage, Claude; Rioux, Pierre; Rousseau, Marc-Etienne; Sherif, Tarek; Deelman, Ewa; Khalili-Mahani, Najmeh; Evans, Alan C.

    2015-01-01

    Neuroimaging pipelines are known to generate different results depending on the computing platform where they are compiled and executed. We quantify these differences for brain tissue classification, fMRI analysis, and cortical thickness (CT) extraction, using three of the main neuroimaging packages (FSL, Freesurfer and CIVET) and different versions of GNU/Linux. We also identify some causes of these differences using library and system call interception. We find that these packages use mathematical functions based on single-precision floating-point arithmetic whose implementations in operating systems continue to evolve. While these differences have little or no impact on simple analysis pipelines such as brain extraction and cortical tissue classification, their accumulation creates important differences in longer pipelines such as subcortical tissue classification, fMRI analysis, and cortical thickness extraction. With FSL, most Dice coefficients between subcortical classifications obtained on different operating systems remain above 0.9, but values as low as 0.59 are observed. Independent component analyses (ICA) of fMRI data differ between operating systems in one third of the tested subjects, due to differences in motion correction. With Freesurfer and CIVET, in some brain regions we find an effect of build or operating system on cortical thickness. A first step to correct these reproducibility issues would be to use more precise representations of floating-point numbers in the critical sections of the pipelines. The numerical stability of pipelines should also be reviewed. PMID:25964757

  6. The structural neuroimaging of bipolar disorder.

    PubMed

    Emsell, Louise; McDonald, Colm

    2009-01-01

    There is an increasing body of literature fuelled by advances in high-resolution structural MRI acquisition and image processing techniques which implicates subtle neuroanatomical abnormalities in the aetiopathogenesis of bipolar disorder. This account reviews the main findings from structural neuroimaging research into regional brain abnormalities, the impact of genetic liability and mood stabilizing medication on brain structure in bipolar disorder, and the overlapping structural deviations found in the allied disorders of schizophrenia and depression. The manifold challenges extant within neuroimaging research are highlighted with accompanying recommendations for future studies. The most consistent findings include preservation of total cerebral volume with regional grey and white matter structural changes in prefrontal, midline and anterior limbic networks, non-contingent ventriculomegaly and increased rates of white matter hyperintensities, with more pronounced deficits in juveniles suffering from the illness. There is increasing evidence that medication has observable effects on brain structure, whereby lithium status is associated with volumetric increase in the medial temporal lobe and anterior cingulate gyrus. However, research continues to be confounded by the use of highly heterogeneous methodology and clinical populations, in studies employing small scale, low-powered, cross-sectional designs. Future work should investigate larger, clinically homogenous groups of patients and unaffected relatives, combining both categorical and dimensional approaches to illness classification in cross-sectional and longitudinal designs in order to elucidate trait versus state mechanisms, genetic effects and medication/illness progression effects over time. PMID:20374145

  7. J'accuse! depression as a likely culprit in cases of AD.

    PubMed

    Steffens, David C

    2016-09-01

    Clinicians have long appreciated the links between depression, cognitive impairment, and development of Alzheimer's disease (AD) and other dementias. More recently, investigators in the fields of epidemiology, genetics, neuroimaging, and neuropathology have sought to quantify the risk and to understand the underlying neurobiology of the relationship between depression and AD. PMID:27460509

  8. Can Emotional and Behavioral Dysregulation in Youth Be Decoded from Functional Neuroimaging?

    PubMed Central

    Portugal, Liana C. L.; Rosa, Maria João; Rao, Anil; Bebko, Genna; Bertocci, Michele A.; Hinze, Amanda K.; Bonar, Lisa; Almeida, Jorge R. C.; Perlman, Susan B.; Versace, Amelia; Schirda, Claudiu; Travis, Michael; Gill, Mary Kay; Demeter, Christine; Diwadkar, Vaibhav A.; Ciuffetelli, Gary; Rodriguez, Eric; Forbes, Erika E.; Sunshine, Jeffrey L.; Holland, Scott K.; Kowatch, Robert A.; Birmaher, Boris; Axelson, David; Horwitz, Sarah M.; Arnold, Eugene L.; Fristad, Mary A.; Youngstrom, Eric A.; Findling, Robert L.; Pereira, Mirtes; Oliveira, Leticia; Phillips, Mary L.; Mourao-Miranda, Janaina

    2016-01-01

    Introduction High comorbidity among pediatric disorders characterized by behavioral and emotional dysregulation poses problems for diagnosis and treatment, and suggests that these disorders may be better conceptualized as dimensions of abnormal behaviors. Furthermore, identifying neuroimaging biomarkers related to dimensional measures of behavior may provide targets to guide individualized treatment. We aimed to use functional neuroimaging and pattern regression techniques to determine whether patterns of brain activity could accurately decode individual-level severity on a dimensional scale measuring behavioural and emotional dysregulation at two different time points. Methods A sample of fifty-seven youth (mean age: 14.5 years; 32 males) was selected from a multi-site study of youth with parent-reported behavioral and emotional dysregulation. Participants performed a block-design reward paradigm during functional Magnetic Resonance Imaging (fMRI). Pattern regression analyses consisted of Relevance Vector Regression (RVR) and two cross-validation strategies implemented in the Pattern Recognition for Neuroimaging toolbox (PRoNTo). Medication was treated as a binary confounding variable. Decoded and actual clinical scores were compared using Pearson’s correlation coefficient (r) and mean squared error (MSE) to evaluate the models. Permutation test was applied to estimate significance levels. Results Relevance Vector Regression identified patterns of neural activity associated with symptoms of behavioral and emotional dysregulation at the initial study screen and close to the fMRI scanning session. The correlation and the mean squared error between actual and decoded symptoms were significant at the initial study screen and close to the fMRI scanning session. However, after controlling for potential medication effects, results remained significant only for decoding symptoms at the initial study screen. Neural regions with the highest contribution to the pattern

  9. Turner Syndrome: Neuroimaging Findings--Structural and Functional

    ERIC Educational Resources Information Center

    Mullaney, Ronan; Murphy, Declan

    2009-01-01

    Neuroimaging studies of Turner syndrome can advance our understanding of the X chromosome in brain development, and the modulatory influence of endocrine factors. There is increasing evidence from neuroimaging studies that TX individuals have significant differences in the anatomy, function, and metabolism of a number of brain regions; including…

  10. Cognitive Neuroimaging: Cognitive Science out of the Armchair

    ERIC Educational Resources Information Center

    de Zubicaray, Greig I.

    2006-01-01

    Cognitive scientists were not quick to embrace the functional neuroimaging technologies that emerged during the late 20th century. In this new century, cognitive scientists continue to question, not unreasonably, the relevance of functional neuroimaging investigations that fail to address questions of interest to cognitive science. However, some…

  11. Childhood-Onset Schizophrenia: Insights from Neuroimaging Studies

    ERIC Educational Resources Information Center

    Gogtay, Nitin; Rapoport, Judith L.

    2008-01-01

    The use of longitudinal neuroimaging to study the developmental perspectives of brain pathology in children with childhood-onset schizophrenia (COS) is described. Structural neuroimaging is capable of providing evidence of neurobiological specificity of COS to distinguish it from other brain abnormalities seen in neuropsychiatric illnesses like…

  12. Advances in neuroimaging research of schizophrenia in China

    PubMed Central

    LIU, Dengtang; XU, Yifeng; JIANG, Kaida

    2014-01-01

    Summary Since Hounsfield’s first report about X-ray computed tomography (CT) in 1972, there has been substantial progress in the application of neuroimaging techniques to study the structure, function, and biochemistry of the brain. This review provides a summary of recent research in structural and functional neuroimaging of schizophrenia in China and four tables describing all of the relevant studies from mainland China. The first research report using neuroimaging techniques in China dates back to 1983, a study that reported encephalatrophy in 30% of individuals with schizophrenia. Functional neuroimaging research in China emerged in the 1990s and has undergone rapid development since. Recently, structural and functional brain networks has become a hot topic among China’s neuroimaging researchers. PMID:25317005

  13. A Review on the Bioinformatics Tools for Neuroimaging

    PubMed Central

    MAN, Mei Yen; ONG, Mei Sin; Mohamad, Mohd Saberi; DERIS, Safaai; SULONG, Ghazali; YUNUS, Jasmy; CHE HARUN, Fauzan Khairi

    2015-01-01

    Neuroimaging is a new technique used to create images of the structure and function of the nervous system in the human brain. Currently, it is crucial in scientific fields. Neuroimaging data are becoming of more interest among the circle of neuroimaging experts. Therefore, it is necessary to develop a large amount of neuroimaging tools. This paper gives an overview of the tools that have been used to image the structure and function of the nervous system. This information can help developers, experts, and users gain insight and a better understanding of the neuroimaging tools available, enabling better decision making in choosing tools of particular research interest. Sources, links, and descriptions of the application of each tool are provided in this paper as well. Lastly, this paper presents the language implemented, system requirements, strengths, and weaknesses of the tools that have been widely used to image the structure and function of the nervous system. PMID:27006633

  14. Neuromarketing: the hope and hype of neuroimaging in business

    PubMed Central

    Ariely, Dan; Berns, Gregory S.

    2010-01-01

    The application of neuroimaging methods to product marketing — neuromarketing — has recently gained considerable popularity. We propose that there are two main reasons for this trend. First, the possibility that neuroimaging will become cheaper and faster than other marketing methods; and second, the hope that neuroimaging will provide marketers with information that is not obtainable through conventional marketing methods. Although neuroimaging is unlikely to be cheaper than other tools in the near future, there is growing evidence that it may provide hidden information about the consumer experience. The most promising application of neuroimaging methods to marketing may come before a product is even released — when it is just an idea being developed. PMID:20197790

  15. Neuropathology of mild traumatic brain injury: relationship to neuroimaging findings.

    PubMed

    Bigler, Erin D; Maxwell, William L

    2012-06-01

    Neuroimaging identified abnormalities associated with traumatic brain injury (TBI) are but gross indicators that reflect underlying trauma-induced neuropathology at the cellular level. This review examines how cellular pathology relates to neuroimaging findings with the objective of more closely relating how neuroimaging findings reveal underlying neuropathology. Throughout this review an attempt will be made to relate what is directly known from post-mortem microscopic and gross anatomical studies of TBI of all severity levels to the types of lesions and abnormalities observed in contemporary neuroimaging of TBI, with an emphasis on mild traumatic brain injury (mTBI). However, it is impossible to discuss the neuropathology of mTBI without discussing what occurs with more severe injury and viewing pathological changes on some continuum from the mildest to the most severe. Historical milestones in understanding the neuropathology of mTBI are reviewed along with implications for future directions in the examination of neuroimaging and neuropathological correlates of TBI.

  16. Neuroimaging-based biomarkers in psychiatry: clinical opportunities of a paradigm shift.

    PubMed

    Fu, Cynthia H Y; Costafreda, Sergi G

    2013-09-01

    Neuroimaging research has substantiated the functional and structural abnormalities underlying psychiatric disorders but has, thus far, failed to have a significant impact on clinical practice. Recently, neuroimaging-based diagnoses and clinical predictions derived from machine learning analysis have shown significant potential for clinical translation. This review introduces the key concepts of this approach, including how the multivariate integration of patterns of brain abnormalities is a crucial component. We survey recent findings that have potential application for diagnosis, in particular early and differential diagnoses in Alzheimer disease and schizophrenia, and the prediction of clinical response to treatment in depression. We discuss the specific clinical opportunities and the challenges for developing biomarkers for psychiatry in the absence of a diagnostic gold standard. We propose that longitudinal outcomes, such as early diagnosis and prediction of treatment response, offer definite opportunities for progress. We propose that efforts should be directed toward clinically challenging predictions in which neuroimaging may have added value, compared with the existing standard assessment. We conclude that diagnostic and prognostic biomarkers will be developed through the joint application of expert psychiatric knowledge in addition to advanced methods of analysis.

  17. Integrated feature extraction and selection for neuroimage classification

    NASA Astrophysics Data System (ADS)

    Fan, Yong; Shen, Dinggang

    2009-02-01

    Feature extraction and selection are of great importance in neuroimage classification for identifying informative features and reducing feature dimensionality, which are generally implemented as two separate steps. This paper presents an integrated feature extraction and selection algorithm with two iterative steps: constrained subspace learning based feature extraction and support vector machine (SVM) based feature selection. The subspace learning based feature extraction focuses on the brain regions with higher possibility of being affected by the disease under study, while the possibility of brain regions being affected by disease is estimated by the SVM based feature selection, in conjunction with SVM classification. This algorithm can not only take into account the inter-correlation among different brain regions, but also overcome the limitation of traditional subspace learning based feature extraction methods. To achieve robust performance and optimal selection of parameters involved in feature extraction, selection, and classification, a bootstrapping strategy is used to generate multiple versions of training and testing sets for parameter optimization, according to the classification performance measured by the area under the ROC (receiver operating characteristic) curve. The integrated feature extraction and selection method is applied to a structural MR image based Alzheimer's disease (AD) study with 98 non-demented and 100 demented subjects. Cross-validation results indicate that the proposed algorithm can improve performance of the traditional subspace learning based classification.

  18. The Virtual Brain Integrates Computational Modeling and Multimodal Neuroimaging

    PubMed Central

    Schirner, Michael; McIntosh, Anthony R.; Jirsa, Viktor K.

    2013-01-01

    Abstract Brain function is thought to emerge from the interactions among neuronal populations. Apart from traditional efforts to reproduce brain dynamics from the micro- to macroscopic scales, complementary approaches develop phenomenological models of lower complexity. Such macroscopic models typically generate only a few selected—ideally functionally relevant—aspects of the brain dynamics. Importantly, they often allow an understanding of the underlying mechanisms beyond computational reproduction. Adding detail to these models will widen their ability to reproduce a broader range of dynamic features of the brain. For instance, such models allow for the exploration of consequences of focal and distributed pathological changes in the system, enabling us to identify and develop approaches to counteract those unfavorable processes. Toward this end, The Virtual Brain (TVB) (www.thevirtualbrain.org), a neuroinformatics platform with a brain simulator that incorporates a range of neuronal models and dynamics at its core, has been developed. This integrated framework allows the model-based simulation, analysis, and inference of neurophysiological mechanisms over several brain scales that underlie the generation of macroscopic neuroimaging signals. In this article, we describe how TVB works, and we present the first proof of concept. PMID:23442172

  19. DIAGNOSIS-GUIDED METHOD FOR IDENTIFYING MULTI-MODALITY NEUROIMAGING BIOMARKERS ASSOCIATED WITH GENETIC RISK FACTORS IN ALZHEIMER'S DISEASE.

    PubMed

    Hao, Xiaoke; Yan, Jingwen; Yao, Xiaohui; Risacher, Shannon L; Saykin, Andrew J; Zhang, Daoqiang; Shen, Li

    2016-01-01

    Many recent imaging genetic studies focus on detecting the associations between genetic markers such as single nucleotide polymorphisms (SNPs) and quantitative traits (QTs). Although there exist a large number of generalized multivariate regression analysis methods, few of them have used diagnosis information in subjects to enhance the analysis performance. In addition, few of models have investigated the identification of multi-modality phenotypic patterns associated with interesting genotype groups in traditional methods. To reveal disease-relevant imaging genetic associations, we propose a novel diagnosis-guided multi-modality (DGMM) framework to discover multi-modality imaging QTs that are associated with both Alzheimer's disease (AD) and its top genetic risk factor (i.e., APOE SNP rs429358). The strength of our proposed method is that it explicitly models the priori diagnosis information among subjects in the objective function for selecting the disease-relevant and robust multi-modality QTs associated with the SNP. We evaluate our method on two modalities of imaging phenotypes, i.e., those extracted from structural magnetic resonance imaging (MRI) data and fluorodeoxyglucose positron emission tomography (FDG-PET) data in the Alzheimer's Disease Neuroimaging Initiative (ADNI) database. The experimental results demonstrate that our proposed method not only achieves better performances under the metrics of root mean squared error and correlation coefficient but also can identify common informative regions of interests (ROIs) across multiple modalities to guide the disease-induced biological interpretation, compared with other reference methods.

  20. Systems Biology, Neuroimaging, Neuropsychology, Neuroconnectivity and Traumatic Brain Injury

    PubMed Central

    Bigler, Erin D.

    2016-01-01

    The patient who sustains a traumatic brain injury (TBI) typically undergoes neuroimaging studies, usually in the form of computed tomography (CT) and magnetic resonance imaging (MRI). In most cases the neuroimaging findings are clinically assessed with descriptive statements that provide qualitative information about the presence/absence of visually identifiable abnormalities; though little if any of the potential information in a scan is analyzed in any quantitative manner, except in research settings. Fortunately, major advances have been made, especially during the last decade, in regards to image quantification techniques, especially those that involve automated image analysis methods. This review argues that a systems biology approach to understanding quantitative neuroimaging findings in TBI provides an appropriate framework for better utilizing the information derived from quantitative neuroimaging and its relation with neuropsychological outcome. Different image analysis methods are reviewed in an attempt to integrate quantitative neuroimaging methods with neuropsychological outcome measures and to illustrate how different neuroimaging techniques tap different aspects of TBI-related neuropathology. Likewise, how different neuropathologies may relate to neuropsychological outcome is explored by examining how damage influences brain connectivity and neural networks. Emphasis is placed on the dynamic changes that occur following TBI and how best to capture those pathologies via different neuroimaging methods. However, traditional clinical neuropsychological techniques are not well suited for interpretation based on contemporary and advanced neuroimaging methods and network analyses. Significant improvements need to be made in the cognitive and behavioral assessment of the brain injured individual to better interface with advances in neuroimaging-based network analyses. By viewing both neuroimaging and neuropsychological processes within a systems biology

  1. Systems Biology, Neuroimaging, Neuropsychology, Neuroconnectivity and Traumatic Brain Injury.

    PubMed

    Bigler, Erin D

    2016-01-01

    The patient who sustains a traumatic brain injury (TBI) typically undergoes neuroimaging studies, usually in the form of computed tomography (CT) and magnetic resonance imaging (MRI). In most cases the neuroimaging findings are clinically assessed with descriptive statements that provide qualitative information about the presence/absence of visually identifiable abnormalities; though little if any of the potential information in a scan is analyzed in any quantitative manner, except in research settings. Fortunately, major advances have been made, especially during the last decade, in regards to image quantification techniques, especially those that involve automated image analysis methods. This review argues that a systems biology approach to understanding quantitative neuroimaging findings in TBI provides an appropriate framework for better utilizing the information derived from quantitative neuroimaging and its relation with neuropsychological outcome. Different image analysis methods are reviewed in an attempt to integrate quantitative neuroimaging methods with neuropsychological outcome measures and to illustrate how different neuroimaging techniques tap different aspects of TBI-related neuropathology. Likewise, how different neuropathologies may relate to neuropsychological outcome is explored by examining how damage influences brain connectivity and neural networks. Emphasis is placed on the dynamic changes that occur following TBI and how best to capture those pathologies via different neuroimaging methods. However, traditional clinical neuropsychological techniques are not well suited for interpretation based on contemporary and advanced neuroimaging methods and network analyses. Significant improvements need to be made in the cognitive and behavioral assessment of the brain injured individual to better interface with advances in neuroimaging-based network analyses. By viewing both neuroimaging and neuropsychological processes within a systems biology

  2. Systems Biology, Neuroimaging, Neuropsychology, Neuroconnectivity and Traumatic Brain Injury.

    PubMed

    Bigler, Erin D

    2016-01-01

    The patient who sustains a traumatic brain injury (TBI) typically undergoes neuroimaging studies, usually in the form of computed tomography (CT) and magnetic resonance imaging (MRI). In most cases the neuroimaging findings are clinically assessed with descriptive statements that provide qualitative information about the presence/absence of visually identifiable abnormalities; though little if any of the potential information in a scan is analyzed in any quantitative manner, except in research settings. Fortunately, major advances have been made, especially during the last decade, in regards to image quantification techniques, especially those that involve automated image analysis methods. This review argues that a systems biology approach to understanding quantitative neuroimaging findings in TBI provides an appropriate framework for better utilizing the information derived from quantitative neuroimaging and its relation with neuropsychological outcome. Different image analysis methods are reviewed in an attempt to integrate quantitative neuroimaging methods with neuropsychological outcome measures and to illustrate how different neuroimaging techniques tap different aspects of TBI-related neuropathology. Likewise, how different neuropathologies may relate to neuropsychological outcome is explored by examining how damage influences brain connectivity and neural networks. Emphasis is placed on the dynamic changes that occur following TBI and how best to capture those pathologies via different neuroimaging methods. However, traditional clinical neuropsychological techniques are not well suited for interpretation based on contemporary and advanced neuroimaging methods and network analyses. Significant improvements need to be made in the cognitive and behavioral assessment of the brain injured individual to better interface with advances in neuroimaging-based network analyses. By viewing both neuroimaging and neuropsychological processes within a systems biology

  3. Hierarchical Interactions Model for Predicting Mild Cognitive Impairment (MCI) to Alzheimer's Disease (AD) Conversion

    PubMed Central

    Li, Han; Liu, Yashu; Gong, Pinghua; Zhang, Changshui; Ye, Jieping

    2014-01-01

    Identifying patients with Mild Cognitive Impairment (MCI) who are likely to convert to dementia has recently attracted increasing attention in Alzheimer's disease (AD) research. An accurate prediction of conversion from MCI to AD can aid clinicians to initiate treatments at early stage and monitor their effectiveness. However, existing prediction systems based on the original biosignatures are not satisfactory. In this paper, we propose to fit the prediction models using pairwise biosignature interactions, thus capturing higher-order relationship among biosignatures. Specifically, we employ hierarchical constraints and sparsity regularization to prune the high-dimensional input features. Based on the significant biosignatures and underlying interactions identified, we build classifiers to predict the conversion probability based on the selected features. We further analyze the underlying interaction effects of different biosignatures based on the so-called stable expectation scores. We have used 293 MCI subjects from Alzheimer's Disease Neuroimaging Initiative (ADNI) database that have MRI measurements at the baseline to evaluate the effectiveness of the proposed method. Our proposed method achieves better classification performance than state-of-the-art methods. Moreover, we discover several significant interactions predictive of MCI-to-AD conversion. These results shed light on improving the prediction performance using interaction features. PMID:24416143

  4. Obesity is linked with lower brain volume in 700 AD and MCI patients

    PubMed Central

    Ho, April J.; Raji, Cyrus A.; Becker, James T.; Lopez, Oscar L.; Kuller, Lewis H.; Hua, Xue; Lee, Suh; Hibar, Derrek; Dinov, Ivo D.; Stein, Jason L.; Jack, Clifford R.; Weiner, Michael W.; Toga, Arthur W.; Thompson, Paul M.

    2011-01-01

    Obesity is associated with lower brain volumes in cognitively normal elderly subjects, but no study has yet investigated the effects of obesity on brain structure in patients with mild cognitive impairment (MCI) or Alzheimer’s disease (AD). To determine if higher body mass index (BMI) is associated with brain volume deficits in cognitively impaired elderly subjects, we analyzed brain magnetic resonance imaging (MRI) scans of 700 MCI or AD patients from two different cohorts: the Alzheimer’s Disease Neuroimaging Initiative (ADNI) and the Cardiovascular Health Study-Cognition Study (CHS-CS). Tensor-based morphometry (TBM) was used to create 3-dimensional maps of regional tissue excess or deficits in subjects with MCI (ADNI, N=399; CHS, N=77) and AD (ADNI, N=188; CHS, N=36). In both AD and MCI groups, higher BMI was associated with brain volume deficits in frontal, temporal, parietal, and occipital lobes; the atrophic pattern was consistent in both ADNI and CHS populations. Cardiovascular risk factors, especially obesity, should be considered as influencing brain structure in those already afflicted by cognitive impairment and dementia. PMID:20570405

  5. A coherent neurobiological framework for functional neuroimaging provided by a model integrating compartmentalized energy metabolism.

    PubMed

    Aubert, Agnès; Pellerin, Luc; Magistretti, Pierre J; Costalat, Robert

    2007-03-01

    Functional neuroimaging has undergone spectacular developments in recent years. Paradoxically, its neurobiological bases have remained elusive, resulting in an intense debate around the cellular mechanisms taking place upon activation that could contribute to the signals measured. Taking advantage of a modeling approach, we propose here a coherent neurobiological framework that not only explains several in vitro and in vivo observations but also provides a physiological basis to interpret imaging signals. First, based on a model of compartmentalized energy metabolism, we show that complex kinetics of NADH changes observed in vitro can be accounted for by distinct metabolic responses in two cell populations reminiscent of neurons and astrocytes. Second, extended application of the model to an in vivo situation allowed us to reproduce the evolution of intraparenchymal oxygen levels upon activation as measured experimentally without substantially altering the initial parameter values. Finally, applying the same model to functional neuroimaging in humans, we were able to determine that the early negative component of the blood oxygenation level-dependent response recorded with functional MRI, known as the initial dip, critically depends on the oxidative response of neurons, whereas the late aspects of the signal correspond to a combination of responses from cell types with two distinct metabolic profiles that could be neurons and astrocytes. In summary, our results, obtained with such a modeling approach, support the concept that both neuronal and glial metabolic responses form essential components of neuroimaging signals. PMID:17360498

  6. Spatiotemporal Linear Mixed Effects Modeling for the Mass-univariate Analysis of Longitudinal Neuroimage Data

    PubMed Central

    Bernal-Rusiel, Jorge L.; Reuter, Martin; Greve, Douglas N.; Fischl, Bruce; Sabuncu, Mert R.

    2013-01-01

    We present an extension of the Linear Mixed Effects (LME) modeling approach to be applied to the mass-univariate analysis of longitudinal neuroimaging (LNI) data. The proposed method, called spatiotemporal LME or ST-LME, builds on the flexible LME framework and exploits the spatial structure in image data. We instantiated ST-LME for the analysis of cortical surface measurements (e.g. thickness) computed by FreeSurfer, a widely-used brain Magnetic Resonance Image (MRI) analysis software package. We validate the proposed ST-LME method and provide a quantitative and objective empirical comparison with two popular alternative methods, using two brain MRI datasets obtained from the Alzheimer’s disease neuroimaging initiative (ADNI) and Open Access Series of Imaging Studies (OASIS). Our experiments revealed that ST-LME offers a dramatic gain in statistical power and repeatability of findings, while providing good control of the false positive rate. PMID:23702413

  7. Common Data Elements for Neuroimaging of Traumatic Brain Injury: Pediatric Considerations

    PubMed Central

    Holshouser, Barbara; Hunter, Jill V.; Tong, Karen

    2012-01-01

    Abstract As part of the Traumatic Brain Injury Common Data Elements project, a large-scale effort to define common data elements across a variety of domains, including neuroimaging, special considerations for pediatric patients were introduced. This article is an extension of that initial work, in which pediatric-specific pathoanatomical entities, technical considerations, interpretation paradigms, and safety considerations were reviewed. The goal of this review was to outline differences and specific information relevant to optimal performance and proper interpretation of neuroimaging in pediatric patients with traumatic brain injury. The long-range goal of this project is to facilitate data sharing as well as to provide critical infrastructure for potential clinical trials in this major public health area. PMID:21671798

  8. How Shakespeare tempests the brain: neuroimaging insights.

    PubMed

    Keidel, James L; Davis, Philip M; Gonzalez-Diaz, Victorina; Martin, Clara D; Thierry, Guillaume

    2013-04-01

    Shakespeare made extensive use of the functional shift (FS), a rhetorical device involving a change in the grammatical status of words, e.g., using nouns as verbs. Previous work using event-related brain potentials showed how FS triggers a surprise effect inviting mental re-evaluation, seemingly independent of semantic processing. Here, we used functional magnetic resonance imaging to investigate brain activation in participants making judgements on the semantic relationship between sentences -some containing a Shakespearean FS- and subsequently presented words. Behavioural performance in the semantic decision task was high and unaffected by sentence type. However, neuroimaging results showed that sentences featuring FS elicited significant activation beyond regions classically activated by typical language tasks, including the left caudate nucleus, the right inferior frontal gyrus and the right inferior temporal gyrus. These findings show how Shakespeare's grammatical exploration forces the listener to take a more active role in integrating the meaning of what is said.

  9. The Human Connectome Project's neuroimaging approach.

    PubMed

    Glasser, Matthew F; Smith, Stephen M; Marcus, Daniel S; Andersson, Jesper L R; Auerbach, Edward J; Behrens, Timothy E J; Coalson, Timothy S; Harms, Michael P; Jenkinson, Mark; Moeller, Steen; Robinson, Emma C; Sotiropoulos, Stamatios N; Xu, Junqian; Yacoub, Essa; Ugurbil, Kamil; Van Essen, David C

    2016-08-26

    Noninvasive human neuroimaging has yielded many discoveries about the brain. Numerous methodological advances have also occurred, though inertia has slowed their adoption. This paper presents an integrated approach to data acquisition, analysis and sharing that builds upon recent advances, particularly from the Human Connectome Project (HCP). The 'HCP-style' paradigm has seven core tenets: (i) collect multimodal imaging data from many subjects; (ii) acquire data at high spatial and temporal resolution; (iii) preprocess data to minimize distortions, blurring and temporal artifacts; (iv) represent data using the natural geometry of cortical and subcortical structures; (v) accurately align corresponding brain areas across subjects and studies; (vi) analyze data using neurobiologically accurate brain parcellations; and (vii) share published data via user-friendly databases. We illustrate the HCP-style paradigm using existing HCP data sets and provide guidance for future research. Widespread adoption of this paradigm should accelerate progress in understanding the brain in health and disease. PMID:27571196

  10. Neuroimaging for drug addiction and related behaviors

    SciTech Connect

    Parvaz M. A.; Parvaz, M.A.; Alia-Klein, N.; Woicik,P.A.; Volkow, N.D.; Goldstein, R.Z.

    2011-10-01

    In this review, we highlight the role of neuroimaging techniques in studying the emotional and cognitive-behavioral components of the addiction syndrome by focusing on the neural substrates subserving them. The phenomenology of drug addiction can be characterized by a recurrent pattern of subjective experiences that includes drug intoxication, craving, bingeing, and withdrawal with the cycle culminating in a persistent preoccupation with obtaining, consuming, and recovering from the drug. In the past two decades, imaging studies of drug addiction have demonstrated deficits in brain circuits related to reward and impulsivity. The current review focuses on studies employing positron emission tomography (PET), functional magnetic resonance imaging (fMRI), and electroencephalography (EEG) to investigate these behaviors in drug-addicted human populations. We begin with a brief account of drug addiction followed by a technical account of each of these imaging modalities. We then discuss how these techniques have uniquely contributed to a deeper understanding of addictive behaviors.

  11. Reduplicative paramnesia: longitudinal neurobehavioral and neuroimaging analysis.

    PubMed

    Moser, D J; Cohen, R A; Malloy, P F; Stone, W M; Rogg, J M

    1998-01-01

    Reduplicative paramnesia (RP) is a delusion in which the patient perceives familiar places, objects, or events to have been duplicated. The current case describes the development of RP in an 81-year-old male following a large right frontal lobe infarction. As the patient had been hospitalized previously with hemorrhagic contusions, neurologic, neuropsychological, and neuroimaging data were obtained both prior to and following RP onset. Psychophysiologic data were obtained following the development of the delusion. Both premorbidly and at follow-up, neuropsychological functioning was characterized by significant impairments of learning and memory and frontal-executive functions. Language and visuospatial skills and motor speed were intact both before and after RP onset. The case is described within the context of preexisting theories of RP, and it is surmised that the delusion is secondary to temporal-limbic-frontal dysfunction giving rise to a distorted sense of familiarity and impaired ability to resolve the delusion via reasoning.

  12. The experience of art: insights from neuroimaging.

    PubMed

    Nadal, Marcos

    2013-01-01

    The experience of art is a complex one. It emerges from the interaction of multiple cognitive and affective processes. Neuropsychological and neuroimaging studies are revealing the broadly distributed network of brain regions upon which it relies. This network can be divided into three functional components: (i) prefrontal, parietal, and temporal cortical regions support evaluative judgment, attentional processing, and memory retrieval; (ii) the reward circuit, including cortical, subcortical regions, and some of its regulators, is involved in the generation of pleasurable feelings and emotions, and the valuation and anticipation of reward; and (iii) attentional modulation of activity in low-, mid-, and high-level cortical sensory regions enhances the perceptual processing of certain features, relations, locations, or objects. Understanding how these regions act in concert to produce unique and moving art experiences and determining the impact of personal and cultural meaning and context on this network the biological foundation of the experience of art--remain future challenges.

  13. The experience of art: insights from neuroimaging.

    PubMed

    Nadal, Marcos

    2013-01-01

    The experience of art is a complex one. It emerges from the interaction of multiple cognitive and affective processes. Neuropsychological and neuroimaging studies are revealing the broadly distributed network of brain regions upon which it relies. This network can be divided into three functional components: (i) prefrontal, parietal, and temporal cortical regions support evaluative judgment, attentional processing, and memory retrieval; (ii) the reward circuit, including cortical, subcortical regions, and some of its regulators, is involved in the generation of pleasurable feelings and emotions, and the valuation and anticipation of reward; and (iii) attentional modulation of activity in low-, mid-, and high-level cortical sensory regions enhances the perceptual processing of certain features, relations, locations, or objects. Understanding how these regions act in concert to produce unique and moving art experiences and determining the impact of personal and cultural meaning and context on this network the biological foundation of the experience of art--remain future challenges. PMID:24041322

  14. Neuroimaging for drug addiction and related behaviors

    PubMed Central

    Parvaz, Muhammad A.; Alia-Klein, Nelly; Woicik, Patricia A.; Volkow, Nora D.; Goldstein, Rita Z.

    2012-01-01

    In this review, we highlight the role of neuroimaging techniques in studying the emotional and cognitive-behavioral components of the addiction syndrome by focusing on the neural substrates subserving them. The phenomenology of drug addiction can be characterized by a recurrent pattern of subjective experiences that includes drug intoxication, craving, bingeing, and withdrawal with the cycle culminating in a persistent preoccupation with obtaining, consuming, and recovering from the drug. In the past two decades, imaging studies of drug addiction have demonstrated deficits in brain circuits related to reward and impulsivity. The current review focuses on studies employing positron emission tomography (PET), functional magnetic resonance imaging (fMRI), and electroencephalography (EEG) to investigate these behaviors in drug-addicted human populations. We begin with a brief account of drug addiction followed by a technical account of each of these imaging modalities. We then discuss how these techniques have uniquely contributed to a deeper understanding of addictive behaviors. PMID:22117165

  15. Neuroimaging of child abuse: a critical review

    PubMed Central

    Hart, Heledd; Rubia, Katya

    2012-01-01

    Childhood maltreatment is a stressor that can lead to the development of behavior problems and affect brain structure and function. This review summarizes the current evidence for the effects of childhood maltreatment on behavior, cognition and the brain in adults and children. Neuropsychological studies suggest an association between child abuse and deficits in IQ, memory, working memory, attention, response inhibition and emotion discrimination. Structural neuroimaging studies provide evidence for deficits in brain volume, gray and white matter of several regions, most prominently the dorsolateral and ventromedial prefrontal cortex but also hippocampus, amygdala, and corpus callosum (CC). Diffusion tensor imaging (DTI) studies show evidence for deficits in structural interregional connectivity between these areas, suggesting neural network abnormalities. Functional imaging studies support this evidence by reporting atypical activation in the same brain regions during response inhibition, working memory, and emotion processing. There are, however, several limitations of the abuse research literature which are discussed, most prominently the lack of control for co-morbid psychiatric disorders, which make it difficult to disentangle which of the above effects are due to maltreatment, the associated psychiatric conditions or a combination or interaction between both. Overall, the better controlled studies that show a direct correlation between childhood abuse and brain measures suggest that the most prominent deficits associated with early childhood abuse are in the function and structure of lateral and ventromedial fronto-limbic brain areas and networks that mediate behavioral and affect control. Future, large scale multimodal neuroimaging studies in medication-naïve subjects, however, are needed that control for psychiatric co-morbidities in order to elucidate the structural and functional brain sequelae that are associated with early environmental adversity

  16. Efficacy of lifestyle interventions on clinical and neuroimaging outcomes in elderly.

    PubMed

    Rolandi, Elena; Frisoni, Giovanni Battista; Cavedo, Enrica

    2016-01-01

    The prevalence of Alzheimer's disease (AD) is constantly growing worldwide in absence of any effective treatment. Methodology and technique advancements facilitated the early diagnosis of AD leading to a shift toward preclinical AD stages investigation in order to delay the disease onset in individuals at risk for AD. Recent evidence demonstrating the aging related multifactorial nature of AD supported the hypothesis that modifiable environmental factors can accelerate or delay the disease onset. In particular, healthy dietary habits, constant physical and cognitive activities are associated with reduced brain atrophy, amyloid load and incidence of AD cases. Due to these promising results, an emerging field of studies is currently investigating the efficacy of interventions addressing different lifestyle habits in cognitive intact elderly individuals as a potential preventive strategy against AD onset. We provide a critical overview of the current evidence on nonpharmacologic treatments in elderly individuals, discussing their efficacy on clinical and neuroimaging outcomes and identifying current methodological issues. Future perspectives, relevant for the scientific community and the worldwide public health institutes will be further discussed.

  17. Cardiac sympathetic neuroimaging: summary of the First International Symposium

    PubMed Central

    Orimo, Satoshi

    2010-01-01

    The First International Symposium on Cardiac Sympathetic Neuroimaging brought together for the first time clinical and preclinical researchers evaluating autonomic and neurocardiologic disorders by this modality. The invited lectures and posters presented some uses of cardiac sympathetic neuroimaging for diagnosis, prognosis, and monitoring treatments. The Symposium also included a discussion about whether and how to expand the availability of cardiac sympathetic neuroimaging at medical centers in the United States. Here, we review the background for the Symposium, provide an annotated summary of the lectures and posters, discuss some of the take-home points from the roundtable discussion, and propose a plan of action for the future. PMID:19266158

  18. Functional neuroimaging and schizophrenia: a view towards effective connectivity modeling and polygenic risk.

    PubMed

    Birnbaum, Rebecca; Weinberger, Daniel R

    2013-09-01

    We review critical trends in imaging genetics as applied to schizophrenia research, and then discuss some future directions of the field. A plethora of imaging genetics studies have investigated the impact of genetic variation on brain function, since the paradigm of a neuroimaging intermediate phenotype for schizophrenia first emerged. It was initially posited that the effects of schizophrenia susceptibility genes would be more penetrant at the level of biologically based neuroimaging intermediate phenotypes than at the level of a complex and phenotypically heterogeneous psychiatric syndrome. The results of many studies support this assumption, most of which show single genetic variants to be associated with changes in activity of localized brain regions, as determined by select cognitive controlled tasks. From these basic studies, functional neuroimaging analysis of intermediate phenotypes has progressed to more complex and realistic models of brain dysfunction, incorporating models of functional and effective connectivity, including the modalities of psycho-physiological interaction, dynamic causal modeling, and graph theory metrics. The genetic association approaches applied to imaging genetics have also progressed to more sophisticated multivariate effects, including incorporation of two-way and three-way epistatic interactions, and most recently polygenic risk models. Imaging genetics is a unique and powerful strategy for understanding the neural mechanisms of genetic risk for complex CNS disorders at the human brain level. PMID:24174900

  19. Functional neuroimaging and schizophrenia: a view towards effective connectivity modeling and polygenic risk

    PubMed Central

    Birnbaum, Rebecca; Weinberger, Daniel R.

    2013-01-01

    We review critical trends in imaging genetics as applied to schizophrenia research, and then discuss some future directions of the field. A plethora of imaging genetics studies have investigated the impact of genetic variation on brain function, since the paradigm of a neuroimaging intermediate phenotype for schizophrenia first emerged. It was initially posited that the effects of schizophrenia susceptibility genes would be more penetrant at the level of biologically based neuroimaging intermediate phenotypes than at the level of a complex and phenotypically heterogeneous psychiatric syndrome. The results of many studies support this assumption, most of which show single genetic variants to be associated with changes in activity of localized brain regions, as determined by select cognitive controlled tasks. From these basic studies, functional neuroimaging analysis of intermediate phenotypes has progressed to more complex and realistic models of brain dysfunction, incorporating models of functional and effective connectivity, including the modalities of psycho-physiological interaction, dynamic causal modeling, and graph theory metrics. The genetic association approaches applied to imaging genetics have also progressed to more sophisticated multivariate effects, including incorporation of two-way and three-way epistatic interactions, and most recently polygenic risk models. Imaging genetics is a unique and powerful strategy for understanding the neural mechanisms of genetic risk for complex CNS disorders at the human brain level. PMID:24174900

  20. Functional neuroimaging and schizophrenia: a view towards effective connectivity modeling and polygenic risk.

    PubMed

    Birnbaum, Rebecca; Weinberger, Daniel R

    2013-09-01

    We review critical trends in imaging genetics as applied to schizophrenia research, and then discuss some future directions of the field. A plethora of imaging genetics studies have investigated the impact of genetic variation on brain function, since the paradigm of a neuroimaging intermediate phenotype for schizophrenia first emerged. It was initially posited that the effects of schizophrenia susceptibility genes would be more penetrant at the level of biologically based neuroimaging intermediate phenotypes than at the level of a complex and phenotypically heterogeneous psychiatric syndrome. The results of many studies support this assumption, most of which show single genetic variants to be associated with changes in activity of localized brain regions, as determined by select cognitive controlled tasks. From these basic studies, functional neuroimaging analysis of intermediate phenotypes has progressed to more complex and realistic models of brain dysfunction, incorporating models of functional and effective connectivity, including the modalities of psycho-physiological interaction, dynamic causal modeling, and graph theory metrics. The genetic association approaches applied to imaging genetics have also progressed to more sophisticated multivariate effects, including incorporation of two-way and three-way epistatic interactions, and most recently polygenic risk models. Imaging genetics is a unique and powerful strategy for understanding the neural mechanisms of genetic risk for complex CNS disorders at the human brain level.

  1. Role of Neuroimaging in the Presurgical Evaluation of Epilepsy

    PubMed Central

    Lüders, Hans

    2008-01-01

    A significant minority of patients with focal epilepsy are candidates for resective epilepsy surgery. Structural and functional neuroimaging plays an important role in the presurgical evaluation of theses patients. The most frequent etiologies of pharmacoresistant epilepsy in the adult population are mesial temporal sclerosis, malformations of cortical development, cavernous angiomas, and low-grade neoplasms. High-resolution multiplanar magnetic resonance imaging (MRI) with sequences providing T1 and T2 contrast is the initial imaging study of choice to detect these epileptogenic lesions. The epilepsy MRI protocol can be individually tailored when considering the patient's clinical and electrophysiological data. Metabolic imaging techniques such as positron emission tomography (PET) and single photon emission tomography (SPECT) visualize metabolic alterations of the brain in the ictal and interictal states. These techniques may have localizing value in patients with a normal MRI scan. Functional MRI is helpful in non-invasively identifying areas of eloquent cortex. Developments in imaging technology and digital postprocessing may increase the yield for imaging studies to detect the epileptogenic lesion and to characterize its connectivity within the epileptic brain. PMID:19513318

  2. A review of neuroimaging findings in repetitive brain trauma.

    PubMed

    Koerte, Inga K; Lin, Alexander P; Willems, Anna; Muehlmann, Marc; Hufschmidt, Jakob; Coleman, Michael J; Green, Isobel; Liao, Huijun; Tate, David F; Wilde, Elisabeth A; Pasternak, Ofer; Bouix, Sylvain; Rathi, Yogesh; Bigler, Erin D; Stern, Robert A; Shenton, Martha E

    2015-05-01

    Chronic traumatic encephalopathy (CTE) is a neurodegenerative disease confirmed at postmortem. Those at highest risk are professional athletes who participate in contact sports and military personnel who are exposed to repetitive blast events. All neuropathologically confirmed CTE cases, to date, have had a history of repetitive head impacts. This suggests that repetitive head impacts may be necessary for the initiation of the pathogenetic cascade that, in some cases, leads to CTE. Importantly, while all CTE appears to result from repetitive brain trauma, not all repetitive brain trauma results in CTE. Magnetic resonance imaging has great potential for understanding better the underlying mechanisms of repetitive brain trauma. In this review, we provide an overview of advanced imaging techniques currently used to investigate brain anomalies. We also provide an overview of neuroimaging findings in those exposed to repetitive head impacts in the acute/subacute and chronic phase of injury and in more neurodegenerative phases of injury, as well as in military personnel exposed to repetitive head impacts. Finally, we discuss future directions for research that will likely lead to a better understanding of the underlying mechanisms separating those who recover from repetitive brain trauma vs. those who go on to develop CTE. PMID:25904047

  3. Neuroimaging the temporal dynamics of human avoidance to sustained threat.

    PubMed

    Schlund, Michael W; Hudgins, Caleb D; Magee, Sandy; Dymond, Simon

    2013-11-15

    Many forms of human psychopathology are characterized by sustained negative emotional responses to threat and chronic behavioral avoidance, implicating avoidance as a potential transdiagnostic factor. Evidence from both nonhuman neurophysiological and human neuroimaging studies suggests a distributed frontal-limbic-striatal brain network supports avoidance. However, our understanding of the temporal dynamics of the network to sustained threat that prompts sustained avoidance is limited. To address this issue, 17 adults were given extensive training on a modified free-operant avoidance task in which button pressing avoided money loss during a sustained threat period. Subsequently, subjects underwent functional magnetic resonance imaging while completing the avoidance task. In our regions of interest, we observed phasic, rather than sustained, activation during sustained threat in dorsolateral and inferior frontal regions, anterior and dorsal cingulate, ventral striatum and regions associated with emotion, including the amygdala, insula, substantia nigra and bed nucleus of the stria terminalis complex. Moreover, trait levels of experiential avoidance were negatively correlated with insula, hippocampal and amygdala activation. These findings suggest knowledge that one can consistently avoid aversive outcomes is not associated with decreased threat-related responses and that individuals with greater experiential avoidance exhibit reduced reactivity to initial threat. Implications for understanding brain mechanisms supporting human avoidance and psychological theories of avoidance are discussed. PMID:24095880

  4. Neuroimaging in adult penetrating brain injury: a guide for radiographers

    PubMed Central

    Temple, Nikki; Donald, Cortny; Skora, Amanda; Reed, Warren

    2015-01-01

    Penetrating brain injuries (PBI) are a medical emergency, often resulting in complex damage and high mortality rates. Neuroimaging is essential to evaluate the location and extent of injuries, and to manage them accordingly. Currently, a myriad of imaging modalities are included in the diagnostic workup for adult PBI, including skull radiography, computed tomography (CT), magnetic resonance imaging (MRI) and angiography, with each modality providing their own particular benefits. This literature review explores the current modalities available for investigating PBI and aims to assist in decision making for the appropriate use of diagnostic imaging when presented with an adult PBI. Based on the current literature, the authors have developed an imaging pathway for adult penetrating brain injury that functions as both a learning tool and reference guide for radiographers and other health professionals. Currently, CT is recommended as the imaging modality of choice for the initial assessment of PBI patients, while MRI is important in the sub-acute setting where it aids prognosis prediction and rehabilitation planning, Additional follow-up imaging, such as angiography, should be dependent upon clinical findings. PMID:26229677

  5. Neuroimaging in adult penetrating brain injury: a guide for radiographers

    SciTech Connect

    Temple, Nikki; Donald, Cortny; Skora, Amanda; Reed, Warren

    2015-06-15

    Penetrating brain injuries (PBI) are a medical emergency, often resulting in complex damage and high mortality rates. Neuroimaging is essential to evaluate the location and extent of injuries, and to manage them accordingly. Currently, a myriad of imaging modalities are included in the diagnostic workup for adult PBI, including skull radiography, computed tomography (CT), magnetic resonance imaging (MRI) and angiography, with each modality providing their own particular benefits. This literature review explores the current modalities available for investigating PBI and aims to assist in decision making for the appropriate use of diagnostic imaging when presented with an adult PBI. Based on the current literature, the authors have developed an imaging pathway for adult penetrating brain injury that functions as both a learning tool and reference guide for radiographers and other health professionals. Currently, CT is recommended as the imaging modality of choice for the initial assessment of PBI patients, while MRI is important in the sub-acute setting where it aids prognosis prediction and rehabilitation planning, Additional follow-up imaging, such as angiography, should be dependent upon clinical findings.

  6. A review of neuroimaging findings in repetitive brain trauma.

    PubMed

    Koerte, Inga K; Lin, Alexander P; Willems, Anna; Muehlmann, Marc; Hufschmidt, Jakob; Coleman, Michael J; Green, Isobel; Liao, Huijun; Tate, David F; Wilde, Elisabeth A; Pasternak, Ofer; Bouix, Sylvain; Rathi, Yogesh; Bigler, Erin D; Stern, Robert A; Shenton, Martha E

    2015-05-01

    Chronic traumatic encephalopathy (CTE) is a neurodegenerative disease confirmed at postmortem. Those at highest risk are professional athletes who participate in contact sports and military personnel who are exposed to repetitive blast events. All neuropathologically confirmed CTE cases, to date, have had a history of repetitive head impacts. This suggests that repetitive head impacts may be necessary for the initiation of the pathogenetic cascade that, in some cases, leads to CTE. Importantly, while all CTE appears to result from repetitive brain trauma, not all repetitive brain trauma results in CTE. Magnetic resonance imaging has great potential for understanding better the underlying mechanisms of repetitive brain trauma. In this review, we provide an overview of advanced imaging techniques currently used to investigate brain anomalies. We also provide an overview of neuroimaging findings in those exposed to repetitive head impacts in the acute/subacute and chronic phase of injury and in more neurodegenerative phases of injury, as well as in military personnel exposed to repetitive head impacts. Finally, we discuss future directions for research that will likely lead to a better understanding of the underlying mechanisms separating those who recover from repetitive brain trauma vs. those who go on to develop CTE.

  7. Neuroimaging, Genetics and the Treatment of Nicotine Addiction

    PubMed Central

    Ray, Riju; Loughead, James; Wang, Ze; Detre, John; Yang, Edward; Gur, Ruben; Lerman, Caryn

    2008-01-01

    Advances in neuroimaging and genomics provide an unprecedented opportunity to accelerate medication development for nicotine dependence and other addictions. Neuroimaging studies have begun to elucidate the functional neuroanatomy and neurochemistry underlying effects of nicotine and nicotine abstinence. In parallel, genetic studies, including both candidate gene and genome-wide association approaches, are identifying key neurobiological targets and pathways important in addiction to nicotine. To date, only a few neuroimaging studies have explored effects of nicotine or abstinence on brain activity as a function of genotype. Most analyses of genotype are retrospective, resulting in small sample sizes for testing effects of the minor alleles for candidate genes. The purpose of this review is to provide an outline of the work in neuroimaging, genetics, and nicotine dependence, and to explore the potential for increased integration of these approaches to improve nicotine dependence treatment. PMID:18599130

  8. The adolescent brain: Insights from functional neuroimaging research

    PubMed Central

    Ernst, M.; Mueller, S.C.

    2009-01-01

    With the development of functional neuroimaging tools, the past two decades have witnessed an explosion of work examining functional brain maps, mostly in the adult brain. Against this backdrop of work in adults, developmental research begins to gather a substantial body of knowledge about brain maturation. The purpose of this review is to present some of these findings from the perspective of functional neuroimaging. First, a brief survey of available neuroimaging techniques (i.e., fMRI, MRS, MEG, PET, SPECT, and infrared techniques) is provided. Next, the key cognitive, emotional, and social changes taking place during adolescence are outlined. The third section gives examples of how these behavioral changes can be understood from a neuroscience perspective. The conclusion places this functional neuroimaging research in relation to clinical and molecular work, and shows how answers will ultimately come from the combined efforts of these disciplines. PMID:18383544

  9. Terminology development towards harmonizing multiple clinical neuroimaging research repositories

    PubMed Central

    Turner, Jessica A.; Pasquerello, Danielle; Turner, Matthew D.; Keator, David B.; Alpert, Kathryn; King, Margaret; Landis, Drew; Calhoun, Vince D.; Potkin, Steven G.; Tallis, Marcelo; Ambite, Jose Luis; Wang, Lei

    2015-01-01

    Data sharing and mediation across disparate neuroimaging repositories requires extensive effort to ensure that the different domains of data types are referred to by commonly agreed upon terms. Within the SchizConnect project, which enables querying across decentralized databases of neuroimaging, clinical, and cognitive data from various studies of schizophrenia, we developed a model for each data domain, identified common usable terms that could be agreed upon across the repositories, and linked them to standard ontological terms where possible. We had the goal of facilitating both the current user experience in querying and future automated computations and reasoning regarding the data. We found that existing terminologies are incomplete for these purposes, even with the history of neuroimaging data sharing in the field; and we provide a model for efforts focused on querying multiple clinical neuroimaging repositories. PMID:26688838

  10. Neuroimaging biomarkers in mild traumatic brain injury (mTBI).

    PubMed

    Bigler, Erin D

    2013-09-01

    Reviewed herein are contemporary neuroimaging methods that detect abnormalities associated with mild traumatic brain injury (mTBI). Despite advances in demonstrating underlying neuropathology in a subset of individuals who sustain mTBI, considerable disagreement persists in neuropsychology about mTBI outcome and metrics for evaluation. This review outlines a thesis for the select use of sensitive neuroimaging methods as potential biomarkers of brain injury recognizing that the majority of individuals who sustain an mTBI recover without neuroimaging signs or neuropsychological sequelae detected with methods currently applied. Magnetic resonance imaging (MRI) provides several measures that could serve as mTBI biomarkers including the detection of hemosiderin and white matter abnormalities, assessment of white matter integrity derived from diffusion tensor imaging (DTI), and quantitative measures that directly assess neuroanatomy. Improved prediction of neuropsychological outcomes in mTBI may be achieved with the use of targeted neuroimaging markers.

  11. The Evolution of Neuroimaging Research and Developmental Language Disorders.

    ERIC Educational Resources Information Center

    Lane, Angela B.; Foundas, Anne L.; Leonard, Christiana M.

    2001-01-01

    This article reviews current neuroimaging literature, including computer tomography, positron emission tomography, single photon emission spectroscopy, and magnetic resonance imaging, on individuals with developmental language disorders. The review suggests a complicated relationship between cortical morphometry and language development that is…

  12. Efficient, Distributed and Interactive Neuroimaging Data Analysis Using the LONI Pipeline.

    PubMed

    Dinov, Ivo D; Van Horn, John D; Lozev, Kamen M; Magsipoc, Rico; Petrosyan, Petros; Liu, Zhizhong; Mackenzie-Graham, Allan; Eggert, Paul; Parker, Douglas S; Toga, Arthur W

    2009-01-01

    The LONI Pipeline is a graphical environment for construction, validation and execution of advanced neuroimaging data analysis protocols (Rex et al., 2003). It enables automated data format conversion, allows Grid utilization, facilitates data provenance, and provides a significant library of computational tools. There are two main advantages of the LONI Pipeline over other graphical analysis workflow architectures. It is built as a distributed Grid computing environment and permits efficient tool integration, protocol validation and broad resource distribution. To integrate existing data and computational tools within the LONI Pipeline environment, no modification of the resources themselves is required. The LONI Pipeline provides several types of process submissions based on the underlying server hardware infrastructure. Only workflow instructions and references to data, executable scripts and binary instructions are stored within the LONI Pipeline environment. This makes it portable, computationally efficient, distributed and independent of the individual binary processes involved in pipeline data-analysis workflows. We have expanded the LONI Pipeline (V.4.2) to include server-to-server (peer-to-peer) communication and a 3-tier failover infrastructure (Grid hardware, Sun Grid Engine/Distributed Resource Management Application API middleware, and the Pipeline server). Additionally, the LONI Pipeline provides three layers of background-server executions for all users/sites/systems. These new LONI Pipeline features facilitate resource-interoperability, decentralized computing, construction and validation of efficient and robust neuroimaging data-analysis workflows. Using brain imaging data from the Alzheimer's Disease Neuroimaging Initiative (Mueller et al., 2005), we demonstrate integration of disparate resources, graphical construction of complex neuroimaging analysis protocols and distributed parallel computing. The LONI Pipeline, its features, specifications

  13. Efficient, Distributed and Interactive Neuroimaging Data Analysis Using the LONI Pipeline

    PubMed Central

    Dinov, Ivo D.; Van Horn, John D.; Lozev, Kamen M.; Magsipoc, Rico; Petrosyan, Petros; Liu, Zhizhong; MacKenzie-Graham, Allan; Eggert, Paul; Parker, Douglas S.; Toga, Arthur W.

    2009-01-01

    The LONI Pipeline is a graphical environment for construction, validation and execution of advanced neuroimaging data analysis protocols (Rex et al., 2003). It enables automated data format conversion, allows Grid utilization, facilitates data provenance, and provides a significant library of computational tools. There are two main advantages of the LONI Pipeline over other graphical analysis workflow architectures. It is built as a distributed Grid computing environment and permits efficient tool integration, protocol validation and broad resource distribution. To integrate existing data and computational tools within the LONI Pipeline environment, no modification of the resources themselves is required. The LONI Pipeline provides several types of process submissions based on the underlying server hardware infrastructure. Only workflow instructions and references to data, executable scripts and binary instructions are stored within the LONI Pipeline environment. This makes it portable, computationally efficient, distributed and independent of the individual binary processes involved in pipeline data-analysis workflows. We have expanded the LONI Pipeline (V.4.2) to include server-to-server (peer-to-peer) communication and a 3-tier failover infrastructure (Grid hardware, Sun Grid Engine/Distributed Resource Management Application API middleware, and the Pipeline server). Additionally, the LONI Pipeline provides three layers of background-server executions for all users/sites/systems. These new LONI Pipeline features facilitate resource-interoperability, decentralized computing, construction and validation of efficient and robust neuroimaging data-analysis workflows. Using brain imaging data from the Alzheimer's Disease Neuroimaging Initiative (Mueller et al., 2005), we demonstrate integration of disparate resources, graphical construction of complex neuroimaging analysis protocols and distributed parallel computing. The LONI Pipeline, its features, specifications

  14. Neuroimaging findings in treatment-resistant schizophrenia: a systematic review

    PubMed Central

    Nakajima, Shinichiro; Takeuchi, Hiroyoshi; Plitman, Eric; Fervaha, Gagan; Gerretsen, Philip; Caravaggio, Fernando; Chung, Jun Ku; Iwata, Yusuke; Remington, Gary; Graff-Guerrero, Ariel

    2015-01-01

    Background Recent developments in neuroimaging have advanced understanding biological mechanisms underlying schizophrenia. However, neuroimaging correlates of treatment-resistant schizophrenia (TRS) and superior effects of clozapine on TRS remain unclear. Methods Systematic search was performed to identify neuroimaging characteristics unique to TRS and ultra-resistant schizophrenia (i.e. clozapine-resistant [URS]), and clozapine's efficacy in TRS using Embase, Medline, and PsychInfo. Search terms included (schizophreni*) and (resistan* OR refractory OR clozapine) and (ASL OR CT OR DTI OR FMRI OR MRI OR MRS OR NIRS OR PET OR SPECT). Results 25 neuroimaging studies have investigated TRS and effects of clozapine. Only 5 studies have compared TRS and non-TRS, collectively providing no replicated neuroimaging finding specific to TRS. Studies comparing TRS and healthy controls suggest hypometabolism in the prefrontal cortex, hypermetabolism in the basal ganglia, and structural anomalies in the corpus callosum contribute to TRS. Clozapine may increase prefrontal hypoactivation in TRS although this was not related to clinical improvement; in contrast, evidence has suggested a link between clozapine efficacy and decreased metabolism in the basal ganglia and thalamus. Conclusion Existing literature does not elucidate neuroimaging correlates specific to TRS or URS, which, if present, might also shed light on clozapine's efficacy in TRS. This said, leads from other lines of investigation, including the glutamatergic system can prove useful in guiding future neuroimaging studies focused on, in particular, the frontocortical-basal ganglia-thalamic circuits. Critical to the success of this work will be precise subtyping of study subjects based on treatment response/nonresponse and the use of multimodal neuroimaging. PMID:25684554

  15. [Neuroimaging findings in cerebroretinal microangiopathy with calcifications and cysts].

    PubMed

    Herrera, Diego Alberto; Vargas, Sergio Alberto; Montoya, Claudia

    2014-01-01

    Cerebroretinal microangiopathy with calcifications and cysts is a rare condition characterized by brain, retinal and bone anomalies, as well as a predisposition to gastrointestinal bleeding. There are few reported cases of this condition in adults, among whom the incidence is low. Neuroimaging findings are characteristic, with bilateral calcifications, leukoencephalopathy and intracranial cysts. The purpose of this article was to do a literature survey and illustrate two cases diagnosed with the aid of neuroimaging. PMID:24967922

  16. Neuroimaging studies in people with gender incongruence.

    PubMed

    Kreukels, Baudewijntje P C; Guillamon, Antonio

    2016-01-01

    The current review gives an overview of brain studies in transgender people. First, we describe studies into the aetiology of feelings of gender incongruence, primarily addressing the sexual differentiation hypothesis: does the brain of transgender individuals resemble that of their natal sex, or that of their experienced gender? Findings from neuroimaging studies focusing on brain structure suggest that the brain phenotypes of trans women (MtF) and trans men (FtM) differ in various ways from control men and women with feminine, masculine, demasculinized and defeminized features. The brain phenotypes of people with feelings of gender incongruence may help us to figure out whether sex differentiation of the brain is atypical in these individuals, and shed light on gender identity development. Task-related imaging studies may show whether brain activation and task performance in transgender people is sex-atypical. Second, we review studies that evaluate the effects of cross-sex hormone treatment on the brain. This type of research provides knowledge on how changes in sex hormone levels may affect brain structure and function. PMID:26766406

  17. Neuroimaging supports central pathology in familial dysautonomia.

    PubMed

    Axelrod, Felicia B; Hilz, Max J; Berlin, Dena; Yau, Po Lai; Javier, David; Sweat, Victoria; Bruehl, Hannah; Convit, Antonio

    2010-02-01

    Familial dysautonomia (FD) is a hereditary peripheral and central nervous system disorder with poorly defined central neuropathology. This prospective pilot study aimed to determine if MRI would provide objective parameters of central neuropathology. There were 14 study subjects, seven FD individuals (18.6 +/- 4.2 years, 3 female) and seven controls (19.1 +/- 5.8 years, 3 female). All subjects had standardized brain MRI evaluation including quantitative regional volume measurements, diffusion tensor imaging (DTI) for assessment of white matter (WM) microstructural integrity by calculation of fractional anisotropy (FA), and proton MR spectroscopy ((1)H MRS) to assess neuronal health. The FD patients had significantly decreased FA in optic radiation (p = 0.009) and middle cerebellar peduncle (p = 0.004). Voxel-wise analysis identified both GM and WM microstructural damage among FD subjects as there were nine clusters of WM FA reductions and 16 clusters of GM apparent diffusion coefficient (ADC) elevations. Their WM proportion was significantly decreased (p = 0.003) as was the WM proportion in the frontal region (p = 0.007). (1)H MRS showed no significant abnormalities. The findings of WM abnormalities and decreased optic radiation and middle cerebellar peduncle FA in the FD study group, suggest compromised myelination and WM micro-structural integrity in FD brains. These neuroimaging results are consistent with clinical visual abnormalities and gait disturbance. Furthermore the frontal lobe atrophy is consistent with previously reported neuropsychological deficits. PMID:19705052

  18. [Gambling addiction: insights from neuroscience and neuroimaging].

    PubMed

    Sescousse, Guillaume

    2015-01-01

    Although most people consider gambling as a recreational activity, some individuals lose control over their behavior and enter a spiral of compulsive gambling leading to dramatic consequences. In its most severe form, pathological gambling is considered a behavioral addiction sharing many similarities with substance addiction. A number of neurobiological hypotheses have been investigated in the past ten years, relying mostly on neuroimaging techniques. Similarly to substance addiction, a number of observations indicate a central role for dopamine in pathological gambling. However, the underlying mechanism seems partly different and is still poorly understood. Neuropsychological studies have shown decision-making and behavioral inhibition deficits in pathological gamblers, likely reflecting frontal lobe dysfunction. Finally, functional MRI studies have revealed abnormal reactivity within the brain reward system, including the striatum and ventro-medial prefrontal cortex. These regions are over-activated by gambling cues, and under-activated by monetary gains. However, the scarcity and heterogeneity of brain imaging studies currently hinder the development of a coherent neurobiological model of pathological gambling. Further replications of results and diversification of approaches will be needed in the coming years in order to strengthen our current model. PMID:26340839

  19. Challenges for Molecular Neuroimaging with MRI

    PubMed Central

    Lelyveld, Victor S.; Atanasijevic, Tatjana; Jasanoff, Alan

    2010-01-01

    Magnetic resonance (MRI)-based molecular imaging methods are beginning to have impact in neuroscience. A growing number of molecular imaging agents have been synthesized and tested in vitro, but so far relatively few have been validated in the brains of live animals. Here, we discuss key challenges associated with expanding the repertoire of successful molecular neuroimaging approaches. The difficulty of delivering agents past the blood-brain barrier (BBB) is a particular obstacle to molecular imaging in the central nervous system. We review established and emerging techniques for trans-BBB delivery, including intracranial infusion, BBB disruption, and transporter-related methods. Improving the sensitivity with which MRI-based molecular agents can be detected is a second major challenge. Better sensitivity would in turn reduce the requirements for delivery and alleviate potential side effects. We discuss recent efforts to enhance relaxivity of conventional longitudinal relaxation time (T1) and transverse relaxation time (T2) MRI contrast agents, as well as strategies that involve amplifying molecular signals or reducing endogenous background influences. With ongoing refinement of imaging approaches and brain delivery methods, MRI-based techniques for molecular-level neuroscientific investigation will fall increasingly within reach. PMID:20808721

  20. Neuroimaging studies in people with gender incongruence.

    PubMed

    Kreukels, Baudewijntje P C; Guillamon, Antonio

    2016-01-01

    The current review gives an overview of brain studies in transgender people. First, we describe studies into the aetiology of feelings of gender incongruence, primarily addressing the sexual differentiation hypothesis: does the brain of transgender individuals resemble that of their natal sex, or that of their experienced gender? Findings from neuroimaging studies focusing on brain structure suggest that the brain phenotypes of trans women (MtF) and trans men (FtM) differ in various ways from control men and women with feminine, masculine, demasculinized and defeminized features. The brain phenotypes of people with feelings of gender incongruence may help us to figure out whether sex differentiation of the brain is atypical in these individuals, and shed light on gender identity development. Task-related imaging studies may show whether brain activation and task performance in transgender people is sex-atypical. Second, we review studies that evaluate the effects of cross-sex hormone treatment on the brain. This type of research provides knowledge on how changes in sex hormone levels may affect brain structure and function.

  1. Sleep Neuroimaging and Models of Consciousness

    PubMed Central

    Tagliazucchi, Enzo; Behrens, Marion; Laufs, Helmut

    2013-01-01

    Human deep sleep is characterized by reduced sensory activity, responsiveness to stimuli, and conscious awareness. Given its ubiquity and reversible nature, it represents an attractive paradigm to study the neural changes which accompany the loss of consciousness in humans. In particular, the deepest stages of sleep can serve as an empirical test for the predictions of theoretical models relating the phenomenology of consciousness with underlying neural activity. A relatively recent shift of attention from the analysis of evoked responses toward spontaneous (or “resting state”) activity has taken place in the neuroimaging community, together with the development of tools suitable to study distributed functional interactions. In this review we focus on recent functional Magnetic Resonance Imaging (fMRI) studies of spontaneous activity during sleep and their relationship with theoretical models for human consciousness generation, considering the global workspace theory, the information integration theory, and the dynamical core hypothesis. We discuss the venues of research opened by these results, emphasizing the need to extend the analytic methodology in order to obtain a dynamical picture of how functional interactions change over time and how their evolution is modulated during different conscious states. Finally, we discuss the need to experimentally establish absent or reduced conscious content, even when studying the deepest sleep stages. PMID:23717291

  2. Neuroimaging of Fear-Associated Learning.

    PubMed

    Greco, John A; Liberzon, Israel

    2016-01-01

    Fear conditioning has been commonly used as a model of emotional learning in animals and, with the introduction of functional neuroimaging techniques, has proven useful in establishing the neurocircuitry of emotional learning in humans. Studies of fear acquisition suggest that regions such as amygdala, insula, anterior cingulate cortex, and hippocampus play an important role in acquisition of fear, whereas studies of fear extinction suggest that the amygdala is also crucial for safety learning. Extinction retention testing points to the ventromedial prefrontal cortex as an essential region in the recall of the safety trace, and explicit learning of fear and safety associations recruits additional cortical and subcortical regions. Importantly, many of these findings have implications in our understanding of the pathophysiology of psychiatric disease. Recent studies using clinical populations have lent insight into the changes in regional activity in specific disorders, and treatment studies have shown how pharmaceutical and other therapeutic interventions modulate brain activation during emotional learning. Finally, research investigating individual differences in neurotransmitter receptor genotypes has highlighted the contribution of these systems in fear-associated learning.

  3. Latent feature representation with stacked auto-encoder for AD/MCI diagnosis.

    PubMed

    Suk, Heung-Il; Lee, Seong-Whan; Shen, Dinggang

    2015-03-01

    Recently, there have been great interests for computer-aided diagnosis of Alzheimer's disease (AD) and its prodromal stage, mild cognitive impairment (MCI). Unlike the previous methods that considered simple low-level features such as gray matter tissue volumes from MRI, and mean signal intensities from PET, in this paper, we propose a deep learning-based latent feature representation with a stacked auto-encoder (SAE). We believe that there exist latent non-linear complicated patterns inherent in the low-level features such as relations among features. Combining the latent information with the original features helps build a robust model in AD/MCI classification, with high diagnostic accuracy. Furthermore, thanks to the unsupervised characteristic of the pre-training in deep learning, we can benefit from the target-unrelated samples to initialize parameters of SAE, thus finding optimal parameters in fine-tuning with the target-related samples, and further enhancing the classification performances across four binary classification problems: AD vs. healthy normal control (HC), MCI vs. HC, AD vs. MCI, and MCI converter (MCI-C) vs. MCI non-converter (MCI-NC). In our experiments on ADNI dataset, we validated the effectiveness of the proposed method, showing the accuracies of 98.8, 90.7, 83.7, and 83.3 % for AD/HC, MCI/HC, AD/MCI, and MCI-C/MCI-NC classification, respectively. We believe that deep learning can shed new light on the neuroimaging data analysis, and our work presented the applicability of this method to brain disease diagnosis.

  4. Human Neuroimaging as a “Big Data” Science

    PubMed Central

    Van Horn, John Darrell; Toga, Arthur W.

    2013-01-01

    The maturation of in vivo neuroimaging has lead to incredible quantities of digital information about the human brain. While much is made of the data deluge in science, neuroimaging represents the leading edge of this onslaught of “big data”. A range of neuroimaging databasing approaches has streamlined the transmission, storage, and dissemination of data from such brain imaging studies. Yet few, if any, common solutions exist to support the science of neuroimaging. In this article, we discuss how modern neuroimaging research represents a mutifactorial and broad ranging data challenge, involving the growing size of the data being acquired; sociologial and logistical sharing issues; infrastructural challenges for multi-site, multi-datatype archiving; and the means by which to explore and mine these data. As neuroimaging advances further, e.g. aging, genetics, and age-related disease, new vision is needed to manage and process this information while marshalling of these resources into novel results. Thus, “big data” can become “big” brain science. PMID:24113873

  5. Kolmogorov-Zakharov spectrum in AdS gravitational collapse.

    PubMed

    de Oliveira, H P; Pando Zayas, Leopoldo A; Rodrigues, E L

    2013-08-01

    We study black hole formation during the gravitational collapse of a massless scalar field in asymptotically D-dimensional anti-de Sitter AdS(D) spacetimes for D = 4, 5. We conclude that spherically symmetric gravitational collapse in asymptotically AdS spaces is turbulent and characterized by a Kolmogorov-Zakharov spectrum. Namely, we find that after an initial period of weakly nonlinear evolution, there is a regime where the power spectrum of the Ricci scalar evolves as ω(-s) with the frequency, ω, and s ≈ 1.7 ± 0.1.

  6. Effect of CLU genetic variants on cerebrospinal fluid and neuroimaging markers in healthy, mild cognitive impairment and Alzheimer's disease cohorts.

    PubMed

    Tan, Lin; Wang, Hui-Fu; Tan, Meng-Shan; Tan, Chen-Chen; Zhu, Xi-Chen; Miao, Dan; Yu, Wan-Jiang; Jiang, Teng; Tan, Lan; Yu, Jin-Tai

    2016-01-01

    The Clusterin (CLU) gene, also known as apolipoprotein J (ApoJ), is currently the third most associated late-onset Alzheimer's disease (LOAD) risk gene. However, little was known about the possible effect of CLU genetic variants on AD pathology in brain. Here, we evaluated the interaction between 7 CLU SNPs (covering 95% of genetic variations) and the role of CLU in β-amyloid (Aβ) deposition, AD-related structure atrophy, abnormal glucose metabolism on neuroimaging and CSF markers to clarify the possible approach by that CLU impacts AD. Finally, four loci (rs11136000, rs1532278, rs2279590, rs7982) showed significant associations with the Aβ deposition at the baseline level while genotypes of rs9331888 (P = 0.042) increased Aβ deposition. Besides, rs9331888 was significantly associated with baseline volume of left hippocampus (P = 0.014). We then further validated the association with Aβ deposition in the AD, mild cognitive impairment (MCI), normal control (NC) sub-groups. The results in sub-groups confirmed the association between CLU genotypes and Aβ deposition further. Our findings revealed that CLU genotypes could probably modulate the cerebral the Aβ loads on imaging and volume of hippocampus. These findings raise the possibility that the biological effects of CLU may be relatively confined to neuroimaging trait and hence may offer clues to AD. PMID:27229352

  7. Integration and relative value of biomarkers for prediction of MCI to AD progression: spatial patterns of brain atrophy, cognitive scores, APOE genotype and CSF biomarkers.

    PubMed

    Da, Xiao; Toledo, Jon B; Zee, Jarcy; Wolk, David A; Xie, Sharon X; Ou, Yangming; Shacklett, Amanda; Parmpi, Paraskevi; Shaw, Leslie; Trojanowski, John Q; Davatzikos, Christos

    2014-01-01

    This study evaluates the individual, as well as relative and joint value of indices obtained from magnetic resonance imaging (MRI) patterns of brain atrophy (quantified by the SPARE-AD index), cerebrospinal fluid (CSF) biomarkers, APOE genotype, and cognitive performance (ADAS-Cog) in progression from mild cognitive impairment (MCI) to Alzheimer's disease (AD) within a variable follow-up period up to 6 years, using data from the Alzheimer's Disease Neuroimaging Initiative-1 (ADNI-1). SPARE-AD was first established as a highly sensitive and specific MRI-marker of AD vs. cognitively normal (CN) subjects (AUC = 0.98). Baseline predictive values of all aforementioned indices were then compared using survival analysis on 381 MCI subjects. SPARE-AD and ADAS-Cog were found to have similar predictive value, and their combination was significantly better than their individual performance. APOE genotype did not significantly improve prediction, although the combination of SPARE-AD, ADAS-Cog and APOE ε4 provided the highest hazard ratio estimates of 17.8 (last vs. first quartile). In a subset of 192 MCI patients who also had CSF biomarkers, the addition of Aβ1-42, t-tau, and p-tau181p to the previous model did not improve predictive value significantly over SPARE-AD and ADAS-Cog combined. Importantly, in amyloid-negative patients with MCI, SPARE-AD had high predictive power of clinical progression. Our findings suggest that SPARE-AD and ADAS-Cog in combination offer the highest predictive power of conversion from MCI to AD, which is improved, albeit not significantly, by APOE genotype. The finding that SPARE-AD in amyloid-negative MCI patients was predictive of clinical progression is not expected under the amyloid hypothesis and merits further investigation.

  8. Segmented strings in AdS 3

    NASA Astrophysics Data System (ADS)

    Callebaut, Nele; Gubser, Steven S.; Samberg, Andreas; Toldo, Chiara

    2015-11-01

    We study segmented strings in flat space and in AdS 3. In flat space, these well known classical motions describe strings which at any instant of time are piecewise linear. In AdS 3, the worldsheet is composed of faces each of which is a region bounded by null geodesics in an AdS 2 subspace of AdS 3. The time evolution can be described by specifying the null geodesic motion of kinks in the string at which two segments are joined. The outcome of collisions of kinks on the worldsheet can be worked out essentially using considerations of causality. We study several examples of closed segmented strings in AdS 3 and find an unexpected quasi-periodic behavior. We also work out a WKB analysis of quantum states of yo-yo strings in AdS 5 and find a logarithmic term reminiscent of the logarithmic twist of string states on the leading Regge trajectory.

  9. Polarised black holes in AdS

    NASA Astrophysics Data System (ADS)

    Costa, Miguel S.; Greenspan, Lauren; Oliveira, Miguel; Penedones, João; Santos, Jorge E.

    2016-06-01

    We consider solutions in Einstein-Maxwell theory with a negative cosmological constant that asymptote to global AdS 4 with conformal boundary {S}2× {{{R}}}t. At the sphere at infinity we turn on a space-dependent electrostatic potential, which does not destroy the asymptotic AdS behaviour. For simplicity we focus on the case of a dipolar electrostatic potential. We find two new geometries: (i) an AdS soliton that includes the full backreaction of the electric field on the AdS geometry; (ii) a polarised neutral black hole that is deformed by the electric field, accumulating opposite charges in each hemisphere. For both geometries we study boundary data such as the charge density and the stress tensor. For the black hole we also study the horizon charge density and area, and further verify a Smarr formula. Then we consider this system at finite temperature and compute the Gibbs free energy for both AdS soliton and black hole phases. The corresponding phase diagram generalizes the Hawking-Page phase transition. The AdS soliton dominates the low temperature phase and the black hole the high temperature phase, with a critical temperature that decreases as the external electric field increases. Finally, we consider the simple case of a free charged scalar field on {S}2× {{{R}}}t with conformal coupling. For a field in the SU(N ) adjoint representation we compare the phase diagram with the above gravitational system.

  10. Analyzing neuroimaging data with subclasses: A shrinkage approach.

    PubMed

    Höhne, Johannes; Bartz, Daniel; Hebart, Martin N; Müller, Klaus-Robert; Blankertz, Benjamin

    2016-01-01

    Among the numerous methods used to analyze neuroimaging data, Linear Discriminant Analysis (LDA) is commonly applied for binary classification problems. LDAs popularity derives from its simplicity and its competitive classification performance, which has been reported for various types of neuroimaging data. Yet the standard LDA approach proves less than optimal for binary classification problems when additional label information (i.e. subclass labels) is present. Subclass labels allow to model structure in the data, which can be used to facilitate the classification task. In this paper, we illustrate how neuroimaging data exhibit subclass labels that may contain valuable information. We also show that the standard LDA classifier is unable to exploit subclass labels. We introduce a novel method that allows subclass labels to be incorporated efficiently into the classifier. The novel method, which we call Relevance Subclass LDA (RSLDA), computes an individual classification hyperplane for each subclass. It is based on regularized estimators of the subclass mean and uses other subclasses as regularization targets. We demonstrate the applicability and performance of our method on data drawn from two different neuroimaging modalities: (I) EEG data from brain-computer interfacing with event-related potentials, and (II) fMRI data in response to different levels of visual motion. We show that RSLDA outperforms the standard LDA approach for both types of datasets. These findings illustrate the benefits of exploiting subclass structure in neuroimaging data. Finally, we show that our classifier also outputs regularization profiles, enabling researchers to interpret the subclass structure in a meaningful way. RSLDA therefore yields increased classification accuracy as well as a better interpretation of neuroimaging data. Since both results are highly favorable, we suggest to apply RSLDA for various classification problems within neuroimaging and beyond. PMID:26407815

  11. Cognitive Impairment, Neuroimaging, and Alzheimer Neuropathology in Mouse Models of Down Syndrome.

    PubMed

    Hamlett, Eric D; Boger, Heather A; Ledreux, Aurélie; Kelley, Christy M; Mufson, Elliott J; Falangola, Maria F; Guilfoyle, David N; Nixon, Ralph A; Patterson, David; Duval, Nathan; Granholm, Ann-Charlotte E

    2016-01-01

    Down syndrome (DS) is the most common non-lethal genetic condition that affects approximately 1 in 700 births in the United States of America. DS is characterized by complete or segmental chromosome 21 trisomy, which leads to variable intellectual disabilities, progressive memory loss, and accelerated neurodegeneration with age. During the last three decades, people with DS have experienced a doubling of life expectancy due to progress in treatment of medical comorbidities, which has allowed this population to reach the age when they develop early onset Alzheimer's disease (AD). Individuals with DS develop cognitive and pathological hallmarks of AD in their fourth or fifth decade, and are currently lacking successful prevention or treatment options for dementia. The profound memory deficits associated with DS-related AD (DS-AD) have been associated with degeneration of several neuronal populations, but mechanisms of neurodegeneration are largely unexplored. The most successful animal model for DS is the Ts65Dn mouse, but several new models have also been developed. In the current review, we discuss recent findings and potential treatment options for the management of memory loss and AD neuropathology in DS mouse models. We also review agerelated neuropathology, and recent findings from neuroimaging studies. The validation of appropriate DS mouse models that mimic neurodegeneration and memory loss in humans with DS can be valuable in the study of novel preventative and treatment interventions, and may be helpful in pinpointing gene-gene interactions as well as specific gene segments involved in neurodegeneration. PMID:26391050

  12. Cognitive Impairment, Neuroimaging, and Alzheimer Neuropathology in Mouse Models of Down Syndrome

    PubMed Central

    Hamlett, Eric D.; Boger, Heather A.; Ledreux, Aurélie; Kelley, Christy M.; Mufson, Elliott J.; Falangola, Maria F.; Guilfoyle, David N.; Nixon, Ralph A.; Patterson, David; Duval, Nathan; Granholm, Ann-Charlotte E.

    2016-01-01

    Down syndrome (DS) is the most common non-lethal genetic condition that affects approximately 1 in 700 births in the United States of America. DS is characterized by complete or segmental chromosome 21 trisomy, which leads to variable intellectual disabilities, progressive memory loss, and accelerated neurodegeneration with age. During the last three decades, people with DS have experienced a doubling of life expectancy due to progress in treatment of medical comorbidities, which has allowed this population to reach the age when they develop early onset Alzheimer’s disease (AD). Individuals with DS develop cognitive and pathological hallmarks of AD in their fourth or fifth decade, and are currently lacking successful prevention or treatment options for dementia. The profound memory deficits associated with DS-related AD (DS-AD) have been associated with degeneration of several neuronal populations, but mechanisms of neurodegeneration are largely unexplored. The most successful animal model for DS is the Ts65Dn mouse, but several new models have also been developed. In the current review, we discuss recent findings and potential treatment options for the management of memory loss and AD neuropathology in DS mouse models. We also review age-related neuropathology, and recent findings from neuroimaging studies. The validation of appropriate DS mouse models that mimic neurodegeneration and memory loss in humans with DS can be valuable in the study of novel preventative and treatment interventions, and may be helpful in pinpointing gene-gene interactions as well as specific gene segments involved in neurodegeneration. PMID:26391050

  13. Functional neuroimaging of traumatic brain injury: advances and clinical utility

    PubMed Central

    Irimia, Andrei; Van Horn, John Darrell

    2015-01-01

    Functional deficits due to traumatic brain injury (TBI) can have significant and enduring consequences upon patients’ life quality and expectancy. Although functional neuroimaging is essential for understanding TBI pathophysiology, an insufficient amount of effort has been dedicated to the task of translating functional neuroimaging findings into information with clinical utility. The purpose of this review is to summarize the use of functional neuroimaging techniques – especially functional magnetic resonance imaging, diffusion tensor imaging, positron emission tomography, magnetic resonance spectroscopy, and electroencephalography – for advancing current knowledge of TBI-related brain dysfunction and for improving the rehabilitation of TBI patients. We focus on seven core areas of functional deficits, namely consciousness, motor function, attention, memory, higher cognition, personality, and affect, and, for each of these, we summarize recent findings from neuroimaging studies which have provided substantial insight into brain function changes due to TBI. Recommendations are also provided to aid in setting the direction of future neuroimaging research and for understanding brain function changes after TBI. PMID:26396520

  14. Prognostic serum miRNA biomarkers associated with Alzheimer's disease shows concordance with neuropsychological and neuroimaging assessment.

    PubMed

    Cheng, L; Doecke, J D; Sharples, R A; Villemagne, V L; Fowler, C J; Rembach, A; Martins, R N; Rowe, C C; Macaulay, S L; Masters, C L; Hill, A F

    2015-10-01

    There is no consensus for a blood-based test for the early diagnosis of Alzheimer's disease (AD). Expression profiling of small non-coding RNA's, microRNA (miRNA), has revealed diagnostic potential in human diseases. Circulating miRNA are found in small vesicles known as exosomes within biological fluids such as human serum. The aim of this work was to determine a set of differential exosomal miRNA biomarkers between healthy and AD patients, which may aid in diagnosis. Using next-generation deep sequencing, we profiled exosomal miRNA from serum (N=49) collected from the Australian Imaging, Biomarkers and Lifestyle Flagship Study (AIBL). Sequencing results were validated using quantitative reverse transcription PCR (qRT-PCR; N=60), with predictions performed using the Random Forest method. Additional risk factors collected during the 4.5-year AIBL Study including clinical, medical and cognitive assessments, and amyloid neuroimaging with positron emission tomography were assessed. An AD-specific 16-miRNA signature was selected and adding established risk factors including age, sex and apolipoprotein ɛ4 (APOE ɛ4) allele status to the panel of deregulated miRNA resulted in a sensitivity and specificity of 87% and 77%, respectively, for predicting AD. Furthermore, amyloid neuroimaging information for those healthy control subjects incorrectly classified with AD-suggested progression in these participants towards AD. These data suggest that an exosomal miRNA signature may have potential to be developed as a suitable peripheral screening tool for AD. PMID:25349172

  15. Lorentzian AdS geometries, wormholes, and holography

    SciTech Connect

    Arias, Raul E.; Silva, Guillermo A.; Botta Cantcheff, Marcelo

    2011-03-15

    We investigate the structure of two-point functions for the quantum field theory dual to an asymptotically Lorentzian Anti de Sitter (AdS) wormhole. The bulk geometry is a solution of five-dimensional second-order Einstein-Gauss-Bonnet gravity and causally connects two asymptotically AdS spacetimes. We revisit the Gubser-Klebanov-Polyakov-Witten prescription for computing two-point correlation functions for dual quantum field theories operators O in Lorentzian signature and we propose to express the bulk fields in terms of the independent boundary values {phi}{sub 0}{sup {+-}} at each of the two asymptotic AdS regions; along the way we exhibit how the ambiguity of normalizable modes in the bulk, related to initial and final states, show up in the computations. The independent boundary values are interpreted as sources for dual operators O{sup {+-}} and we argue that, apart from the possibility of entanglement, there exists a coupling between the degrees of freedom living at each boundary. The AdS{sub 1+1} geometry is also discussed in view of its similar boundary structure. Based on the analysis, we propose a very simple geometric criterion to distinguish coupling from entanglement effects among two sets of degrees of freedom associated with each of the disconnected parts of the boundary.

  16. Neuroimaging, a new tool for investigating the effects of early diet on cognitive and brain development.

    PubMed

    Isaacs, Elizabeth B

    2013-01-01

    Nutrition is crucial to the initial development of the central nervous system (CNS), and then to its maintenance, because both depend on dietary intake to supply the elements required to develop and fuel the system. Diet in early life is often seen in the context of "programming" where a stimulus occurring during a vulnerable period can have long-lasting or even lifetime effects on some aspect of the organism's structure or function. Nutrition was first shown to be a programming stimulus for growth, and then for cognitive behavior, in animal studies that were able to employ methods that allowed the demonstration of neural effects of early nutrition. Such research raised the question of whether nutrition could also programme cognition/brain structure in humans. Initial studies of cognitive effects were observational, usually conducted in developing countries where the presence of confounding factors made it difficult to interpret the role of nutrition in the cognitive deficits that were seen. Attributing causality to nutrition required randomized controlled trials (RCTs) and these, often in developed countries, started to appear around 30 years ago. Most demonstrated convincingly that early nutrition could affect subsequent cognition. Until the advent of neuroimaging techniques that allowed in vivo examination of the brain, however, we could determine very little about the neural effects of early diet in humans. The combination of well-designed trials with neuroimaging tools means that we are now able to pose and answer questions that would have seemed impossible only recently. This review discusses various neuroimaging methods that are suitable for use in nutrition studies, while pointing out some of the limitations that they may have. The existing literature is small, but examples of studies that have used these methods are presented. Finally, some considerations that have arisen from previous studies, as well as suggestions for future research, are discussed.

  17. Functional neuroimaging studies of the effects of psychotherapy.

    PubMed

    Beauregard, Mario

    2014-03-01

    It has been long established that psychological interventions can markedly alter patients' thinking patterns, beliefs, attitudes, emotional states, and behaviors. Little was known about the neural mechanisms mediating such alterations before the advent of functional neuroimaging techniques. Since the turn of the new millenium, several functional neuroimaging studies have been conducted to tackle this important issue. Some of these studies have explored the neural impact of various forms of psychotherapy in individuals with major depressive disorder. Other neuroimaging studies have investigated the effects of psychological interventions for anxiety disorders. I review these studies in the present article, and discuss the putative neural mechanisms of change in psychotherapy. The findings of these studies suggest that mental and behavioral changes occurring during psychotherapeutic interventions can lead to a normalization of functional brain activity at a global level.

  18. Machine learning for neuroimaging with scikit-learn.

    PubMed

    Abraham, Alexandre; Pedregosa, Fabian; Eickenberg, Michael; Gervais, Philippe; Mueller, Andreas; Kossaifi, Jean; Gramfort, Alexandre; Thirion, Bertrand; Varoquaux, Gaël

    2014-01-01

    Statistical machine learning methods are increasingly used for neuroimaging data analysis. Their main virtue is their ability to model high-dimensional datasets, e.g., multivariate analysis of activation images or resting-state time series. Supervised learning is typically used in decoding or encoding settings to relate brain images to behavioral or clinical observations, while unsupervised learning can uncover hidden structures in sets of images (e.g., resting state functional MRI) or find sub-populations in large cohorts. By considering different functional neuroimaging applications, we illustrate how scikit-learn, a Python machine learning library, can be used to perform some key analysis steps. Scikit-learn contains a very large set of statistical learning algorithms, both supervised and unsupervised, and its application to neuroimaging data provides a versatile tool to study the brain. PMID:24600388

  19. Neuroimaging of Semantic Processing in Schizophrenia: A Parametric Priming Approach

    PubMed Central

    Han, S. Duke; Wible, Cynthia G.

    2009-01-01

    The use of fMRI and other neuroimaging techniques in the study of cognitive language processes in psychiatric and non-psychiatric conditions has led at times to discrepant findings. Many issues complicate the study of language, especially in psychiatric populations. For example, the use of subtractive designs can produce misleading results. We propose and advocate for a semantic priming parametric approach to the study of semantic processing using fMRI methodology. Implications of this parametric approach are discussed in view of current functional neuroimaging research investigating the semantic processing disturbance of schizophrenia. PMID:19765623

  20. Neuroimaging data sharing on the neuroinformatics database platform.

    PubMed

    Book, Gregory A; Stevens, Michael C; Assaf, Michal; Glahn, David C; Pearlson, Godfrey D

    2016-01-01

    We describe the Neuroinformatics Database (NiDB), an open-source database platform for archiving, analysis, and sharing of neuroimaging data. Data from the multi-site projects Autism Brain Imaging Data Exchange (ABIDE), Bipolar-Schizophrenia Network on Intermediate Phenotypes parts one and two (B-SNIP1, B-SNIP2), and Monetary Incentive Delay task (MID) are available for download from the public instance of NiDB, with more projects sharing data as it becomes available. As demonstrated by making several large datasets available, NiDB is an extensible platform appropriately suited to archive and distribute shared neuroimaging data. PMID:25888923

  1. Neuroimaging the interaction of mind and metabolism in humans

    PubMed Central

    D’Agostino, Alexandra E.; Small, Dana M.

    2012-01-01

    Hormonal and metabolic signals interact with neural circuits orchestrating behavior to guide food intake. Neuroimaging techniques such as functional magnetic resonance imaging (fMRI) enable the identification of where in the brain particular mental processes like desire, satiety and pleasure occur. Once these neural circuits are described it then becomes possible to determine how metabolic and hormonal signals can alter brain response to influence psychological states and decision-making processes to guide intake. Here, we provide an overview of the contributions of functional neuroimaging to the understanding of how subjective and neural responses to food and food cues interact with metabolic/hormonal factors. PMID:24024114

  2. Neuroimaging data sharing on the neuroinformatics database platform.

    PubMed

    Book, Gregory A; Stevens, Michael C; Assaf, Michal; Glahn, David C; Pearlson, Godfrey D

    2016-01-01

    We describe the Neuroinformatics Database (NiDB), an open-source database platform for archiving, analysis, and sharing of neuroimaging data. Data from the multi-site projects Autism Brain Imaging Data Exchange (ABIDE), Bipolar-Schizophrenia Network on Intermediate Phenotypes parts one and two (B-SNIP1, B-SNIP2), and Monetary Incentive Delay task (MID) are available for download from the public instance of NiDB, with more projects sharing data as it becomes available. As demonstrated by making several large datasets available, NiDB is an extensible platform appropriately suited to archive and distribute shared neuroimaging data.

  3. AdS duals of matrix strings

    NASA Astrophysics Data System (ADS)

    Morales, Jose F.; Samtleben, Henning

    2003-06-01

    We review recent work on the holographic duals of type II and heterotic matrix string theories described by warped AdS3 supergravities. In particular, we compute the spectra of Kaluza-Klein primaries for type I, II supergravities on warped AdS3 × S7 and match them with the primary operators in the dual two-dimensional gauge theories. The presence of non-trivial warp factors and dilaton profiles requires a modification of the familiar dictionary between masses and 'scaling' dimensions of fields and operators. We present these modifications for the general case of domain wall/QFT correspondences between supergravities on warped AdSd+1 × Sq geometries and super Yang-Mills theories with 16 supercharges.

  4. A Novel Matrix-Similarity Based Loss Function for Joint Regression and Classification in AD Diagnosis

    PubMed Central

    Zhu, Xiaofeng; Suk, Heung-Il; Shen, Dinggang

    2014-01-01

    Recent studies on AD/MCI diagnosis have shown that the tasks of identifying brain disease and predicting clinical scores are highly related to each other. Furthermore, it has been shown that feature selection with a manifold learning or a sparse model can handle the problems of high feature dimensionality and small sample size. However, the tasks of clinical score regression and clinical label classification were often conducted separately in the previous studies. Regarding the feature selection, to our best knowledge, most of the previous work considered a loss function defined as an element-wise difference between the target values and the predicted ones. In this paper, we consider the problems of joint regression and classification for AD/MCI diagnosis and propose a novel matrix-similarity based loss function that uses high-level information inherent in the target response matrix and imposes the information to be preserved in the predicted response matrix. The newly devised loss function is combined with a group lasso method for joint feature selection across tasks, i.e., predictions of clinical scores and a class label. In order to validate the effectiveness of the proposed method, we conducted experiments on the Alzheimer’s Disease Neuroimaging Initiative (ADNI) dataset, and showed that the newly devised loss function helped enhance the performances of both clinical score prediction and disease status identification, outperforming the state-of-the-art methods. PMID:24911377

  5. Testing for association with multiple traits in generalized estimation equations, with application to neuroimaging data.

    PubMed

    Zhang, Yiwei; Xu, Zhiyuan; Shen, Xiaotong; Pan, Wei

    2014-08-01

    There is an increasing need to develop and apply powerful statistical tests to detect multiple traits-single locus associations, as arising from neuroimaging genetics and other studies. For example, in the Alzheimer's Disease Neuroimaging Initiative (ADNI), in addition to genome-wide single nucleotide polymorphisms (SNPs), thousands of neuroimaging and neuropsychological phenotypes as intermediate phenotypes for Alzheimer's disease, have been collected. Although some classic methods like MANOVA and newly proposed methods may be applied, they have their own limitations. For example, MANOVA cannot be applied to binary and other discrete traits. In addition, the relationships among these methods are not well understood. Importantly, since these tests are not data adaptive, depending on the unknown association patterns among multiple traits and between multiple traits and a locus, these tests may or may not be powerful. In this paper we propose a class of data-adaptive weights and the corresponding weighted tests in the general framework of generalized estimation equations (GEE). A highly adaptive test is proposed to select the most powerful one from this class of the weighted tests so that it can maintain high power across a wide range of situations. Our proposed tests are applicable to various types of traits with or without covariates. Importantly, we also analytically show relationships among some existing and our proposed tests, indicating that many existing tests are special cases of our proposed tests. Extensive simulation studies were conducted to compare and contrast the power properties of various existing and our new methods. Finally, we applied the methods to an ADNI dataset to illustrate the performance of the methods. We conclude with the recommendation for the use of the GEE-based Score test and our proposed adaptive test for their high and complementary performance.

  6. Neuroimaging: A Window to the Neurological Foundations of Learning and Behavior in Children.

    ERIC Educational Resources Information Center

    Lyon, G. Reid, Ed.; Rumsey, Judith M., Ed.

    This book presents 11 papers on the use of neuroimaging technology in brain-related disorders. The text contains full-color neuroimaging scans and provides both theoretical and methodological explanations of the various neuroimaging techniques and their application to developmental disorders in children. The papers are grouped into three sections,…

  7. Neuroimaging findings in late-onset schizophrenia and bipolar disorder.

    PubMed

    Hahn, Changtae; Lim, Hyun Kook; Lee, Chang Uk

    2014-03-01

    In recent years, there has been an increasing interest in late-onset mental disorders. Among them, geriatric schizophrenia and bipolar disorder are significant health care risks and major causes of disability. We discussed whether late-onset schizophrenia (LOS) and late-onset bipolar (LOB) disorder can be a separate entity from early-onset schizophrenia (EOS) and early-onset bipolar (EOB) disorder in a subset of late-life schizophrenia or late-life bipolar disorder through neuroimaging studies. A literature search for imaging studies of LOS or LOB was performed in the PubMed database. Search terms used were "(imaging OR MRI OR CT OR SPECT OR DTI OR PET OR fMRI) AND (schizophrenia or bipolar disorder) AND late onset." Articles that were published in English before October 2013 were included. There were a few neuroimaging studies assessing whether LOS and LOB had different disease-specific neural substrates compared with EOS and EOB. These researches mainly observed volumetric differences in specific brain regions, white matter hyperintensities, diffusion tensor imaging, or functional neuroimaging to explore the differences between LOS and LOB and EOS and EOB. The aim of this review was to highlight the neural substrates involved in LOS and LOB through neuroimaging studies. The exploration of neuroanatomical markers may be the key to the understanding of underlying neurobiology in LOS and LOB. PMID:24401535

  8. Neuroimaging in Psychiatric Pharmacogenetics Research: The Promise and Pitfalls

    PubMed Central

    Falcone, Mary; Smith, Ryan M; Chenoweth, Meghan J; Kumar Bhattacharjee, Abesh; Kelsoe, John R; Tyndale, Rachel F; Lerman, Caryn

    2013-01-01

    The integration of research on neuroimaging and pharmacogenetics holds promise for improving treatment for neuropsychiatric conditions. Neuroimaging may provide a more sensitive early measure of treatment response in genetically defined patient groups, and could facilitate development of novel therapies based on an improved understanding of pathogenic mechanisms underlying pharmacogenetic associations. This review summarizes progress in efforts to incorporate neuroimaging into genetics and treatment research on major psychiatric disorders, such as schizophrenia, major depressive disorder, bipolar disorder, attention-deficit/hyperactivity disorder, and addiction. Methodological challenges include: performing genetic analyses in small study populations used in imaging studies; inclusion of patients with psychiatric comorbidities; and the extensive variability across studies in neuroimaging protocols, neurobehavioral task probes, and analytic strategies. Moreover, few studies use pharmacogenetic designs that permit testing of genotype × drug effects. As a result of these limitations, few findings have been fully replicated. Future studies that pre-screen participants for genetic variants selected a priori based on drug metabolism and targets have the greatest potential to advance the science and practice of psychiatric treatment. PMID:23793356

  9. Neuroimaging of the Periaqueductal Gray: State of the Field

    PubMed Central

    Linnman, Clas; Moulton, Eric A.; Barmettler, Gabi; Becerra, Lino; Borsook, David

    2011-01-01

    This review and meta-analysis aims at summarizing and integrating the human neuroimaging studies that report periaqueductal gray (PAG) involvement; 250 original manuscripts on human neuroimaging of the PAG were identified. A narrative review and meta-analysis using activation likelihood estimates is included. Behaviors covered include pain and pain modulation, anxiety, bladder and bowel function and autonomic regulation. Methods include structural and functional magnetic resonance imaging, functional connectivity measures, diffusion weighted imaging and positron emission tomography. Human neuroimaging studies in healthy and clinical populations largely confirm the animal literature indicating that the PAG is involved in homeostatic regulation of salient functions such as pain, anxiety and autonomic function. Methodological concerns in the current literature, including resolution constraints, imaging artifacts and imprecise neuroanatomical labeling are discussed, and future directions are proposed. A general conclusion is that PAG neuroimaging is a field with enormous potential to translate animal data onto human behaviors, but with some growing pains that can and need to be addressed in order to add to our understanding of the neurobiology of this key region. PMID:22197740

  10. Uncovering the etiology of conversion disorder: insights from functional neuroimaging.

    PubMed

    Ejareh Dar, Maryam; Kanaan, Richard Aa

    2016-01-01

    Conversion disorder (CD) is a syndrome of neurological symptoms arising without organic cause, arguably in response to emotional stress, but the exact neural substrates of these symptoms and the underlying mechanisms remain poorly understood with the hunt for a biological basis afoot for centuries. In the past 15 years, novel insights have been gained with the advent of functional neuroimaging studies in patients suffering from CDs in both motor and nonmotor domains. This review summarizes recent functional neuroimaging studies including functional magnetic resonance imaging (fMRI), single photon emission computerized tomography (SPECT), and positron emission tomography (PET) to see whether they bring us closer to understanding the etiology of CD. Convergent functional neuroimaging findings suggest alterations in brain circuits that could point to different mechanisms for manifesting functional neurological symptoms, in contrast with feigning or healthy controls. Abnormalities in emotion processing and in emotion-motor processing suggest a diathesis, while differential reactions to certain stressors implicate a specific response to trauma. No comprehensive theory emerges from these clues, and all results remain preliminary, but functional neuroimaging has at least given grounds for hope that a model for CD may soon be found. PMID:26834476

  11. Uncovering the etiology of conversion disorder: insights from functional neuroimaging.

    PubMed

    Ejareh Dar, Maryam; Kanaan, Richard Aa

    2016-01-01

    Conversion disorder (CD) is a syndrome of neurological symptoms arising without organic cause, arguably in response to emotional stress, but the exact neural substrates of these symptoms and the underlying mechanisms remain poorly understood with the hunt for a biological basis afoot for centuries. In the past 15 years, novel insights have been gained with the advent of functional neuroimaging studies in patients suffering from CDs in both motor and nonmotor domains. This review summarizes recent functional neuroimaging studies including functional magnetic resonance imaging (fMRI), single photon emission computerized tomography (SPECT), and positron emission tomography (PET) to see whether they bring us closer to understanding the etiology of CD. Convergent functional neuroimaging findings suggest alterations in brain circuits that could point to different mechanisms for manifesting functional neurological symptoms, in contrast with feigning or healthy controls. Abnormalities in emotion processing and in emotion-motor processing suggest a diathesis, while differential reactions to certain stressors implicate a specific response to trauma. No comprehensive theory emerges from these clues, and all results remain preliminary, but functional neuroimaging has at least given grounds for hope that a model for CD may soon be found.

  12. Uncovering the etiology of conversion disorder: insights from functional neuroimaging

    PubMed Central

    Ejareh dar, Maryam; Kanaan, Richard AA

    2016-01-01

    Conversion disorder (CD) is a syndrome of neurological symptoms arising without organic cause, arguably in response to emotional stress, but the exact neural substrates of these symptoms and the underlying mechanisms remain poorly understood with the hunt for a biological basis afoot for centuries. In the past 15 years, novel insights have been gained with the advent of functional neuroimaging studies in patients suffering from CDs in both motor and nonmotor domains. This review summarizes recent functional neuroimaging studies including functional magnetic resonance imaging (fMRI), single photon emission computerized tomography (SPECT), and positron emission tomography (PET) to see whether they bring us closer to understanding the etiology of CD. Convergent functional neuroimaging findings suggest alterations in brain circuits that could point to different mechanisms for manifesting functional neurological symptoms, in contrast with feigning or healthy controls. Abnormalities in emotion processing and in emotion-motor processing suggest a diathesis, while differential reactions to certain stressors implicate a specific response to trauma. No comprehensive theory emerges from these clues, and all results remain preliminary, but functional neuroimaging has at least given grounds for hope that a model for CD may soon be found. PMID:26834476

  13. Flickering admissibility: neuroimaging evidence in the U.S. courts.

    PubMed

    Moriarty, Jane Campbell

    2008-01-01

    This article explores the admissibility of neuroimaging evidence in U.S. courts, recognizing various trends in decisions about such evidence.While courts have routinely admitted some neuroimages, such as CT scans and MRI, as proof of trauma and disease, they have been more circumspect about admitting the PET and SPECT scans and fMRI evidence. With the latter technologies, courts have often expressed reservations about what can be inferred from the images. Moreover, courts seem unwilling to find neuroimaging sufficient to prove either insanity or incompetency, but are relatively lenient about admitting neuroimages in death penalty hearings. Some claim that fMRI and "brain fingerprinting" are able to detect deception. Other scholars argue that brain fingerprinting is a dubious concept and that fMRI is not yet sufficiently reliable. Moreover, there are substantial concerns about privacy and the perils of mind reading implicit in such technology. Yet, there is a movement to try to make these new technologies "courtroom ready" in the near future, raising a host of legal, policy, and ethical questions to be answered.

  14. MANIA-a pattern classification toolbox for neuroimaging data.

    PubMed

    Grotegerd, Dominik; Redlich, Ronny; Almeida, Jorge R C; Riemenschneider, Mona; Kugel, Harald; Arolt, Volker; Dannlowski, Udo

    2014-07-01

    Conventional univariate statistics are common and widespread in neuroimaging research. However, functional and structural MRI data reveal a multivariate nature, since neighboring voxels are highly correlated and different localized brain regions activate interdependently. Multivariate pattern classification techniques are capable of overcoming shortcomings of univariate statistics. A rising interest in such approaches on neuroimaging data leads to an increasing demand of appropriate software and tools in this field. Here, we introduce and release MANIA-Machine learning Application for NeuroImaging Analyses. MANIA is a Matlab based software toolbox enabling easy pattern classification of neuroimaging data and offering a broad assortment of machine learning algorithms and feature selection methods. Between groups classifications are the main scope of this software, for instance the differentiation between patients and controls. A special emphasis was placed on an intuitive and easy to use graphical user interface allowing quick implementation and guidance also for clinically oriented researchers. MANIA is free and open source, published under GPL3 license. This work will give an overview regarding the functionality and the modular software architecture as well as a comparison between other software packages.

  15. 25 years of neuroimaging in amyotrophic lateral sclerosis

    PubMed Central

    Foerster, Bradley R.; Welsh, Robert C.; Feldman, Eva L.

    2014-01-01

    Amyotrophic lateral sclerosis (ALS) is a fatal motor neuron disease for which a precise cause has not yet been identified. Standard CT or MRI evaluation does not demonstrate gross structural nervous system changes in ALS, so conventional neuroimaging techniques have provided little insight into the pathophysiology of this disease. Advanced neuroimaging techniques—such as structural MRI, diffusion tensor imaging and proton magnetic resonance spectroscopy—allow evaluation of alterations of the nervous system in ALS. These alterations include focal loss of grey and white matter and reductions in white matter tract integrity, as well as changes in neural networks and in the chemistry, metabolism and receptor distribution in the brain. Given their potential for investigation of both brain structure and function, advanced neuroimaging methods offer important opportunities to improve diagnosis, guide prognosis, and direct future treatment strategies in ALS. In this article, we review the contributions made by various advanced neuroimaging techniques to our understanding of the impact of ALS on different brain regions, and the potential role of such measures in biomarker development. PMID:23917850

  16. Neuroimaging Research with Children: Ethical Issues and Case Scenarios

    ERIC Educational Resources Information Center

    Coch, Donna

    2007-01-01

    There are few available resources for learning and teaching about ethical issues in neuroimaging research with children, who constitute a special and vulnerable population. Here, a brief review of ethical issues in developmental research, situated within the emerging field of neuroethics, highlights the increasingly interdisciplinary nature of…

  17. Functional neuroimaging of emotional learning and autonomic reactions.

    PubMed

    Peper, Martin; Herpers, Martin; Spreer, Joachim; Hennig, Jürgen; Zentner, Josef

    2006-06-01

    This article provides a selective overview of the functional neuroimaging literature with an emphasis on emotional activation processes. Emotions are fast and flexible response systems that provide basic tendencies for adaptive action. From the range of involved component functions, we first discuss selected automatic mechanisms that control basic adaptational changes. Second, we illustrate how neuroimaging work has contributed to the mapping of the network components associated with basic emotion families (fear, anger, disgust, happiness), and secondary dimensional concepts that organise the meaning space for subjective experience and verbal labels (emotional valence, activity/intensity, approach/withdrawal, etc.). Third, results and methodological difficulties are discussed in view of own neuroimaging experiments that investigated the component functions involved in emotional learning. The amygdala, prefrontal cortex, and striatum form a network of reciprocal connections that show topographically distinct patterns of activity as a correlate of up and down regulation processes during an emotional episode. Emotional modulations of other brain systems have attracted recent research interests. Emotional neuroimaging calls for more representative designs that highlight the modulatory influences of regulation strategies and socio-cultural factors responsible for inhibitory control and extinction. We conclude by emphasising the relevance of the temporal process dynamics of emotional activations that may provide improved prediction of individual differences in emotionality.

  18. A Developmental Neuroimaging Investigation of the Change Paradigm

    ERIC Educational Resources Information Center

    Thomas, Laura A.; Hall, Julie M.; Skup, Martha; Jenkins, Sarah E.; Pine, Daniel S.; Leibenluft, Ellen

    2011-01-01

    This neuroimaging study examines the development of cognitive flexibility using the Change task in a sample of youths and adults. The Change task requires subjects to inhibit a prepotent response and substitute an alternative response, and the task incorporates an algorithm that adjusts task difficulty in response to subject performance. Data from…

  19. Neuroimaging characteristics of patients with focal hand dystonia.

    PubMed

    Hinkley, Leighton B N; Webster, Rebecca L; Byl, Nancy N; Nagarajan, Srikantan S

    2009-01-01

    NARRATIVE REVIEW: Advances in structural and functional imaging have provided both scientists and clinicians with information about the neural mechanisms underlying focal hand dystonia (FHd), a motor disorder associated with aberrant posturing and patterns of muscle contraction specific to movements of the hand. Consistent with the hypothesis that FHd is the result of reorganization in cortical fields, studies in neuroimaging have confirmed alterations in the topography and response properties of somatosensory and motor areas of the brain. Noninvasive stimulation of these regions also demonstrates that FHd may be due to reductions in inhibition between competing sensory and motor representations. Compromises in neuroanatomical structure, such as white matter density and gray matter volume, have also been identified through neuroimaging methods. These advances in neuroimaging have provided clinicians with an expanded understanding of the changes in the brain that contribute to FHd. These findings should provide a foundation for the development of retraining paradigms focused on reversing overlapping sensory representations and interactions between brain regions in patients with FHd. Continued collaborations between health professionals who treat FHd and research scientists who examine the brain using neuroimaging tools are imperative for answering difficult questions about patients with specific movement disorders. PMID:19217255

  20. Diagnostic and therapeutic utility of neuroimaging in depression: an overview

    PubMed Central

    Wise, Toby; Cleare, Anthony J; Herane, Andrés; Young, Allan H; Arnone, Danilo

    2014-01-01

    A growing number of studies have used neuroimaging to further our understanding of how brain structure and function are altered in major depression. More recently, these techniques have begun to show promise for the diagnosis and treatment of depression, both as aids to conventional methods and as methods in their own right. In this review, we describe recent neuroimaging findings in the field that might aid diagnosis and improve treatment accuracy. Overall, major depression is associated with numerous structural and functional differences in neural systems involved in emotion processing and mood regulation. Furthermore, several studies have shown that the structure and function of these systems is changed by pharmacological and psychological treatments of the condition and that these changes in candidate brain regions might predict clinical response. More recently, “machine learning” methods have used neuroimaging data to categorize individual patients according to their diagnostic status and predict treatment response. Despite being mostly limited to group-level comparisons at present, with the introduction of new methods and more naturalistic studies, neuroimaging has the potential to become part of the clinical armamentarium and may improve diagnostic accuracy and inform treatment choice at the patient level. PMID:25187715

  1. Renewal of the neurophysiology of language: functional neuroimaging.

    PubMed

    Démonet, Jean-François; Thierry, Guillaume; Cardebat, Dominique

    2005-01-01

    Functional neuroimaging methods have reached maturity. It is now possible to start to build the foundations of a physiology of language. The remarkable number of neuroimaging studies performed so far illustrates the potential of this approach, which complements the classical knowledge accumulated on aphasia. Here we attempt to characterize the impact of the functional neuroimaging revolution on our understanding of language. Although today considered as neuroimaging techniques, we refer less to electroencephalography and magnetoencephalography studies than to positron emission tomography and functional magnetic resonance imaging studies, which deal more directly with the question of localization and functional neuroanatomy. This review is structured in three parts. 1) Because of their rapid evolution, we address technical and methodological issues to provide an overview of current procedures and sketch out future perspectives. 2) We review a set of significant results acquired in normal adults (the core of functional imaging studies) to provide an overview of language mechanisms in the "standard" brain. Single-word processing is considered in relation to input modalities (visual and auditory input), output modalities (speech and written output), and the involvement of "central" semantic processes before sentence processing and nonstandard language (illiteracy, multilingualism, and sensory deficits) are addressed. 3) We address the influence of plasticity on physiological functions in relation to its main contexts of appearance, i.e., development and brain lesions, to show how functional imaging can allow fine-grained approaches to adaptation, the fundamental property of the brain. In closing, we consider future developments for language research using functional imaging.

  2. The Bilingual Brain as Revealed by Functional Neuroimaging.

    ERIC Educational Resources Information Center

    Abutalebi, Jubin; Cappa, Stefano F.; Perani, Daniela

    2001-01-01

    Functional neuroimaging of bilinguals and monolinguals used in conjunction with experimental cognitive tasks has been successful in establishing functional specialization as a principle of brain organization in humans. Consistent results show that attained proficiency and possibly language exposure are more important than age of acquisition as a…

  3. Cognitive Improvement after Mild Traumatic Brain Injury Measured with Functional Neuroimaging during the Acute Period.

    PubMed

    Wylie, Glenn R; Freeman, Kalev; Thomas, Alex; Shpaner, Marina; OKeefe, Michael; Watts, Richard; Naylor, Magdalena R

    2015-01-01

    Functional neuroimaging studies in mild traumatic brain injury (mTBI) have been largely limited to patients with persistent post-concussive symptoms, utilizing images obtained months to years after the actual head trauma. We sought to distinguish acute and delayed effects of mild traumatic brain injury on working memory functional brain activation patterns < 72 hours after mild traumatic brain injury (mTBI) and again one-week later. We hypothesized that clinical and fMRI measures of working memory would be abnormal in symptomatic mTBI patients assessed < 72 hours after injury, with most patients showing clinical recovery (i.e., improvement in these measures) within 1 week after the initial assessment. We also hypothesized that increased memory workload at 1 week following injury would expose different cortical activation patterns in mTBI patients with persistent post-concussive symptoms, compared to those with full clinical recovery. We performed a prospective, cohort study of working memory in emergency department patients with isolated head injury and clinical diagnosis of concussion, compared to control subjects (both uninjured volunteers and emergency department patients with extremity injuries and no head trauma). The primary outcome of cognitive recovery was defined as resolution of reported cognitive impairment and quantified by scoring the subject's reported cognitive post-concussive symptoms at 1 week. Secondary outcomes included additional post-concussive symptoms and neurocognitive testing results. We enrolled 46 subjects: 27 with mild TBI and 19 controls. The time of initial neuroimaging was 48 (+22 S.D.) hours after injury (time 1). At follow up (8.7, + 1.2 S.D., days after injury, time 2), 18 of mTBI subjects (64%) reported moderate to complete cognitive recovery, 8 of whom fully recovered between initial and follow-up imaging. fMRI changes from time 1 to time 2 showed an increase in posterior cingulate activation in the mTBI subjects compared to

  4. Neuroimaging of hippocampal atrophy in early recognition of Alzheimer's disease--a critical appraisal after two decades of research.

    PubMed

    Schröder, Johannes; Pantel, Johannes

    2016-01-30

    As a characteristic feature of Alzheimer's disease (AD) hippocampal atrophy (HA) can be demonstrated in the majority of patients by using neuroimaging techniques in particular magnetic resonance imaging (MRI). Hippocampal atrophy is associated with declarative memory deficits and can also be associated with changes of adjacent medial temporal substructures such as the parahippocampal gyrus or the the entorhinal cortex. Similar findings are present in patients with mild cognitive impairment (MCI) albeit to a lesser extent. While these finding facilitate the diagnostic process in patients with clinical suspicious AD, the metric properties of hippocampal atrophy for delineating healthy aging from MCI and mild AD still appear to be rather limited; as such it is not sufficient to establish the diagnosis of AD (and even more so of MCI). This limitation partly refers to methodological issues and partly to the fact that hippocampal tissue integrity is subject to various pathogenetic influences other than AD. Moreover,the effects of hippocampal atrophy on the behavioral level (e.g. cognitive deficits) are modulated by the individual's cognitive reserve. From a clinical standpoint these observations are in line with the hypothesis that the onset and course of AD is influenced by a number of peristatic factors which are partly conceptualized in the concepts of brain and/or cognitive reserve. These complex interactions have to be considered when using the presence of hippocampal atrophy in the routine diagnostic procedure of AD.

  5. Agricultural Education: Value Adding.

    ERIC Educational Resources Information Center

    Riesenberg, Lou E.; And Others

    1989-01-01

    This issue develops the theme of "Agricultural Education--Value Adding." The concept value adding has been a staple in the world of agricultural business for describing adding value to a commodity that would profit the producer and the local community. Agricultural education should add value to individuals and society to justify agricultural…

  6. Sharing privacy-sensitive access to neuroimaging and genetics data: a review and preliminary validation

    PubMed Central

    Sarwate, Anand D.; Plis, Sergey M.; Turner, Jessica A.; Arbabshirani, Mohammad R.; Calhoun, Vince D.

    2014-01-01

    The growth of data sharing initiatives for neuroimaging and genomics represents an exciting opportunity to confront the “small N” problem that plagues contemporary neuroimaging studies while further understanding the role genetic markers play in the function of the brain. When it is possible, open data sharing provides the most benefits. However, some data cannot be shared at all due to privacy concerns and/or risk of re-identification. Sharing other data sets is hampered by the proliferation of complex data use agreements (DUAs) which preclude truly automated data mining. These DUAs arise because of concerns about the privacy and confidentiality for subjects; though many do permit direct access to data, they often require a cumbersome approval process that can take months. An alternative approach is to only share data derivatives such as statistical summaries—the challenges here are to reformulate computational methods to quantify the privacy risks associated with sharing the results of those computations. For example, a derived map of gray matter is often as identifiable as a fingerprint. Thus alternative approaches to accessing data are needed. This paper reviews the relevant literature on differential privacy, a framework for measuring and tracking privacy loss in these settings, and demonstrates the feasibility of using this framework to calculate statistics on data distributed at many sites while still providing privacy. PMID:24778614

  7. A transformation similarity constraint for groupwise nonlinear registration in longitudinal neuroimaging studies

    NASA Astrophysics Data System (ADS)

    Fleishman, Greg M.; Gutman, Boris A.; Fletcher, P. Thomas; Thompson, Paul

    2015-03-01

    Patients with Alzheimer's disease and other brain disorders often show a similar spatial distribution of volume change throughout the brain over time, but this information is not yet used in registration algorithms to refine the quantification of change. Here, we develop a mathematical basis to incorporate that prior information into a longitudinal structural neuroimaging study. We modify the canonical minimization problem for non-linear registration to include a term that couples a collection of registrations together to enforce group similarity. More specifically, throughout the computation we maintain a group-level representation of the transformations and constrain updates to individual transformations to be similar to this representation. The derivations necessary to produce the Euler-Lagrange equations for the coupling term are presented and a gradient descent algorithm based on the formulation was implemented. We demonstrate using 57 longitudinal image pairs from the Alzheimer's Disease Neuroimaging Initiative (ADNI) that longitudinal registration with such a groupwise coupling prior is more robust to noise in estimating change, suggesting such change maps may have several important applications.

  8. Identifying Treatment Response of Sertraline in a Teenager with Selective Mutism using Electrophysiological Neuroimaging

    PubMed Central

    Eugene, Andy R.; Masiak, Jolanta

    2016-01-01

    Background Selective Mutism is described as the inability to verbally express oneself in anxiety provoking social situations and may result in awkward social interactions in school-aged children. In this case-report we present the baseline electrophysiological neuroimaging results and after treatment with Sertraline for 6-weeks. Methods A 20-channel EEG event-related potential recording was acquired during an internal voice task at baseline prior to the initiation of 50mg of Sertraline and then repeated 6-weeks after treatment with Sertraline. EEG signals were processed for movement, eye-blink, and muscle artifacts and ERP signal averaging was completed. ERPs were analyzed using Standard Low Resolution Brain Electromagnetic Tomography (sLORETA). Results At baseline, Sertraline increased the neuronal activation in the middle temporal gyrus and the anterior cingulate gyrus from baseline in the patient following 6-weeks of treatment. Conclusion Our findings suggest that electrophysiological neuroimaging may provide a creative approach for personalizing medicine by providing insight to the pharmacodynamics of antidepressants. PMID:27468379

  9. Neuroimaging in Central Nervous System Lymphoma.

    PubMed

    Nabavizadeh, Seyed Ali; Vossough, Arastoo; Hajmomenian, Mehrdad; Assadsangabi, Reza; Mohan, Suyash

    2016-08-01

    Primary central nervous system lymphoma (PCNSL) is a rare aggressive high-grade type of extranodal lymphoma. PCNSL can have a variable imaging appearance and can mimic other brain disorders such as encephalitis, demyelination, and stroke. In addition to PCNSL, the CNS can be secondarily involved by systemic lymphoma. Computed tomography and conventional MRI are the initial imaging modalities to evaluate these lesions. Recently, however, advanced MRI techniques are more often used in an effort to narrow the differential diagnosis and potentially inform diagnostic and therapeutic decisions. PMID:27443998

  10. Neuroimaging schizophrenia: a picture is worth a thousand words, but is it saying anything important?

    PubMed

    Ahmed, Anthony O; Buckley, Peter F; Hanna, Mona

    2013-03-01

    Schizophrenia is characterized by neurostructural and neurofunctional aberrations that have now been demonstrated through neuroimaging research. The article reviews recent studies that have attempted to use neuroimaging to understand the relation between neurological abnormalities and aspects of the phenomenology of schizophrenia. Neuroimaging studies show that neurostructural and neurofunctional abnormalities are present in people with schizophrenia and their close relatives and may represent putative endophenotypes. Neuroimaging phenotypes predict the emergence of psychosis in individuals classified as high-risk. Neuroimaging studies have linked structural and functional abnormalities to symptoms; and progressive structural changes to clinical course and functional outcome. Neuroimaging has successfully indexed the neurotoxic and neuroprotective effects of schizophrenia treatments. Pictures can inform about aspects of the phenomenology of schizophrenia including etiology, onset, symptoms, clinical course, and treatment effects but this assertion is tempered by the scientific and practical limitations of neuroimaging. PMID:23397252

  11. Whole genome association study of brain-wide imaging phenotypes for identifying quantitative trait loci in MCI and AD: A study of the ADNI cohort.

    PubMed

    Shen, Li; Kim, Sungeun; Risacher, Shannon L; Nho, Kwangsik; Swaminathan, Shanker; West, John D; Foroud, Tatiana; Pankratz, Nathan; Moore, Jason H; Sloan, Chantel D; Huentelman, Matthew J; Craig, David W; Dechairo, Bryan M; Potkin, Steven G; Jack, Clifford R; Weiner, Michael W; Saykin, Andrew J

    2010-11-15

    A genome-wide, whole brain approach to investigate genetic effects on neuroimaging phenotypes for identifying quantitative trait loci is described. The Alzheimer's Disease Neuroimaging Initiative 1.5 T MRI and genetic dataset was investigated using voxel-based morphometry (VBM) and FreeSurfer parcellation followed by genome-wide association studies (GWAS). One hundred forty-two measures of grey matter (GM) density, volume, and cortical thickness were extracted from baseline scans. GWAS, using PLINK, were performed on each phenotype using quality-controlled genotype and scan data including 530,992 of 620,903 single nucleotide polymorphisms (SNPs) and 733 of 818 participants (175 AD, 354 amnestic mild cognitive impairment, MCI, and 204 healthy controls, HC). Hierarchical clustering and heat maps were used to analyze the GWAS results and associations are reported at two significance thresholds (p<10(-7) and p<10(-6)). As expected, SNPs in the APOE and TOMM40 genes were confirmed as markers strongly associated with multiple brain regions. Other top SNPs were proximal to the EPHA4, TP63 and NXPH1 genes. Detailed image analyses of rs6463843 (flanking NXPH1) revealed reduced global and regional GM density across diagnostic groups in TT relative to GG homozygotes. Interaction analysis indicated that AD patients homozygous for the T allele showed differential vulnerability to right hippocampal GM density loss. NXPH1 codes for a protein implicated in promotion of adhesion between dendrites and axons, a key factor in synaptic integrity, the loss of which is a hallmark of AD. A genome-wide, whole brain search strategy has the potential to reveal novel candidate genes and loci warranting further investigation and replication.

  12. SchizConnect: Virtual Data Integration in Neuroimaging

    PubMed Central

    Ambite, Jose Luis; Tallis, Marcelo; Alpert, Kathryn; Keator, David B.; King, Margaret; Landis, Drew; Konstantinidis, George; Calhoun, Vince D.; Potkin, Steven G.; Turner, Jessica A.; Wang, Lei

    2015-01-01

    In many scientific domains, including neuroimaging studies, there is a need to obtain increasingly larger cohorts to achieve the desired statistical power for discovery. However, the economics of imaging studies make it unlikely that any single study or consortia can achieve the desired sample sizes. What is needed is an architecture that can easily incorporate additional studies as they become available. We present such architecture based on a virtual data integration approach, where data remains at the original sources, and is retrieved and harmonized in response to user queries. This is in contrast to approaches that move the data to a central warehouse. We implemented our approach in the SchizConnect system that integrates data from three neuroimaging consortia on Schizophrenia: FBIRN's Human Imaging Database (HID), MRN's Collaborative Imaging and Neuroinformatics System (COINS), and the NUSDAST project at XNAT Central. A portal providing harmonized access to these sources is publicly deployed at schizconnect.org. PMID:26688837

  13. Functional Neuro-Imaging and Post-Traumatic Olfactory Impairment

    PubMed Central

    Roberts, Richard J.; Sheehan, William; Thurber, Steven; Roberts, Mary Ann

    2010-01-01

    Objective: To evaluate via a research literature survey the anterior neurological significance of decreased olfactory functioning following traumatic brain injuries. Materials and Methods: A computer literature review was performed to locate all functional neuro-imaging studies on patients with post-traumatic anosmia and other olfactory deficits. Results: A convergence of findings from nine functional neuro-imaging studies indicating evidence for reduced metabolic activity at rest or relative hypo-perfusion during olfactory activations. Hypo-activation of the prefrontal regions was apparent in all nine post-traumatic samples, with three samples yielding evidence of reduced activity in the temporal regions as well. Conclusions: The practical ramifications include the reasonable hypothesis that a total anosmic head trauma patient likely has frontal lobe involvement. PMID:21716782

  14. Neuroimaging the Effectiveness of Substance Use Disorder Treatments.

    PubMed

    Cabrera, Elizabeth A; Wiers, Corinde E; Lindgren, Elsa; Miller, Gregg; Volkow, Nora D; Wang, Gene-Jack

    2016-09-01

    Neuroimaging techniques to measure the function and biochemistry of the human brain such as positron emission tomography (PET), proton magnetic resonance spectroscopy ((1)H MRS), and functional magnetic resonance imaging (fMRI), are powerful tools for assessing neurobiological mechanisms underlying the response to treatments in substance use disorders. Here, we review the neuroimaging literature on pharmacological and behavioral treatment in substance use disorder. We focus on neural effects of medications that reduce craving (e.g., naltrexone, bupropion hydrochloride, baclofen, methadone, varenicline) and that improve cognitive control (e.g., modafinil, N-acetylcysteine), of behavioral treatments for substance use disorders (e.g., cognitive bias modification training, virtual reality, motivational interventions) and neuromodulatory interventions such as neurofeedback and transcranial magnetic stimulation. A consistent finding for the effectiveness of therapeutic interventions identifies the improvement of executive control networks and the dampening of limbic activation, highlighting their values as targets for therapeutic interventions in substance use disorders. PMID:27184387

  15. Meditation states and traits: EEG, ERP, and neuroimaging studies.

    PubMed

    Cahn, B Rael; Polich, John

    2006-03-01

    Neuroelectric and imaging studies of meditation are reviewed. Electroencephalographic measures indicate an overall slowing subsequent to meditation, with theta and alpha activation related to proficiency of practice. Sensory evoked potential assessment of concentrative meditation yields amplitude and latency changes for some components and practices. Cognitive event-related potential evaluation of meditation implies that practice changes attentional allocation. Neuroimaging studies indicate increased regional cerebral blood flow measures during meditation. Taken together, meditation appears to reflect changes in anterior cingulate cortex and dorsolateral prefrontal areas. Neurophysiological meditative state and trait effects are variable but are beginning to demonstrate consistent outcomes for research and clinical applications. Psychological and clinical effects of meditation are summarized, integrated, and discussed with respect to neuroimaging data.

  16. Structural Neuroimaging Findings in Mild Traumatic Brain Injury.

    PubMed

    Bigler, Erin D; Abildskov, Tracy J; Goodrich-Hunsaker, Naomi J; Black, Garrett; Christensen, Zachary P; Huff, Trevor; Wood, Dawn-Marie G; Hesselink, John R; Wilde, Elisabeth A; Max, Jeffrey E

    2016-09-01

    Common neuroimaging findings in mild traumatic brain injury (mTBI), including sport-related concussion (SRC), are reviewed based on computed tomography and magnetic resonance imaging (MRI). Common abnormalities radiologically identified on the day of injury, typically a computed tomographic scan, are in the form of contusions, small subarachnoid or intraparenchymal hemorrhages as well as subdural and epidural collections, edema, and skull fractures. Common follow-up neuroimaging findings with MRI include white matter hyperintensities, hypointense signal abnormalities that reflect prior hemorrhage, focal encephalomalacia, presence of atrophy and/or dilated Virchow-Robins perivascular space. The MRI findings from a large pediatric mTBI study show low frequency of positive MRI findings at 6 months postinjury. The review concludes with an examination of some of the advanced MRI-based image analysis methods that can be performed in the patient who has sustained an mTBI. PMID:27482782

  17. The role of neuroimaging in the diagnosis of headache disorders

    PubMed Central

    Obermann, Mark

    2013-01-01

    Headache is a common clinical feature in patients in the emergency room and in general neurology clinics. For physicians not experienced in headache disorders it might be difficult sometimes to decide in which patients neuroimaging is necessary to diagnose an underlying brain pathology and in which patients cerebral imaging is unnecessary. Most patients presenting to the primary-care physician with a nonacute headache and no further neurological signs or symptoms will not be suffering from an underlying serious condition. This review focuses on the main primary headache diseases, including migraine, tension-type headache and cluster headache, as well as frequent secondary headache entities with common clinical presentation and appropriate diagnostic and therapeutic algorithms to help guide the decision on the utilization of neuroimaging in the diagnostic workup. PMID:24228072

  18. Cognitive and emotional processes during dreaming: a neuroimaging view.

    PubMed

    Desseilles, Martin; Dang-Vu, Thien Thanh; Sterpenich, Virginie; Schwartz, Sophie

    2011-12-01

    Dream is a state of consciousness characterized by internally-generated sensory, cognitive and emotional experiences occurring during sleep. Dream reports tend to be particularly abundant, with complex, emotional, and perceptually vivid experiences after awakenings from rapid eye movement (REM) sleep. This is why our current knowledge of the cerebral correlates of dreaming, mainly derives from studies of REM sleep. Neuroimaging results show that REM sleep is characterized by a specific pattern of regional brain activity. We demonstrate that this heterogeneous distribution of brain activity during sleep explains many typical features in dreams. Reciprocally, specific dream characteristics suggest the activation of selective brain regions during sleep. Such an integration of neuroimaging data of human sleep, mental imagery, and the content of dreams is critical for current models of dreaming; it also provides neurobiological support for an implication of sleep and dreaming in some important functions such as emotional regulation.

  19. Pain perception and hypnosis: findings from recent functional neuroimaging studies.

    PubMed

    Del Casale, Antonio; Ferracuti, Stefano; Rapinesi, Chiara; Serata, Daniele; Caltagirone, Saverio Simone; Savoja, Valeria; Piacentino, Daria; Callovini, Gemma; Manfredi, Giovanni; Sani, Gabriele; Kotzalidis, Georgios D; Girardi, Paolo

    2015-01-01

    Hypnosis modulates pain perception and tolerance by affecting cortical and subcortical activity in brain regions involved in these processes. By reviewing functional neuroimaging studies focusing on pain perception under hypnosis, the authors aimed to identify brain activation-deactivation patterns occurring in hypnosis-modulated pain conditions. Different changes in brain functionality occurred throughout all components of the pain network and other brain areas. The anterior cingulate cortex appears to be central in modulating pain circuitry activity under hypnosis. Most studies also showed that the neural functions of the prefrontal, insular, and somatosensory cortices are consistently modified during hypnosis-modulated pain conditions. Functional neuroimaging studies support the clinical use of hypnosis in the management of pain conditions. PMID:25719519

  20. Visualization of nonlinear kernel models in neuroimaging by sensitivity maps.

    PubMed

    Rasmussen, Peter Mondrup; Madsen, Kristoffer Hougaard; Lund, Torben Ellegaard; Hansen, Lars Kai

    2011-04-01

    There is significant current interest in decoding mental states from neuroimages. In this context kernel methods, e.g., support vector machines (SVM) are frequently adopted to learn statistical relations between patterns of brain activation and experimental conditions. In this paper we focus on visualization of such nonlinear kernel models. Specifically, we investigate the sensitivity map as a technique for generation of global summary maps of kernel classification models. We illustrate the performance of the sensitivity map on functional magnetic resonance (fMRI) data based on visual stimuli. We show that the performance of linear models is reduced for certain scan labelings/categorizations in this data set, while the nonlinear models provide more flexibility. We show that the sensitivity map can be used to visualize nonlinear versions of kernel logistic regression, the kernel Fisher discriminant, and the SVM, and conclude that the sensitivity map is a versatile and computationally efficient tool for visualization of nonlinear kernel models in neuroimaging.

  1. Structural Neuroimaging Findings in Mild Traumatic Brain Injury.

    PubMed

    Bigler, Erin D; Abildskov, Tracy J; Goodrich-Hunsaker, Naomi J; Black, Garrett; Christensen, Zachary P; Huff, Trevor; Wood, Dawn-Marie G; Hesselink, John R; Wilde, Elisabeth A; Max, Jeffrey E

    2016-09-01

    Common neuroimaging findings in mild traumatic brain injury (mTBI), including sport-related concussion (SRC), are reviewed based on computed tomography and magnetic resonance imaging (MRI). Common abnormalities radiologically identified on the day of injury, typically a computed tomographic scan, are in the form of contusions, small subarachnoid or intraparenchymal hemorrhages as well as subdural and epidural collections, edema, and skull fractures. Common follow-up neuroimaging findings with MRI include white matter hyperintensities, hypointense signal abnormalities that reflect prior hemorrhage, focal encephalomalacia, presence of atrophy and/or dilated Virchow-Robins perivascular space. The MRI findings from a large pediatric mTBI study show low frequency of positive MRI findings at 6 months postinjury. The review concludes with an examination of some of the advanced MRI-based image analysis methods that can be performed in the patient who has sustained an mTBI.

  2. Genetic imaging consortium for addiction medicine: From neuroimaging to genes.

    PubMed

    Mackey, Scott; Kan, Kees-Jan; Chaarani, Bader; Alia-Klein, Nelly; Batalla, Albert; Brooks, Samantha; Cousijn, Janna; Dagher, Alain; de Ruiter, Michiel; Desrivieres, Sylvane; Feldstein Ewing, Sarah W; Goldstein, Rita Z; Goudriaan, Anna E; Heitzeg, Mary M; Hutchison, Kent; Li, Chiang-Shan R; London, Edythe D; Lorenzetti, Valentina; Luijten, Maartje; Martin-Santos, Rocio; Morales, Angelica M; Paulus, Martin P; Paus, Tomas; Pearlson, Godfrey; Schluter, Renée; Momenan, Reza; Schmaal, Lianne; Schumann, Gunter; Sinha, Rajita; Sjoerds, Zsuzsika; Stein, Dan J; Stein, Elliot A; Solowij, Nadia; Tapert, Susan; Uhlmann, Anne; Veltman, Dick; van Holst, Ruth; Walter, Henrik; Wright, Margaret J; Yucel, Murat; Yurgelun-Todd, Deborah; Hibar, Derrek P; Jahanshad, Neda; Thompson, Paul M; Glahn, David C; Garavan, Hugh; Conrod, Patricia

    2016-01-01

    Since the sample size of a typical neuroimaging study lacks sufficient statistical power to explore unknown genomic associations with brain phenotypes, several international genetic imaging consortia have been organized in recent years to pool data across sites. The challenges and achievements of these consortia are considered here with the goal of leveraging these resources to study addiction. The authors of this review have joined together to form an Addiction working group within the framework of the ENIGMA project, a meta-analytic approach to multisite genetic imaging data. Collectively, the Addiction working group possesses neuroimaging and genomic data obtained from over 10,000 subjects. The deadline for contributing data to the first round of analyses occurred at the beginning of May 2015. The studies performed on this data should significantly impact our understanding of the genetic and neurobiological basis of addiction.

  3. Neuroimaging in Animal Seizure Models with 18FDG-PET

    PubMed Central

    Mirrione, Martine M.; Tsirka, Stella E.

    2011-01-01

    Small animal neuroimaging has become increasingly available to researchers, expanding the breadth of questions studied with these methods. Applying these noninvasive techniques to the open questions underlying epileptogenesis is no exception. A major advantage of small animal neuroimaging is its translational appeal. Studies can be well controlled and manipulated, examining the living brain in the animal before, during, and after the disease onset or disease treatment. The results can also be compared to data collected on human patients. Over the past decade, we and others have explored metabolic patterns in animal models of epilepsy to gain insight into the circuitry underlying development of the disease. In this paper, we provide technical details on how metabolic imaging that uses 2-deoxy-2[18F]fluoro-D-glucose (18FDG) and positron emission tomography (PET) is performed and explain the strengths and limitations of these studies. We will also highlight recent advances toward understanding epileptogenesis through small animal imaging. PMID:22937232

  4. Neuroimaging the Effectiveness of Substance Use Disorder Treatments.

    PubMed

    Cabrera, Elizabeth A; Wiers, Corinde E; Lindgren, Elsa; Miller, Gregg; Volkow, Nora D; Wang, Gene-Jack

    2016-09-01

    Neuroimaging techniques to measure the function and biochemistry of the human brain such as positron emission tomography (PET), proton magnetic resonance spectroscopy ((1)H MRS), and functional magnetic resonance imaging (fMRI), are powerful tools for assessing neurobiological mechanisms underlying the response to treatments in substance use disorders. Here, we review the neuroimaging literature on pharmacological and behavioral treatment in substance use disorder. We focus on neural effects of medications that reduce craving (e.g., naltrexone, bupropion hydrochloride, baclofen, methadone, varenicline) and that improve cognitive control (e.g., modafinil, N-acetylcysteine), of behavioral treatments for substance use disorders (e.g., cognitive bias modification training, virtual reality, motivational interventions) and neuromodulatory interventions such as neurofeedback and transcranial magnetic stimulation. A consistent finding for the effectiveness of therapeutic interventions identifies the improvement of executive control networks and the dampening of limbic activation, highlighting their values as targets for therapeutic interventions in substance use disorders.

  5. Neuroimaging essentials in essential tremor: A systematic review

    PubMed Central

    Sharifi, Sarvi; Nederveen, Aart J.; Booij, Jan; van Rootselaar, Anne-Fleur

    2014-01-01

    Background Essential tremor is regarded to be a disease of the central nervous system. Neuroimaging is a rapidly growing field with potential benefits to both diagnostics and research. The exact role of imaging techniques with respect to essential tremor in research and clinical practice is not clear. A systematic review of the different imaging techniques in essential tremor is lacking in the literature. Methods We performed a systematic literature search combining the terms essential tremor and familial tremor with the following keywords: imaging, MRI, VBM, DWI, fMRI, PET and SPECT, both in abbreviated form as well as in full form. We summarize and discuss the quality and the external validity of each study and place the results in the context of existing knowledge regarding the pathophysiology of essential tremor. Results A total of 48 neuroimaging studies met our search criteria, roughly divided into 19 structural and 29 functional and metabolic studies. The quality of the studies varied, especially concerning inclusion criteria. Functional imaging studies indicated cerebellar hyperactivity during rest and during tremor. The studies also pointed to the involvement of the thalamus, the inferior olive and the red nucleus. Structural studies showed less consistent results. Discussion and conclusion Neuroimaging techniques in essential tremor give insight into the pathophysiology of essential tremor indicating the involvement of the cerebellum as the most consistent finding. GABAergic dysfunction might be a major premise in the pathophysiological hypotheses. Inconsistencies between studies can be partly explained by the inclusion of heterogeneous patient groups. Improvement of scientific research requires more stringent inclusion criteria and application of advanced analysis techniques. Also, the use of multimodal neuroimaging techniques is a promising development in movement disorders research. Currently, the role of imaging techniques in essential tremor in daily

  6. Neuroimaging correlates of aggression in schizophrenia: an update

    PubMed Central

    Hoptman, Matthew J.; Antonius, Daniel

    2015-01-01

    Purpose of review Aggression in schizophrenia is associated with poor treatment outcomes, hospital admissions, and stigmatization of patients. As such it represents an important public health issue. This article reviews recent neuroimaging studies of aggression in schizophrenia, focusing on PET/single photon emission computed tomography and MRI methods. Recent findings The neuroimaging literature on aggression in schizophrenia is in a period of development. This is attributable in part to the heterogeneous nature and basis of that aggression. Radiological methods have consistently shown reduced activity in frontal and temporal regions. MRI brain volumetric studies have been less consistent, with some studies finding increased volumes of inferior frontal structures, and others finding reduced volumes in aggressive individuals with schizophrenia. Functional MRI studies have also had inconsistent results, with most finding reduced activity in inferior frontal and temporal regions, but some also finding increased activity in other regions. Some studies have made a distinction between types of aggression in schizophrenia in the context of antisocial traits, and this appears to be useful in understanding the neuroimaging literature. Summary Frontal and temporal abnormalities appear to be a consistent feature of aggression in schizophrenia, but their precise nature likely differs because of the heterogeneous nature of that behavior. PMID:21178624

  7. Research Updates in Neuroimaging Studies of Children Who Stutter

    PubMed Central

    Chang, Soo-Eun

    2016-01-01

    In the past two decades, neuroimaging investigations of stuttering have led to important discoveries of structural and functional brain differences in people who stutter, providing significant clues to the neurological basis of stuttering. One major limitation, however, has been that most studies so far have only examined adults who stutter, whose brain and behavior likely would have adopted compensatory reactions to their stuttering; these confounding factors have made interpretations of the findings difficult. Developmental stuttering is a neurodevelopmental condition, and like many other neurodevelopmental disorders, stuttering is associated with an early childhood onset of symptoms and greater incidence in males relative to females. More recent studies have begun to examine children who stutter using various neuroimaging techniques that allow examination of functional neuroanatomy and interaction of major brain areas that differentiate children who stutter compared with age-matched controls. In this article, I review these more recent neuroimaging investigations of children who stutter, in the context of what we know about typical brain development, neuroplasticity, and sex differences relevant to speech and language development. Although the picture is still far from complete, these studies have potential to provide information that can be used as early objective markers, or prognostic indicators, for persistent stuttering in the future. Furthermore, these studies are the first steps in finding potential neural targets for novel therapies that may involve modulating neuroplastic growth conducive to developing and maintaining fluent speech, which can be applied to treatment of young children who stutter. PMID:24875668

  8. Robust regression for large-scale neuroimaging studies.

    PubMed

    Fritsch, Virgile; Da Mota, Benoit; Loth, Eva; Varoquaux, Gaël; Banaschewski, Tobias; Barker, Gareth J; Bokde, Arun L W; Brühl, Rüdiger; Butzek, Brigitte; Conrod, Patricia; Flor, Herta; Garavan, Hugh; Lemaitre, Hervé; Mann, Karl; Nees, Frauke; Paus, Tomas; Schad, Daniel J; Schümann, Gunter; Frouin, Vincent; Poline, Jean-Baptiste; Thirion, Bertrand

    2015-05-01

    Multi-subject datasets used in neuroimaging group studies have a complex structure, as they exhibit non-stationary statistical properties across regions and display various artifacts. While studies with small sample sizes can rarely be shown to deviate from standard hypotheses (such as the normality of the residuals) due to the poor sensitivity of normality tests with low degrees of freedom, large-scale studies (e.g. >100 subjects) exhibit more obvious deviations from these hypotheses and call for more refined models for statistical inference. Here, we demonstrate the benefits of robust regression as a tool for analyzing large neuroimaging cohorts. First, we use an analytic test based on robust parameter estimates; based on simulations, this procedure is shown to provide an accurate statistical control without resorting to permutations. Second, we show that robust regression yields more detections than standard algorithms using as an example an imaging genetics study with 392 subjects. Third, we show that robust regression can avoid false positives in a large-scale analysis of brain-behavior relationships with over 1500 subjects. Finally we embed robust regression in the Randomized Parcellation Based Inference (RPBI) method and demonstrate that this combination further improves the sensitivity of tests carried out across the whole brain. Altogether, our results show that robust procedures provide important advantages in large-scale neuroimaging group studies. PMID:25731989

  9. Neuroimaging: Technologies at the Interface of Genes, Brain and Behavior

    PubMed Central

    Bigos, Kristin L.; Hariri, Ahmad R.

    2007-01-01

    Synopsis Neuroimaging technologies, because of their unique ability to capture the structural and functional integrity of distributed neural circuitries within individuals, provide a powerful approach to explore the genetic basis of individual differences in complex behaviors and vulnerability to neuropsychiatric illness. Functional magnetic resonance imaging (MRI) studies especially have established important physiological links between genetic polymorphisms and robust differences in information processing within distinct brain regions and circuits that have been linked to the manifestation of various disease states such as Alzheimer’s disease, schizophrenia and depression. Importantly, many of these biological relationships have been revealed in relatively small samples of subjects and in the absence of observable differences at the level of behavior, underscoring the power of a direct assay of brain anatomy and physiology in exploring the functional impact of genetic variation. Through the continued integration of genes, brain and behavior, neuroimaging technologies represent a critical tool in ongoing efforts to understand the neurobiology of normal and pathological behavioral states. Multidisciplinary research capitalizing on such neuroimaging-based integration will contribute to the identification of predictive markers and biological pathways for neuropsychiatric disease vulnerability as well as the generation of novel targets for therapeutic intervention. PMID:17983963

  10. Robust regression for large-scale neuroimaging studies.

    PubMed

    Fritsch, Virgile; Da Mota, Benoit; Loth, Eva; Varoquaux, Gaël; Banaschewski, Tobias; Barker, Gareth J; Bokde, Arun L W; Brühl, Rüdiger; Butzek, Brigitte; Conrod, Patricia; Flor, Herta; Garavan, Hugh; Lemaitre, Hervé; Mann, Karl; Nees, Frauke; Paus, Tomas; Schad, Daniel J; Schümann, Gunter; Frouin, Vincent; Poline, Jean-Baptiste; Thirion, Bertrand

    2015-05-01

    Multi-subject datasets used in neuroimaging group studies have a complex structure, as they exhibit non-stationary statistical properties across regions and display various artifacts. While studies with small sample sizes can rarely be shown to deviate from standard hypotheses (such as the normality of the residuals) due to the poor sensitivity of normality tests with low degrees of freedom, large-scale studies (e.g. >100 subjects) exhibit more obvious deviations from these hypotheses and call for more refined models for statistical inference. Here, we demonstrate the benefits of robust regression as a tool for analyzing large neuroimaging cohorts. First, we use an analytic test based on robust parameter estimates; based on simulations, this procedure is shown to provide an accurate statistical control without resorting to permutations. Second, we show that robust regression yields more detections than standard algorithms using as an example an imaging genetics study with 392 subjects. Third, we show that robust regression can avoid false positives in a large-scale analysis of brain-behavior relationships with over 1500 subjects. Finally we embed robust regression in the Randomized Parcellation Based Inference (RPBI) method and demonstrate that this combination further improves the sensitivity of tests carried out across the whole brain. Altogether, our results show that robust procedures provide important advantages in large-scale neuroimaging group studies.

  11. Effects of neuroimaging evidence on mock juror decision making.

    PubMed

    Greene, Edith; Cahill, Brian S

    2012-01-01

    During the penalty phase of capital trials, defendants may introduce mitigating evidence that argues for a punishment "less than death." In the past few years, a novel form of mitigating evidence-brain scans made possible by technological advances in neuroscience-has been proffered by defendants to support claims that brain abnormalities reduce their culpability. This exploratory study assessed the impact of neuroscience evidence on mock jurors' sentencing recommendations and impressions of a capital defendant. Using actual case facts, we manipulated diagnostic evidence presented by the defense (psychosis diagnosis; diagnosis and neuropsychological test results; or diagnosis, test results, and neuroimages) and future dangerousness evidence presented by the prosecution (low or high risk). Recommendations for death sentences were affected by the neuropsychological and neuroimaging evidence: defendants deemed at high risk for future dangerousness were less likely to be sentenced to death when jurors had this evidence than when they did not. Neuropsychological and neuroimaging evidence also had mitigating effects on impressions of the defendant. We describe study limitations and pose questions for further research.

  12. Effects of neuroimaging evidence on mock juror decision making.

    PubMed

    Greene, Edith; Cahill, Brian S

    2012-01-01

    During the penalty phase of capital trials, defendants may introduce mitigating evidence that argues for a punishment "less than death." In the past few years, a novel form of mitigating evidence-brain scans made possible by technological advances in neuroscience-has been proffered by defendants to support claims that brain abnormalities reduce their culpability. This exploratory study assessed the impact of neuroscience evidence on mock jurors' sentencing recommendations and impressions of a capital defendant. Using actual case facts, we manipulated diagnostic evidence presented by the defense (psychosis diagnosis; diagnosis and neuropsychological test results; or diagnosis, test results, and neuroimages) and future dangerousness evidence presented by the prosecution (low or high risk). Recommendations for death sentences were affected by the neuropsychological and neuroimaging evidence: defendants deemed at high risk for future dangerousness were less likely to be sentenced to death when jurors had this evidence than when they did not. Neuropsychological and neuroimaging evidence also had mitigating effects on impressions of the defendant. We describe study limitations and pose questions for further research. PMID:22213023

  13. Abnormal Neuroimaging in a Case of Infant Botulism.

    PubMed

    Good, Ryan J; Messacar, Kevin; Stence, Nicholas V; Press, Craig A; Carpenter, Todd C

    2015-01-01

    We present the first case of abnormal neuroimaging in a case of infant botulism. The clinical findings of the patient with constipation, bulbar weakness, and descending, symmetric motor weakness are consistent with the classic findings of infant botulism. Magnetic resonance imaging (MRI), however, revealed restricted diffusion in the brain and enhancement of the cervical nerve roots. Traditionally, normal neuroimaging was used to help differentiate infant botulism from other causes of weakness in infants. Abnormal neuroimaging is seen in other causes of weakness in an infant including metabolic disorders and hypoxic-ischemic injury, but these diagnoses did not fit the clinical findings in this case. The explanation for the MRI abnormalities in the brain and cervical nerve roots is unclear as botulinum toxin acts at presynaptic nerve terminals and does not cross the blood-brain barrier. Possible explanations for the findings include inflammation from the botulinum toxin at the synapse, alterations in sensory signaling and retrograde transport of the botulinum toxin. The patient was treated with human botulism immune globulin and had rapid recovery in weakness. A stool sample from the patient was positive for Type A Clostridium botulinum toxin eventually confirming the diagnosis of infant botulism. The findings in this case support use of human botulism immune globulin when the clinical findings are consistent with infant botulism despite the presence of MRI abnormalities in the brain and cervical nerve roots. PMID:26697417

  14. Abnormal Neuroimaging in a Case of Infant Botulism

    PubMed Central

    Good, Ryan J.; Messacar, Kevin; Stence, Nicholas V.; Press, Craig A.; Carpenter, Todd C.

    2015-01-01

    We present the first case of abnormal neuroimaging in a case of infant botulism. The clinical findings of the patient with constipation, bulbar weakness, and descending, symmetric motor weakness are consistent with the classic findings of infant botulism. Magnetic resonance imaging (MRI), however, revealed restricted diffusion in the brain and enhancement of the cervical nerve roots. Traditionally, normal neuroimaging was used to help differentiate infant botulism from other causes of weakness in infants. Abnormal neuroimaging is seen in other causes of weakness in an infant including metabolic disorders and hypoxic–ischemic injury, but these diagnoses did not fit the clinical findings in this case. The explanation for the MRI abnormalities in the brain and cervical nerve roots is unclear as botulinum toxin acts at presynaptic nerve terminals and does not cross the blood–brain barrier. Possible explanations for the findings include inflammation from the botulinum toxin at the synapse, alterations in sensory signaling and retrograde transport of the botulinum toxin. The patient was treated with human botulism immune globulin and had rapid recovery in weakness. A stool sample from the patient was positive for Type A Clostridium botulinum toxin eventually confirming the diagnosis of infant botulism. The findings in this case support use of human botulism immune globulin when the clinical findings are consistent with infant botulism despite the presence of MRI abnormalities in the brain and cervical nerve roots. PMID:26697417

  15. Adding flavor to AdS4/CFT3

    NASA Astrophysics Data System (ADS)

    Ammon, Martin; Erdmenger, Johanna; Meyer, René; O'Bannon, Andy; Wrase, Timm

    2009-11-01

    Aharony, Bergman, Jafferis, and Maldacena have proposed that the low-energy description of multiple M2-branes at a Bbb C4/Bbb Zk singularity is a (2+1)-dimensional Script N = 6 supersymmetric U(Nc) × U(Nc) Chern-Simons matter theory, the ABJM theory. In the large-Nc limit, its holographic dual is supergravity in AdS4 × S7/Bbb Zk. We study various ways to add fields that transform in the fundamental representation of the gauge groups, i.e. flavor fields, to the ABJM theory. We work in a probe limit and perform analyses in both the supergravity and field theory descriptions. In the supergravity description we find a large class of supersymmetric embeddings of probe flavor branes. In the field theory description, we present a general method to determine the couplings of the flavor fields to the fields of the ABJM theory. We then study four examples in detail: codimension-zero Script N = 3 supersymmetric flavor, described in supergravity by Kaluza-Klein monopoles or D6-branes; codimension-one Script N = (0,6) supersymmetric chiral flavor, described by D8-branes; codimension-one Script N = (3,3) supersymmetric non-chiral flavor, described by M5/D4-branes; codimension-two Script N = 4 supersymmetric flavor, described by M2/D2-branes. Finally we discuss special physical equivalences between brane embeddings in M-theory, and their interpretation in the field theory description.

  16. Genetic Studies of Quantitative MCI and AD Phenotypes in ADNI: Progress, Opportunities, and Plans

    PubMed Central

    Saykin, Andrew J.; Shen, Li; Yao, Xiaohui; Kim, Sungeun; Nho, Kwangsik; Risacher, Shannon L.; Ramanan, Vijay K.; Foroud, Tatiana M.; Faber, Kelly M.; Sarwar, Nadeem; Munsie, Leanne M.; Hu, Xiaolan; Soares, Holly D.; Potkin, Steven G.; Thompson, Paul M.; Kauwe, John S.K.; Kaddurah-Daouk, Rima; Green, Robert C.; Toga, Arthur W.; Weiner, Michael W.

    2015-01-01

    INTRODUCTION Genetic data from the Alzheimer’s Disease Neuroimaging Initiative (ADNI) has been crucial in advancing the understanding of AD pathophysiology. Here we provide an update on sample collection, scientific progress and opportunities, conceptual issues, and future plans. METHODS Lymphoblastoid cell lines and DNA and RNA samples from blood have been collected and banked, and data and biosamples have been widely disseminated. To date, APOE genotyping, genome-wide association study (GWAS), and whole exome and whole genome sequencing (WES, WGS) data have been obtained and disseminated. RESULTS ADNI genetic data have been downloaded thousands of times and over 300 publications have resulted, including reports of large scale GWAS by consortia to which ADNI contributed. Many of the first applications of quantitative endophenotype association studies employed ADNI data, including some of the earliest GWAS and pathway-based studies of biospecimen and imaging biomarkers, as well as memory and other clinical/cognitive variables. Other contributions include some of the first WES and WGS data sets and reports in healthy controls, MCI, and AD. DISCUSSION Numerous genetic susceptibility and protective markers for AD and disease biomarkers have been identified and replicated using ADNI data, and have heavily implicated immune, mitochondrial, cell cycle/fate, and other biological processes. Early sequencing studies suggest that rare and structural variants are likely to account for significant additional phenotypic variation. Longitudinal analyses of transcriptomic, proteomic, metabolomic, and epigenomic changes will also further elucidate dynamic processes underlying preclinical and prodromal stages of disease. Integration of this unique collection of multi-omics data within a systems biology framework will help to separate truly informative markers of early disease mechanisms and potential novel therapeutic targets from the vast background of less relevant biological

  17. Spatially augmented LPboosting for AD classification with evaluations on the ADNI dataset.

    PubMed

    Hinrichs, Chris; Singh, Vikas; Mukherjee, Lopamudra; Xu, Guofan; Chung, Moo K; Johnson, Sterling C

    2009-10-15

    Structural and functional brain images are playing an important role in helping us understand the changes associated with neurological disorders such as Alzheimer's disease (AD). Recent efforts have now started investigating their utility for diagnosis purposes. This line of research has shown promising results where methods from machine learning (such as Support Vector Machines) have been used to identify AD-related patterns from images, for use in diagnosing new individual subjects. In this paper, we propose a new framework for AD classification which makes use of the Linear Program (LP) boosting with novel additional regularization based on spatial "smoothness" in 3D image coordinate spaces. The algorithm formalizes the expectation that since the examples for training the classifier are images, the voxels eventually selected for specifying the decision boundary must constitute spatially contiguous chunks, i.e., "regions" must be preferred over isolated voxels. This prior belief turns out to be useful for significantly reducing the space of possible classifiers and leads to substantial benefits in generalization. In our method, the requirement of spatial contiguity (of selected discriminating voxels) is incorporated within the optimization framework directly. Other methods have made use of similar biases as a pre- or post-processing step, however, our model incorporates this emphasis on spatial smoothness directly into the learning step. We report on extensive evaluations of our algorithm on MR and FDG-PET images from the Alzheimer's Disease Neuroimaging Initiative (ADNI) dataset, and discuss the relationship of the classification output with the clinical and cognitive biomarker data available within ADNI.

  18. Neuroimaging and traumatic brain injury: State of the field and voids in translational knowledge.

    PubMed

    Bruce, Erica D; Konda, Sneha; Dean, Dana D; Wang, Ernest W; Huang, Jason H; Little, Deborah M

    2015-05-01

    Traumatic brain injury (TBI) is a leading cause of death and disability in every developed country in the world and is believed to be a risk factor in the later development of depression, anxiety disorders and neurodegenerative diseases including chronic traumatic encephalopathy (CTE), Alzheimer's Disease (AD), Parkinson's Disease (PD), and amyotrophic lateral sclerosis (ALS). One challenge faced by those who conduct research into TBI is the lack of a verified and validated biomarker that can be used to diagnose TBI or for use as a prognostic variable which can identify those at risk for poor recovery following injury or at risk for neurodegeneration later in life. Neuroimaging continues to hold promise as a TBI biomarker but is limited by a lack of clear relationship between the neuropathology of injury/recovery and the quantitative and image based data that is obtained. Specifically lacking is the data on biochemical and biologic changes that lead to alterations in neuroimaging markers. There are multiple routes towards developing the knowledge required to more definitively link pathology to imaging but the most efficient approach is expanded leveraging of in vivo human blood, serum, and imaging biomarkers with both in vivo and ex vivo animal findings. This review describes the current use and limitations of imaging in TBI including a discussion of currently used animal injury models and the available animal imaging data and extracted markers that hold the greatest promise for helping translate alterations in imaging back to injury pathology. Further, it reviews both the human and animal TBI literature supporting current standards, identifies the remaining voids in the literature, and briefly highlights recent advances in molecular imaging. This article is part of a Special Issue entitled 'Traumatic Brain Injury'. PMID:25827094

  19. Twistor methods for AdS5

    NASA Astrophysics Data System (ADS)

    Adamo, Tim; Skinner, David; Williams, Jack

    2016-08-01

    We consider the application of twistor theory to five-dimensional anti-de Sitter space. The twistor space of AdS5 is the same as the ambitwistor space of the four-dimensional conformal boundary; the geometry of this correspondence is reviewed for both the bulk and boundary. A Penrose transform allows us to describe free bulk fields, with or without mass, in terms of data on twistor space. Explicit representatives for the bulk-to-boundary propagators of scalars and spinors are constructed, along with twistor action functionals for the free theories. Evaluating these twistor actions on bulk-to-boundary propagators is shown to produce the correct two-point functions.

  20. AdS3: the NHEK generation

    NASA Astrophysics Data System (ADS)

    Bena, Iosif; Heurtier, Lucien; Puhm, Andrea

    2016-05-01

    It was argued in [1] that the five-dimensional near-horizon extremal Kerr (NHEK) geometry can be embedded in String Theory as the infrared region of an infinite family of non-supersymmetric geometries that have D1, D5, momentum and KK monopole charges. We show that there exists a method to embed these geometries into asymptotically- {AdS}_3× {S}^3/{{Z}}_N solutions, and hence to obtain infinite families of flows whose infrared is NHEK. This indicates that the CFT dual to the NHEK geometry is the IR fixed point of a Renormalization Group flow from a known local UV CFT and opens the door to its explicit construction.

  1. Dysfunction of the prefrontal cortex in addiction: neuroimaging findings and clinical implications

    PubMed Central

    Goldstein, Rita Z.; Volkow, Nora D.

    2012-01-01

    The loss of control over drug intake that occurs in addiction was initially believed to result from disruption of subcortical reward circuits. However, imaging studies in addictive behaviours have identified a key involvement of the prefrontal cortex (PFC) both through its regulation of limbic reward regions and its involvement in higher-order executive function (for example, self-control, salience attribution and awareness). This Review focuses on functional neuroimaging studies conducted in the past decade that have expanded our understanding of the involvement of the PFC in drug addiction. Disruption of the PFC in addiction underlies not only compulsive drug taking but also accounts for the disadvantageous behaviours that are associated with addiction and the erosion of free will. PMID:22011681

  2. Effects of Marijuana Use on Brain Structure and Function: Neuroimaging Findings from a Neurodevelopmental Perspective.

    PubMed

    Brumback, T; Castro, N; Jacobus, J; Tapert, S

    2016-01-01

    Marijuana, behind only tobacco and alcohol, is the most popular recreational drug in America with prevalence rates of use rising over the past decade. A wide range of research has highlighted neurocognitive deficits associated with marijuana use, particularly when initiated during childhood or adolescence. Neuroimaging, describing alterations to brain structure and function, has begun to provide a picture of possible mechanisms associated with the deleterious effects of marijuana use. This chapter provides a neurodevelopmental framework from which recent data on brain structural and functional abnormalities associated with marijuana use is reviewed. Based on the current data, we provide aims for future studies to more clearly delineate the effects of marijuana on the developing brain and to define underlying mechanisms of the potential long-term negative consequences of marijuana use. PMID:27503447

  3. Shadows, currents, and AdS fields

    SciTech Connect

    Metsaev, R. R.

    2008-11-15

    Conformal totally symmetric arbitrary spin currents and shadow fields in flat space-time of dimension greater than or equal to four are studied. A gauge invariant formulation for such currents and shadow fields is developed. Gauge symmetries are realized by involving the Stueckelberg fields. A realization of global conformal boost symmetries is obtained. Gauge invariant differential constraints for currents and shadow fields are obtained. AdS/CFT correspondence for currents and shadow fields and the respective normalizable and non-normalizable solutions of massless totally symmetric arbitrary spin AdS fields are studied. The bulk fields are considered in a modified de Donder gauge that leads to decoupled equations of motion. We demonstrate that leftover on shell gauge symmetries of bulk fields correspond to gauge symmetries of boundary currents and shadow fields, while the modified de Donder gauge conditions for bulk fields correspond to differential constraints for boundary conformal currents and shadow fields. Breaking conformal symmetries, we find interrelations between the gauge invariant formulation of the currents and shadow fields, and the gauge invariant formulation of massive fields.

  4. Effect of CLU genetic variants on cerebrospinal fluid and neuroimaging markers in healthy, mild cognitive impairment and Alzheimer’s disease cohorts

    PubMed Central

    Tan, Lin; Wang, Hui-Fu; Tan, Meng-Shan; Tan, Chen-Chen; Zhu, Xi-Chen; Miao, Dan; Yu, Wan-Jiang; Jiang, Teng; Tan, Lan; Yu, Jin-Tai; Weiner, Michael W.; Aisen, Paul; Petersen, Ronald; Jack, Clifford R.; Jagust, William; Trojanowki, John Q.; Toga, Arthur W.; Beckett, Laurel; Green, Robert C.; Saykin, Andrew J.; Morris, John; Shaw, Leslie M.; Kaye, Jeffrey; Quinn, Joseph; Silbert, Lisa; Lind, Betty; Carter, Raina; Dolen, Sara; Schneider, Lon S.; Pawluczyk, Sonia; Beccera, Mauricio; Teodoro, Liberty; Spann, Bryan M.; Brewer, James; Vanderswag, Helen; Fleisher, Adam; Heidebrink, Judith L.; Lord, Joanne L.; Mason, Sara S.; Albers, Colleen S.; Knopman, David; Johnson, Kris; Doody, Rachelle S.; Villanueva-Meyer, Javier; Chowdhury, Munir; Rountree, Susan; Dang, Mimi; Stern, Yaakov; Honig, Lawrence S.; Bell, Karen L.; Ances, Beau; Morris, John C.; Carroll, Maria; Creech, Mary L.; Franklin, Erin; Mintun, Mark A.; Schneider, Stacy; Oliver, Angela; Marson, Daniel; Griffith, Randall; Clark, David; Geldmacher, David; Brockington, John; Roberson, Erik; Love, Marissa Natelson; Grossman, Hillel; Mitsis, Effie; Shah, Raj C.; deToledo-Morrell, Leyla; Duara, Ranjan; Varon, Daniel; Greig, Maria T.; Roberts, Peggy; Albert, Marilyn; Onyike, Chiadi; D’Agostino, Daniel; Kielb, Stephanie; Galvin, James E.; Cerbone, Brittany; Michel, Christina A.; Pogorelec, Dana M.; Rusinek, Henry; de Leon, Mony J.; Glodzik, Lidia; De Santi, Susan; Doraiswamy, P. Murali; Petrella, Jeffrey R.; Borges-Neto, Salvador; Wong, Terence Z.; Coleman, Edward; Smith, Charles D.; Jicha, Greg; Hardy, Peter; Sinha, Partha; Oates, Elizabeth; Conrad, Gary; Porsteinsson, Anton P.; Goldstein, Bonnie S.; Martin, Kim; Makino, Kelly M.; Ismail, M. Saleem; Brand, Connie; Mulnard, Ruth A.; Thai, Gaby; Mc-Adams-Ortiz, Catherine; Womack, Kyle; Mathews, Dana; Quiceno, Mary; Levey, Allan I.; Lah, James J.; Cellar, Janet S.; Burns, Jeffrey M.; Swerdlow, Russell H.; Brooks, William M.; Apostolova, Liana; Tingus, Kathleen; Woo, Ellen; Silverman, Daniel H. S.; Lu, Po H.; Bartzokis, George; Graff-Radford, Neill R.; Parfitt, Francine; Kendall, Tracy; Johnson, Heather; Farlow, Martin R.; Hake, Ann Marie; Matthews, Brandy R.; Brosch, Jared R.; Herring, Scott; Hunt, Cynthia; van Dyck, Christopher H.; Carson, Richard E.; MacAvoy, Martha G.; Varma, Pradeep; Chertkow, Howard; Bergman, Howard; Hosein, Chris; Black, Sandra; Stefanovic, Bojana; Caldwell, Curtis; Hsiung, Ging-Yuek Robin; Feldman, Howard; Mudge, Benita; Assaly, Michele; Finger, Elizabeth; Pasternack, Stephen; Rachisky, Irina; Trost, Dick; Kertesz, Andrew; Bernick, Charles; Munic, Donna; Mesulam, Marek-Marsel; Lipowski, Kristine; Weintraub, Sandra; Bonakdarpour, Borna; Kerwin, Diana; Wu, Chuang-Kuo; Johnson, Nancy; Sadowsky, Carl; Villena, Teresa; Turner, Raymond Scott; Johnson, Kathleen; Reynolds, Brigid; Sperling, Reisa A.; Johnson, Keith A.; Marshall, Gad; Yesavage, Jerome; Taylor, Joy L.; Lane, Barton; Rosen, Allyson; Tinklenberg, Jared; Sabbagh, Marwan N.; Belden, Christine M.; Jacobson, Sandra A.; Sirrel, Sherye A.; Kowall, Neil; Killiany, Ronald; Budson, Andrew E.; Norbash, Alexander; Johnson, Patricia Lynn; Obisesan, Thomas O.; Wolday, Saba; Allard, Joanne; Lerner, Alan; Ogrocki, Paula; Tatsuoka, Curtis; Fatica, Parianne; Fletcher, Evan; Maillard, Pauline; Olichney, John; DeCarli, Charles; Carmichael, Owen; Kittur, Smita; Borrie, Michael; Lee, T -Y; Bartha, Rob; Johnson, Sterling; Asthana, Sanjay; Carlsson, Cynthia M.; Potkin, Steven G.; Preda, Adrian; Nguyen, Dana; Tariot, Pierre; Burke, Anna; Trncic, Nadira; Fleisher, Adam; Reeder, Stephanie; Bates, Vernice; Capote, Horacio; Rainka, Michelle; Scharre, Douglas W.; Kataki, Maria; Adeli, Anahita; Zimmerman, Earl A.; Celmins, Dzintra; Brown, Alice D.; Pearlson, Godfrey D.; Blank, Karen; Anderson, Karen; Flashman, Laura A.; Seltzer, Marc; Hynes, Mary L.; Santulli, Robert B.; Sink, Kaycee M.; Gordineer, Leslie; Williamson, Jeff D.; Garg, Pradeep; Watkins, Franklin; Ott, Brian R.; Querfurth, Henry; Tremont, Geoffrey; Salloway, Stephen; Malloy, Paul; Correia, Stephen; Rosen, Howard J.; Miller, Bruce L.; Perry, David; Mintzer, Jacobo; Spicer, Kenneth; Bachman, David; Pomara, Nunzio; Hernando, Raymundo; Sarrael, Antero; Relkin, Norman; Chaing, Gloria; Lin, Michael; Ravdin, Lisa; Smith, Amanda; Raj, Balebail Ashok; Fargher, Kristin

    2016-01-01

    The Clusterin (CLU) gene, also known as apolipoprotein J (ApoJ), is currently the third most associated late-onset Alzheimer’s disease (LOAD) risk gene. However, little was known about the possible effect of CLU genetic variants on AD pathology in brain. Here, we evaluated the interaction between 7 CLU SNPs (covering 95% of genetic variations) and the role of CLU in β-amyloid (Aβ) deposition, AD-related structure atrophy, abnormal glucose metabolism on neuroimaging and CSF markers to clarify the possible approach by that CLU impacts AD. Finally, four loci (rs11136000, rs1532278, rs2279590, rs7982) showed significant associations with the Aβ deposition at the baseline level while genotypes of rs9331888 (P = 0.042) increased Aβ deposition. Besides, rs9331888 was significantly associated with baseline volume of left hippocampus (P = 0.014). We then further validated the association with Aβ deposition in the AD, mild cognitive impairment (MCI), normal control (NC) sub-groups. The results in sub-groups confirmed the association between CLU genotypes and Aβ deposition further. Our findings revealed that CLU genotypes could probably modulate the cerebral the Aβ loads on imaging and volume of hippocampus. These findings raise the possibility that the biological effects of CLU may be relatively confined to neuroimaging trait and hence may offer clues to AD. PMID:27229352

  5. Neuroimaging correlates of neuropsychiatric symptoms in Alzheimer's disease: a review of 20 years of research.

    PubMed

    Boublay, N; Schott, A M; Krolak-Salmon, P

    2016-10-01

    Assessing morphological, perfusion and metabolic brain changes preceding or associated with neuropsychiatric symptoms (NPSs) will help in the understanding of pathophysiological underlying processes in Alzheimer's disease (AD). This review aimed to highlight the main findings on significant associations between neuroimaging and NPSs, the pathophysiology to elucidate possible underlying mechanisms, and methodological issues to aid future research. Research papers published from January 1990 to October 2015 were identified in the databases PsycInfo, Embase, PubMed and Medline, using key words related to NPSs and imaging techniques. In addition to a semi-systematic search in the databases, we also performed hand searches based on reported citations identified to be of interest. Delusions, apathy and depression symptoms were particularly associated with brain changes in AD. The majority of studies disclosed an association between frontal lobe structural and/or metabolic changes and NPSs, implicating, interestingly, for all 12 NPSs studied, the anterior cingulate cortex although temporal, subcortical and parietal regions, and insula were also involved. Given the high degree of connectivity of these brain areas, frontal change correlates of NPSs may help in the understanding of neural network participation. This review also highlights crucial methodological issues that may reduce the heterogeneity of results to enable progress on the pathophysiological mechanisms and aid research on NPS treatments in AD. Based on a broad review of the current literature, a global brain pattern to support the huge heterogeneity of neuroimaging correlates of NPSs in AD and methodological strategies are suggested to help direct future research. PMID:27435186

  6. The Yield of Neuroimaging in Children Presenting to the Emergency Department With Acute Ataxia in the Post-Varicella Vaccine Era.

    PubMed

    Rudloe, Tiffany; Prabhu, Sanjay P; Gorman, Mark P; Nigrovic, Lise E; Harper, Marvin B; Landschaft, Assaf; Kimia, Amir A

    2015-09-01

    To determine the yield of neuroimaging in children presenting to the emergency department with acute ataxia in the post-varicella vaccine era, we conducted a cross-sectional study between 1995 and 2013 at a single pediatric tertiary care center. We included children aged 1-18 years evaluated for acute ataxia of <7 days' duration. The main outcome was clinically urgent intracranial pathology defined as a radiologic finding that changed initial management. We identified 364 children, among whom neuroimaging was obtained in 284 (78%). Forty-two children had clinically urgent intracranial pathology (13%, 95% confidence interval 9%-17%); tumors and acute disseminated encephalomyelitis were the leading findings. Age ≤3 years and symptoms ≤3 days of duration were predictors of low risk (0.7%, 95% confidence interval 0%-4.4%). In conclusion, neuroimaging may be indicated for most patients presenting with acute ataxia. Neuroimaging may be deferred in younger children with short duration of symptoms contingent on close follow-up.

  7. The impact of PICALM genetic variations on reserve capacity of posterior cingulate in AD continuum.

    PubMed

    Xu, Wei; Wang, Hui-Fu; Tan, Lin; Tan, Meng-Shan; Tan, Chen-Chen; Zhu, Xi-Chen; Miao, Dan; Yu, Wan-Jiang; Jiang, Teng; Tan, Lan; Yu, Jin-Tai

    2016-01-01

    Phosphatidylinositolbinding clathrin assembly protein (PICALM) gene is one novel genetic player associated with late-onset Alzheimer's disease (LOAD), based on recent genome wide association studies (GWAS). However, how it affects AD occurrence is still unknown. Brain reserve hypothesis highlights the tolerant capacities of brain as a passive means to fight against neurodegenerations. Here, we took the baseline volume and/or thickness of LOAD-associated brain regions as proxies of brain reserve capacities and investigated whether PICALM genetic variations can influence the baseline reserve capacities and the longitudinal atrophy rate of these specific regions using data from Alzheimer's Disease Neuroimaging Initiative (ADNI) dataset. In mixed population, we found that brain region significantly affected by PICALM genetic variations was majorly restricted to posterior cingulate. In sub-population analysis, we found that one PICALM variation (C allele of rs642949) was associated with larger baseline thickness of posterior cingulate in health. We found seven variations in health and two variations (rs543293 and rs592297) in individuals with mild cognitive impairment were associated with slower atrophy rate of posterior cingulate. Our study provided preliminary evidences supporting that PICALM variations render protections by facilitating reserve capacities of posterior cingulate in non-demented elderly. PMID:27117083

  8. The impact of PICALM genetic variations on reserve capacity of posterior cingulate in AD continuum

    PubMed Central

    Xu, Wei; Wang, Hui-Fu; Tan, Lin; Tan, Meng-Shan; Tan, Chen-Chen; Zhu, Xi-Chen; Miao, Dan; Yu, Wan-Jiang; Jiang, Teng; Tan, Lan; Yu, Jin-Tai; Weiner, Michael W.; Aisen, Paul; Petersen, Ronald; Jack, Clifford R.; Jagust, William; Trojanowki, John Q.; Toga, Arthur W.; Beckett, Laurel; Green, Robert C.; Saykin, Andrew J.; Morris, John; Shaw, Leslie M.; Kaye, Jeffrey; Quinn, Joseph; Silbert, Lisa; Lind, Betty; Carter, Raina; Dolen, Sara; Schneider, Lon S.; Pawluczyk, Sonia; Beccera, Mauricio; Teodoro, Liberty; Spann, Bryan M.; Brewer, James; Vanderswag, Helen; Fleisher, Adam; Heidebrink, Judith L.; Lord, Joanne L.; Mason, Sara S.; Albers, Colleen S.; Knopman, David; Johnson, Kris; Doody, Rachelle S.; Villanueva-Meyer, Javier; Chowdhury, Munir; Rountree, Susan; Dang, Mimi; Stern, Yaakov; Honig, Lawrence S.; Bell, Karen L.; Ances, Beau; Morris, John C.; Carroll, Maria; Creech, Mary L.; Franklin, Erin; Mintun, Mark A.; Schneider, Stacy; Oliver, Angela; Marson, Daniel; Griffith, Randall; Clark, David; Geldmacher, David; Brockington, John; Roberson, Erik; Natelson Love, Marissa; Grossman, Hillel; Mitsis, Effie; Shah, Raj C.; deToledo-Morrell, Leyla; Duara, Ranjan; Varon, Daniel; Greig, Maria T.; Roberts, Peggy; Albert, Marilyn; Onyike, Chiadi; D’Agostino, Daniel; Kielb, Stephanie; Galvin, James E.; Cerbone, Brittany; Michel, Christina A.; Pogorelec, Dana M.; Rusinek, Henry; de Leon, Mony J.; Glodzik, Lidia; De Santi, Susan; Doraiswamy, P. Murali; Petrella, Jeffrey R.; Borges-Neto, Salvador; Wong, Terence Z.; Coleman, Edward; Smith, Charles D.; Jicha, Greg; Hardy, Peter; Sinha, Partha; Oates, Elizabeth; Conrad, Gary; Porsteinsson, Anton P.; Goldstein, Bonnie S.; Martin, Kim; Makino, Kelly M.; Ismail, M. Saleem; Brand, Connie; Mulnard, Ruth A.; Thai, Gaby; Mc-Adams-Ortiz, Catherine; Womack, Kyle; Mathews, Dana; Quiceno, Mary; Levey, Allan I.; Lah, James J.; Cellar, Janet S.; Burns, Jeffrey M.; Swerdlow, Russell H.; Brooks, William M.; Apostolova, Liana; Tingus, Kathleen; Woo, Ellen; Silverman, Daniel H.S.; Lu, Po H.; Bartzokis, George; Graff-Radford, Neill R.; Parfitt, Francine; Kendall, Tracy; Johnson, Heather; Farlow, Martin R.; Hake, Ann Marie; Matthews, Brandy R.; Brosch, Jared R.; Herring, Scott; Hunt, Cynthia; van Dyck, Christopher H.; Carson, Richard E.; MacAvoy, Martha G.; Varma, Pradeep; Chertkow, Howard; Bergman, Howard; Hosein, Chris; Black, Sandra; Stefanovic, Bojana; Caldwell, Curtis; Robin Hsiung, Ging-Yuek; Feldman, Howard; Mudge, Benita; Assaly, Michele; Finger, Elizabeth; Pasternack, Stephen; Rachisky, Irina; Trost, Dick; Kertesz, Andrew; Bernick, Charles; Munic, Donna; Mesulam, Marek-Marsel; Lipowski, Kristine; Weintraub, Sandra; Bonakdarpour, Borna; Kerwin, Diana; Wu, Chuang-Kuo; Johnson, Nancy; Sadowsky, Carl; Villena, Teresa; Scott Turner, Raymond; Johnson, Kathleen; Reynolds, Brigid; Sperling, Reisa A.; Johnson, Keith A.; Marshall, Gad; Yesavage, Jerome; Taylor, Joy L.; Lane, Barton; Rosen, Allyson; Tinklenberg, Jared; Sabbagh, Marwan N.; Belden, Christine M.; Jacobson, Sandra A.; Sirrel, Sherye A.; Kowall, Neil; Killiany, Ronald; Budson, Andrew E.; Norbash, Alexander; Lynn Johnson, Patricia; Obisesan, Thomas O.; Wolday, Saba; Allard, Joanne; Lerner, Alan; Ogrocki, Paula; Tatsuoka, Curtis; Fatica, Parianne; Fletcher, Evan; Maillard, Pauline; Olichney, John; DeCarli, Charles; Carmichael, Owen; Kittur, Smita; Borrie, Michael; Lee, T-Y; Bartha, Rob; Johnson, Sterling; Asthana, Sanjay; Carlsson, Cynthia M.; Potkin, Steven G.; Preda, Adrian; Nguyen, Dana; Tariot, Pierre; Burke, Anna; Trncic, Nadira; Fleisher, Adam; Reeder, Stephanie; Bates, Vernice; Capote, Horacio; Rainka, Michelle; Scharre, Douglas W; Kataki, Maria; Adeli, Anahita; Zimmerman, Earl A.; Celmins, Dzintra; Brown, Alice D.; Pearlson, Godfrey D.; Blank, Karen; Anderson, Karen; Flashman, Laura A.; Seltzer, Marc; Hynes, Mary L.; Santulli, Robert B.; Sink, Kaycee M.; Gordineer, Leslie; Williamson, Jeff D.; Garg, Pradeep; Watkins, Franklin; Ott, Brian R.; Querfurth, Henry; Tremont, Geoffrey; Salloway, Stephen; Malloy, Paul; Correia, Stephen; Rosen, Howard J.; Miller, Bruce L.; Perry, David; Mintzer, Jacobo; Spicer, Kenneth; Bachman, David; Pomara, Nunzio; Hernando, Raymundo; Sarrael, Antero; Relkin, Norman; Chaing, Gloria; Lin, Michael; Ravdin, Lisa; Smith, Amanda; Ashok Raj, Balebail; Fargher, Kristin

    2016-01-01

    Phosphatidylinositolbinding clathrin assembly protein (PICALM) gene is one novel genetic player associated with late-onset Alzheimer’s disease (LOAD), based on recent genome wide association studies (GWAS). However, how it affects AD occurrence is still unknown. Brain reserve hypothesis highlights the tolerant capacities of brain as a passive means to fight against neurodegenerations. Here, we took the baseline volume and/or thickness of LOAD-associated brain regions as proxies of brain reserve capacities and investigated whether PICALM genetic variations can influence the baseline reserve capacities and the longitudinal atrophy rate of these specific regions using data from Alzheimer’s Disease Neuroimaging Initiative (ADNI) dataset. In mixed population, we found that brain region significantly affected by PICALM genetic variations was majorly restricted to posterior cingulate. In sub-population analysis, we found that one PICALM variation (C allele of rs642949) was associated with larger baseline thickness of posterior cingulate in health. We found seven variations in health and two variations (rs543293 and rs592297) in individuals with mild cognitive impairment were associated with slower atrophy rate of posterior cingulate. Our study provided preliminary evidences supporting that PICALM variations render protections by facilitating reserve capacities of posterior cingulate in non-demented elderly. PMID:27117083

  9. A stochasticity threshold in holography and the instability of AdS

    NASA Astrophysics Data System (ADS)

    Basu, Pallab; Krishnan, Chethan; Saurabh, Ayush

    2015-07-01

    We give strong numerical evidence that a self-interacting probe scalar field in AdS, with only a few modes turned on initially, will undergo fast thermalization only if it is above a certain energetic threshold. Below the threshold the energy stays close to constant in a few modes for a very long time instead of cascading quickly. This indicates the existence of a Strong Stochasticity Threshold (SST) in holography. The idea of SST is familiar from certain statistical mechanical systems, and we suggest that it exists also in AdS gravity. This would naturally reconcile the generic nonlinear instability of AdS observed by Bizon and Rostworowski, with the Fermi-Pasta-Ulam-Tsingou-like quasiperiodicity noticed recently for some classes of initial conditions. We show that our simple setup captures many of the relevant features of the full gravity-scalar system.

  10. Can structural neuroimaging be used to define phenotypes and course of schizophrenia?

    PubMed

    Kerns, John G; Lauriello, John

    2012-09-01

    This article examines whether structural neuroimaging measures have been found to predict outcome in schizophrenia and whether changes in neuroimaging measures have been found to correlate with poor outcome in the disorder. Overall, there is little compelling evidence that structural neuroimaging measures in either first-episode or chronic patients predict future outcome. Progressive brain changes might reflect a neuroimaging phenotype associated with a worse course of the disorder. At the same time, there are many fruitful avenues that future research could take in an attempt to better predict future outcome or to identify specific imaging phenotypes associated with outcome. PMID:22929870

  11. NPAS3 variants in schizophrenia: a neuroimaging study

    PubMed Central

    2014-01-01

    Background This research is a one-site neuroimaging component of a two-site genetic study involving patients with schizophrenia at early and later stages of illness. Studies support a role for the neuronal Per-Arnt-Sim 3 (NPAS3) gene in processes that are essential for normal brain development. Specific NPAS3 variants have been observed at an increased frequency in schizophrenia. In humans, NPAS3 protein was detected in the hippocampus from the first trimester of gestation. In addition, NPAS3 protein levels were reduced in the dorsolateral prefrontal cortex of some patients with schizophrenia. Npas3 knockout mice display behavioural, neuroanatomical and structural changes with associated severe reductions in neural precursor cell proliferation in the hippocampal dentate gyrus. This study will evaluate the hypothesis that the severe reductions in neural precursor cell proliferation in the dentate gyrus will be present to some degree in patients carrying schizophrenia-associated NPAS3 variants and less so in other patients. Methods/Design Patients enrolled in the larger genetic study (n = 150) will be invited to participate in this neuroimaging arm. The genetic data will be used to ensure a sample size of 45 participants in each genetic subgroup of patients (with and without NPAS3 variants). In addition, we will recruit 60 healthy controls for acquisition of normative data. The following neuroimaging measures will be acquired from the medial temporal region: a) an index of the microcellular environment; b) a macro-structural volumetric measure of the hippocampus; and c) concentration levels of N-acetylaspartate, a marker of neuronal health. Discussion This study will help to establish the contribution of the NPAS3 gene and its variants to brain tissue abnormalities in schizophrenia. Given the genetic and phenotypic heterogeneity of the disorder and the large variation in outcomes, the identification of biological subgroups may in future support tailoring of treatment

  12. Multiple brain atlas database and atlas-based neuroimaging system.

    PubMed

    Nowinski, W L; Fang, A; Nguyen, B T; Raphel, J K; Jagannathan, L; Raghavan, R; Bryan, R N; Miller, G A

    1997-01-01

    For the purpose of developing multiple, complementary, fully labeled electronic brain atlases and an atlas-based neuroimaging system for analysis, quantification, and real-time manipulation of cerebral structures in two and three dimensions, we have digitized, enhanced, segmented, and labeled the following print brain atlases: Co-Planar Stereotaxic Atlas of the Human Brain by Talairach and Tournoux, Atlas for Stereotaxy of the Human Brain by Schaltenbrand and Wahren, Referentially Oriented Cerebral MRI Anatomy by Talairach and Tournoux, and Atlas of the Cerebral Sulci by Ono, Kubik, and Abernathey. Three-dimensional extensions of these atlases have been developed as well. All two- and three-dimensional atlases are mutually preregistered and may be interactively registered with an actual patient's data. An atlas-based neuroimaging system has been developed that provides support for reformatting, registration, visualization, navigation, image processing, and quantification of clinical data. The anatomical index contains about 1,000 structures and over 400 sulcal patterns. Several new applications of the brain atlas database also have been developed, supported by various technologies such as virtual reality, the Internet, and electronic publishing. Fusion of information from multiple atlases assists the user in comprehensively understanding brain structures and identifying and quantifying anatomical regions in clinical data. The multiple brain atlas database and atlas-based neuroimaging system have substantial potential impact in stereotactic neurosurgery and radiotherapy by assisting in visualization and real-time manipulation in three dimensions of anatomical structures, in quantitative neuroradiology by allowing interactive analysis of clinical data, in three-dimensional neuroeducation, and in brain function studies.

  13. Neuroimaging and Neurodevelopmental Outcome in Extremely Preterm Infants

    PubMed Central

    Barnes, Patrick D.; Bulas, Dorothy; Slovis, Thomas L.; Finer, Neil N.; Wrage, Lisa A.; Das, Abhik; Tyson, Jon E.; Stevenson, David K.; Carlo, Waldemar A.; Walsh, Michele C.; Laptook, Abbot R.; Yoder, Bradley A.; Van Meurs, Krisa P.; Faix, Roger G.; Rich, Wade; Newman, Nancy S.; Cheng, Helen; Heyne, Roy J.; Vohr, Betty R.; Acarregui, Michael J.; Vaucher, Yvonne E.; Pappas, Athina; Peralta-Carcelen, Myriam; Wilson-Costello, Deanne E.; Evans, Patricia W.; Goldstein, Ricki F.; Myers, Gary J.; Poindexter, Brenda B.; McGowan, Elisabeth C.; Adams-Chapman, Ira; Fuller, Janell; Higgins, Rosemary D.

    2015-01-01

    BACKGROUND: Extremely preterm infants are at risk for neurodevelopmental impairment (NDI). Early cranial ultrasound (CUS) is usual practice, but near-term brain MRI has been reported to better predict outcomes. We prospectively evaluated MRI white matter abnormality (WMA) and cerebellar lesions, and serial CUS adverse findings as predictors of outcomes at 18 to 22 months’ corrected age. METHODS: Early and late CUS, and brain MRI were read by masked central readers, in a large cohort (n = 480) of infants <28 weeks’ gestation surviving to near term in the Neonatal Research Network. Outcomes included NDI or death after neuroimaging, and significant gross motor impairment or death, with NDI defined as cognitive composite score <70, significant gross motor impairment, and severe hearing or visual impairment. Multivariable models evaluated the relative predictive value of neuroimaging while controlling for other factors. RESULTS: Of 480 infants, 15 died and 20 were lost. Increasing severity of WMA and significant cerebellar lesions on MRI were associated with adverse outcomes. Cerebellar lesions were rarely identified by CUS. In full multivariable models, both late CUS and MRI, but not early CUS, remained independently associated with NDI or death (MRI cerebellar lesions: odds ratio, 3.0 [95% confidence interval: 1.3–6.8]; late CUS: odds ratio, 9.8 [95% confidence interval: 2.8–35]), and significant gross motor impairment or death. In models that did not include late CUS, MRI moderate-severe WMA was independently associated with adverse outcomes. CONCLUSIONS: Both late CUS and near-term MRI abnormalities were associated with outcomes, independent of early CUS and other factors, underscoring the relative prognostic value of near-term neuroimaging. PMID:25554820

  14. High-throughput neuroimaging-genetics computational infrastructure

    PubMed Central

    Dinov, Ivo D.; Petrosyan, Petros; Liu, Zhizhong; Eggert, Paul; Hobel, Sam; Vespa, Paul; Woo Moon, Seok; Van Horn, John D.; Franco, Joseph; Toga, Arthur W.

    2014-01-01

    Many contemporary neuroscientific investigations face significant challenges in terms of data management, computational processing, data mining, and results interpretation. These four pillars define the core infrastructure necessary to plan, organize, orchestrate, validate, and disseminate novel scientific methods, computational resources, and translational healthcare findings. Data management includes protocols for data acquisition, archival, query, transfer, retrieval, and aggregation. Computational processing involves the necessary software, hardware, and networking infrastructure required to handle large amounts of heterogeneous neuroimaging, genetics, clinical, and phenotypic data and meta-data. Data mining refers to the process of automatically extracting data features, characteristics and associations, which are not readily visible by human exploration of the raw dataset. Result interpretation includes scientific visualization, community validation of findings and reproducible findings. In this manuscript we describe the novel high-throughput neuroimaging-genetics computational infrastructure available at the Institute for Neuroimaging and Informatics (INI) and the Laboratory of Neuro Imaging (LONI) at University of Southern California (USC). INI and LONI include ultra-high-field and standard-field MRI brain scanners along with an imaging-genetics database for storing the complete provenance of the raw and derived data and meta-data. In addition, the institute provides a large number of software tools for image and shape analysis, mathematical modeling, genomic sequence processing, and scientific visualization. A unique feature of this architecture is the Pipeline environment, which integrates the data management, processing, transfer, and visualization. Through its client-server architecture, the Pipeline environment provides a graphical user interface for designing, executing, monitoring validating, and disseminating of complex protocols that utilize

  15. ADS pilot program Plan

    NASA Technical Reports Server (NTRS)

    Clauson, J.; Heuser, J.

    1981-01-01

    The Applications Data Service (ADS) is a system based on an electronic data communications network which will permit scientists to share the data stored in data bases at universities and at government and private installations. It is designed to allow users to readily locate and access high quality, timely data from multiple sources. The ADS Pilot program objectives and the current plans for accomplishing those objectives are described.

  16. The emerging role of advanced neuroimaging techniques for brain metastases.

    PubMed

    Nowosielski, Martha; Radbruch, Alexander

    2015-06-01

    Brain metastases are an increasingly encountered and frightening manifestation of systemic cancer. More effective therapeutic strategies for the primary tumor are resulting in longer patient survival on the one hand while on the other, better brain tumor detection has resulted from increased availability and development of more precise brain imaging methods. This review focuses on the emerging role of functional neuroimaging techniques; magnetic resonance imaging (MRI) as well as positron emission tomography (PET), in establishing diagnosis, for monitoring treatment response with an emphasis on new targeted as well as immunomodulatory therapies and for predicting prognosis in patients with brain metastases.

  17. Neuroimaging of schizophrenia: structural abnormalities and pathophysiological implications

    PubMed Central

    Buckley, Peter F

    2005-01-01

    Schizophrenia, once considered a psychological malady devoid of any organic brain substrate, has been the focus of intense neuroimaging research. Findings reveal mild but generalized tissue loss as well as more selective focal loss. It is unclear whether these abnormalities reflect neurodevelopmental or neurodegenerative processes, or some combination of each; current evidence favors a preponderance of neurodevelopmental abnormalities. The pattern of brain abnormalities is also influenced by environmental and genetic risk factors, as well as by the course (and possibly even treatment) of this illness. These findings are described in this article. PMID:18568069

  18. Multimodal Neuroimaging-Informed Clinical Applications in Neuropsychiatric Disorders

    PubMed Central

    O’Halloran, Rafael; Kopell, Brian H.; Sprooten, Emma; Goodman, Wayne K.; Frangou, Sophia

    2016-01-01

    Recent advances in neuroimaging data acquisition and analysis hold the promise to enhance the ability to make diagnostic and prognostic predictions and perform treatment planning in neuropsychiatric disorders. Prior research using a variety of types of neuroimaging techniques has confirmed that neuropsychiatric disorders are associated with dysfunction in anatomical and functional brain circuits. We first discuss current challenges associated with the identification of reliable neuroimaging markers for diagnosis and prognosis in mood disorders and for neurosurgical treatment planning for deep brain stimulation (DBS). We then present data on the use of neuroimaging for the diagnosis and prognosis of mood disorders and for DBS treatment planning. We demonstrate how multivariate analyses of functional activation and connectivity parameters can be used to differentiate patients with bipolar disorder from those with major depressive disorder and non-affective psychosis. We also present data on connectivity parameters that mediate acute treatment response in affective and non-affective psychosis. We then focus on precision mapping of functional connectivity in native space. We describe the benefits of integrating anatomical fiber reconstruction with brain functional parameters and cortical surface measures to derive anatomically informed connectivity metrics within the morphological context of each individual brain. We discuss how this approach may be particularly promising in psychiatry, given the clinical and etiological heterogeneity of the disorders, and particularly in treatment response prediction and planning. Precision mapping of connectivity is essential for DBS. In DBS, treatment electrodes are inserted into positions near key gray matter nodes within the circuits considered relevant to disease expression. However, targeting white matter tracts that underpin connectivity within these circuits may increase treatment efficacy and tolerability therefore relevant

  19. Accelerating Neuroimage Registration through Parallel Computation of Similarity Metric

    PubMed Central

    Luo, Yun-gang; Liu, Ping; Shi, Lin; Luo, Yishan; Yi, Lei; Li, Ang; Qin, Jing; Heng, Pheng-Ann; Wang, Defeng

    2015-01-01

    Neuroimage registration is crucial for brain morphometric analysis and treatment efficacy evaluation. However, existing advanced registration algorithms such as FLIRT and ANTs are not efficient enough for clinical use. In this paper, a GPU implementation of FLIRT with the correlation ratio (CR) as the similarity metric and a GPU accelerated correlation coefficient (CC) calculation for the symmetric diffeomorphic registration of ANTs have been developed. The comparison with their corresponding original tools shows that our accelerated algorithms can greatly outperform the original algorithm in terms of computational efficiency. This paper demonstrates the great potential of applying these registration tools in clinical applications. PMID:26352412

  20. Multimodal Neuroimaging-Informed Clinical Applications in Neuropsychiatric Disorders.

    PubMed

    O'Halloran, Rafael; Kopell, Brian H; Sprooten, Emma; Goodman, Wayne K; Frangou, Sophia

    2016-01-01

    Recent advances in neuroimaging data acquisition and analysis hold the promise to enhance the ability to make diagnostic and prognostic predictions and perform treatment planning in neuropsychiatric disorders. Prior research using a variety of types of neuroimaging techniques has confirmed that neuropsychiatric disorders are associated with dysfunction in anatomical and functional brain circuits. We first discuss current challenges associated with the identification of reliable neuroimaging markers for diagnosis and prognosis in mood disorders and for neurosurgical treatment planning for deep brain stimulation (DBS). We then present data on the use of neuroimaging for the diagnosis and prognosis of mood disorders and for DBS treatment planning. We demonstrate how multivariate analyses of functional activation and connectivity parameters can be used to differentiate patients with bipolar disorder from those with major depressive disorder and non-affective psychosis. We also present data on connectivity parameters that mediate acute treatment response in affective and non-affective psychosis. We then focus on precision mapping of functional connectivity in native space. We describe the benefits of integrating anatomical fiber reconstruction with brain functional parameters and cortical surface measures to derive anatomically informed connectivity metrics within the morphological context of each individual brain. We discuss how this approach may be particularly promising in psychiatry, given the clinical and etiological heterogeneity of the disorders, and particularly in treatment response prediction and planning. Precision mapping of connectivity is essential for DBS. In DBS, treatment electrodes are inserted into positions near key gray matter nodes within the circuits considered relevant to disease expression. However, targeting white matter tracts that underpin connectivity within these circuits may increase treatment efficacy and tolerability therefore relevant

  1. Sex Differences in Grey Matter Atrophy Patterns Among AD and aMCI Patients: Results from ADNI

    PubMed Central

    Skup, Martha; Zhu, Hongtu; Wang, Yaping; Giovanello, Kelly S.; Lin, Ja-an; Shen, Dinggang; Shi, Feng; Gao, Wei; Lin, Weili; Fan, Yong; Zhang, Heping

    2011-01-01

    We used longitudinal magnetic resonance imaging (MRI) data to determine whether there are any gender differences in grey matter atrophy patterns over time in 197 individuals with probable Alzheimer’s disease (AD) and 266 with amnestic mild cognitive impairment (aMCI), compared with 224 healthy controls participating in the Alzheimer’s Disease Neuroimaging Initiative (ADNI). While previous research has differentiated probable AD and aMCI groups from controls in brain atrophy, it is unclear whether and how sex plays a role in patterns of change over time. Using regional volumetric maps, we fit longitudinal models to the grey matter data collected at repeated occasions, seeking differences in patterns of volume change over time by sex and diagnostic group in a voxel-wise analysis. Additionally, using a region-of-interest approach, we fit longitudinal models to the global volumetric data of predetermined brain regions to determine whether this more conventional approach is sufficient for determining sex and group differences in atrophy. Our longitudinal analyses revealed that, of the various grey matter regions investigated, males and females in the AD group and the aMCI group showed different patterns of decline over time compared to controls in the bilateral precuneus, bilateral caudate nucleus, right entorhinal gyrus, bilateral thalamus, bilateral middle temporal gyrus, left insula, and right amygdala. As one of the first investigation to model more than two time points of structural MRI data over time, our findings add insight into how AD and aMCI males and females differ from controls and from each other over time. PMID:21356315

  2. Neuroimaging the brain-gut axis in patients with irritable bowel syndrome

    PubMed Central

    Weaver, Kristen R; Sherwin, LeeAnne B; Walitt, Brian; Melkus, Gail D’Eramo; Henderson, Wendy A

    2016-01-01

    AIM: To summarize and synthesize current literature on neuroimaging the brain-gut axis in patients with irritable bowel syndrome (IBS). METHODS: A database search for relevant literature was conducted using PubMed, Scopus and Embase in February 2015. Date filters were applied from the year 2009 and onward, and studies were limited to those written in the English language and those performed upon human subjects. The initial search yielded 797 articles, out of which 38 were pulled for full text review and 27 were included for study analysis. Investigations were reviewed to determine study design, methodology and results, and data points were placed in tabular format to facilitate analysis of study findings across disparate investigations. RESULTS: Analysis of study data resulted in the abstraction of four key themes: Neurohormonal differences, anatomic measurements of brain structure and connectivity, differences in functional responsiveness of the brain during rectal distention, and confounding/correlating patient factors. Studies in this review noted alterations of glutamate in the left hippocampus (HIPP), commonalities across IBS subjects in terms of brain oscillation patterns, cortical thickness/gray matter volume differences, and neuroanatomical regions with increased activation in patients with IBS: Anterior cingulate cortex, mid cingulate cortex, amygdala, anterior insula, posterior insula and prefrontal cortex. A striking finding among interventions was the substantial influence that patient variables (e.g., sex, psychological and disease related factors) had upon the identification of neuroanatomical differences in structure and connectivity. CONCLUSION: The field of neuroimaging can provide insight into underlying physiological differences that distinguish patients with IBS from a healthy population. PMID:27158548

  3. Relation between neuropsychological and neuroimaging findings in patients with late whiplash syndrome

    PubMed Central

    Radanov, B.; Bicik, I.; Dvorak, J.; Antinnes, J.; von Schulthess, G. K; Buck, A.

    1999-01-01

    OBJECTIVES—The interpretation of long term cognitive impairment after whiplash injury is still a problem for many physicians. On the grounds of nuclear medicine findings previous research speculated that brain damage is responsible for cognitive problems of patients with whiplash. To test this hypothesis the relation between neuroimaging and neuropsychological findings was analysed.
METHODS—Twenty one patients (11 women, 10 men, mean age 42.2 (SD 8.6) years) with the late whiplash syndrome (average interval of trauma 26.1 (SD 20.7) months) referred for diagnostic action to the Department of Neurology were investigated. Assessment included computer assisted assessment of working memory and divided attention, neuroimaging (by the means of [99mTc]-HMPAO-SPECT, [15O]-H2O-PET and [18F]-FDG-PET), testing of emotional functioning (depression and anxiety ratings), and pain intensity at the time of testing.
RESULTS—On average, scoring on tests of cognitive functioning was very low. However, no significant correlations were found between regional perfusion or metabolism in any brain area and the scores of divided attention or working memory. By contrast, significant relations were found between indices of impaired emotional functioning (state anxiety) and divided attention. In addition, low scoring in divided attention was significantly correlated with pain intensity at the time of testing.
CONCLUSIONS—The present data do not provide evidence of a significant relation between detectable morphological or functional brain damage and impaired cognitive performance in the late whiplash syndrome. Results indicate triggering of emotional and cognitive symptoms on the basis of initial injury of the cervical spine.

 PMID:10201421

  4. Primary and secondary central nervous system vasculitis: clinical manifestations, laboratory findings, neuroimaging, and treatment analysis.

    PubMed

    Vera-Lastra, Olga; Sepúlveda-Delgado, Jesús; Cruz-Domínguez, María del Pilar; Medina, Gabriela; Casarrubias-Ramírez, Moisés; Molina-Carrión, Luis E; Pineda-Galindo, Luis F; Olvera-Acevedo, Arturo; Hernández-Gonzalez, Claudia; Jara, Luis J

    2015-04-01

    The objectives of this study are to compare the initial clinical, laboratory, and imaging features in primary central nervous system vasculitis (PCNSV) vs secondary central nervous system vasculitis (SCNSV) and follow up after treatment with intravenous cyclophosphamide (IV-CYC) plus glucocorticosteroids (GCS): methylprednisolone (MP). Neurological, laboratory, and neuroimaging findings were analyzed in PCNSV and SCNSV patients. Cerebral biopsy (CB) was performed in nine patients. Both groups received at onset MP plus IV-CYC for 6 months, followed by bimonthly IV-CYC plus prednisone (PND) for 12 months. All patients were followed during 36 months. Thirty patients were included (12 PCNSV and 18 SCNSV). Focal and non-focal neurological manifestations were similar in both groups, headache being the most frequent manifestation in both groups. Fatigue, myalgias, arthralgias, neuropathy, low leukocytes and platelets, elevated erythrocyte sedimentation rate, positive antinuclear antibodies (ANA), anti-double-stranded DNA (dsDNA), antineutrophil cytoplasmic antibodies (ANCA), low complement, and rheumatoid factor were more frequent in SCNSV (p < 0.05). In cerebrospinal fluid, pleocytosis and proteins were higher in PCNSV (p < 0.05). Periventricular and subcortical hyperintense lesions were observed in cranial magnetic resonance imaging in both vasculitides. Cerebral angiography and angioresonance showed narrowing of vasculature in all patients in both groups. CB showed gliosis and lymphocytic infiltration within and around the walls in four patients and granulomatous infiltration in the other patients. After treatment, the Kaplan-Meier survival curve showed a higher relapse-free survival in PCNSV (p < 0.05). Neurological manifestations and neuroimaging findings were similar in both groups of vasculitides, but general symptoms, joint, musculoskeletal, and peripheral neuropathy were preponderant in SCNSV. After treatment with IV-CYC and GCS, patients with PCNSV

  5. Transcranial magnetic stimulation in schizophrenia: the contribution of neuroimaging.

    PubMed

    Du, Zhong-de; Wang, R; Prakash, Ravi; Chaudhury, S; Dayananda, G

    2012-01-01

    At the most basic level, the Transcranial Magnetic Stimulation(TMS) is a neuro-scientific tool that exerts its action by influencing the neo-cortical functions. However, in-spite of so many well-evidenced roles of TMS in neuropsychiatric conditions, its exact mechanism of action remains to be known. More intriguing are its therapeutic effects in Schizophrenia at the Cerebral-level. In this review, we adopt a neuro-imaging approach for this exploration. We review the present literature for the studies in Schizophrenia which have used a combination of rTMS with 1) Electroenchephalogram (EEG) 2)The functional Magnetic Resonance Imaging (fMRI) and the 3) Positron Emission Tomography (PET)/ Single-Photon Emission Computed Tomography. The TMS-EEG combination provides direct effects of TMS on the electro- magnetic field (EMF) of brain. The TMS-fMRI/PET/SPECT combinations are very effective in exploring the functional connectivity in brains of Schizophrenia patients as well as in performing rTMS guided neuro-navigation. Our review suggests that TMS combined with other neuroimaging modalities are needed for a better clarification of its neural actions. PMID:23409741

  6. Neuroimaging studies of alexithymia: physical, affective, and social perspectives

    PubMed Central

    2013-01-01

    Alexithymia refers to difficulty in identifying and expressing one’s emotions, and it is related to disturbed emotional regulation. It was originally proposed as a personality trait that plays a central role in psychosomatic diseases. This review of neuroimaging studies on alexithymia suggests that alexithymia is associated with reduced neural responses to emotional stimuli from the external environment, as well as with reduced activity during imagery, in the limbic and paralimbic areas (i.e., amygdala, insula, anterior/posterior cingulate cortex). In contrast, alexithymia is also known to be associated with enhanced neural activity in somatosensory and sensorimotor regions, including the insula. Moreover, neural activity in the medial, prefrontal, and insula cortex was lowered when people with alexithymia were involved in social tasks. Because most neuroimaging studies have been based on sampling by self-reported questionnaires, the contrasted features of neural activities in response to internal and external emotional stimuli need to be elucidated. The social and emotional responses of people with alexithymia are discussed and recommendations for future research are presented. PMID:23537323

  7. [A case of pontine astrocytoma with unusual neuroimaging features].

    PubMed

    Matsuoka, Hidenori; Maruyama, Daisuke; Takegami, Tetsuro; Hamasaki, Tomoyuki; Kakita, Kiyohito; Mineura, Katsuyoshi

    2009-10-01

    We would like to report a rare case of pontine glioma with unusual neuroimaging features. The patient was a 3-year-old girl who suffered from chronic nausea and gait disturbance for several months. Computed tomography (CT) demonstrated ventricular dilatation, and ventricular peritoneal (VP) shunt was performed for idiopathic hydrocephalus at another hospital. Fever of unknown origin continued for a month after the VP shunt. At our hospital, cerebrospinal fluid examination showed bacterial meningitis, and it was assumed that shunt infection lead to shunt failure. Magnetic resonance imaging (MRI) revealed hydrocephalus and pontine swelling, and serial MRI suggested brainstem tumor extending to the bilateral thalamus. The patient underwent stereotactic biopsy of the left thalamic tumor, under general anesthesia, and the histological diagnosis was anaplastic astrocytoma. Diffuse pontine glioma rarely increases without cranial nerve deficits. In the present case, pontine glioma extended to the bilateral thalamus symmetrically. It was difficult to diagnose the presented lesion as pontine glioma in the early period because of its unusual neuroimaging.

  8. Understanding face perception by means of prosopagnosia and neuroimaging.

    PubMed

    Rossion, Bruno

    2014-06-01

    Understanding the human neuro-anatomy of face recognition is a long-standing goal of Cognitive Neuroscience. Studies of patients with face recognition impairment following brain damage (i.e., acquired prosopagnosia) have revealed the specificity of face recognition, the importance and nature of holistic/configural perception of individual faces, and the distribution of this function in the ventral occipito-temporal (VOT) cortex, with a right hemispheric dominance. Yet, neuroimaging studies in this field have essentially focused on a single face-selective area of the VOT and underestimated the right hemisphere superiority. Findings in these studies have also been taken as supporting a hierarchical view of face perception, according to which a face is decomposed into parts in early face-selective areas, these parts being subsequently integrated into a whole representation in higher-order areas. This review takes a historical and current perspective on the study of acquired prosopagnosia and neuroimaging that challenges this latter view. It argues for a combination of these methods, an approach suggesting a coarse-to-fine emergence of the holistic face percept in a non-hierarchical network of cortical face-selective areas.

  9. Behavioral, computational, and neuroimaging studies of acquired apraxia of speech.

    PubMed

    Ballard, Kirrie J; Tourville, Jason A; Robin, Donald A

    2014-01-01

    A critical examination of speech motor control depends on an in-depth understanding of network connectivity associated with Brodmann areas 44 and 45 and surrounding cortices. Damage to these areas has been associated with two conditions-the speech motor programming disorder apraxia of speech (AOS) and the linguistic/grammatical disorder of Broca's aphasia. Here we focus on AOS, which is most commonly associated with damage to posterior Broca's area (BA) and adjacent cortex. We provide an overview of our own studies into the nature of AOS, including behavioral and neuroimaging methods, to explore components of the speech motor network that are associated with normal and disordered speech motor programming in AOS. Behavioral, neuroimaging, and computational modeling studies are indicating that AOS is associated with impairment in learning feedforward models and/or implementing feedback mechanisms and with the functional contribution of BA6. While functional connectivity methods are not yet routinely applied to the study of AOS, we highlight the need for focusing on the functional impact of localized lesions throughout the speech network, as well as larger scale comparative studies to distinguish the unique behavioral and neurological signature of AOS. By coupling these methods with neural network models, we have a powerful set of tools to improve our understanding of the neural mechanisms that underlie AOS, and speech production generally. PMID:25404911

  10. Behavioral, computational, and neuroimaging studies of acquired apraxia of speech

    PubMed Central

    Ballard, Kirrie J.; Tourville, Jason A.; Robin, Donald A.

    2014-01-01

    A critical examination of speech motor control depends on an in-depth understanding of network connectivity associated with Brodmann areas 44 and 45 and surrounding cortices. Damage to these areas has been associated with two conditions—the speech motor programming disorder apraxia of speech (AOS) and the linguistic/grammatical disorder of Broca’s aphasia. Here we focus on AOS, which is most commonly associated with damage to posterior Broca’s area (BA) and adjacent cortex. We provide an overview of our own studies into the nature of AOS, including behavioral and neuroimaging methods, to explore components of the speech motor network that are associated with normal and disordered speech motor programming in AOS. Behavioral, neuroimaging, and computational modeling studies are indicating that AOS is associated with impairment in learning feedforward models and/or implementing feedback mechanisms and with the functional contribution of BA6. While functional connectivity methods are not yet routinely applied to the study of AOS, we highlight the need for focusing on the functional impact of localized lesions throughout the speech network, as well as larger scale comparative studies to distinguish the unique behavioral and neurological signature of AOS. By coupling these methods with neural network models, we have a powerful set of tools to improve our understanding of the neural mechanisms that underlie AOS, and speech production generally. PMID:25404911

  11. Neuroimaging in moderate MDMA use: A systematic review.

    PubMed

    Mueller, F; Lenz, C; Steiner, M; Dolder, P C; Walter, M; Lang, U E; Liechti, M E; Borgwardt, S

    2016-03-01

    MDMA ("ecstasy") is widely used as a recreational drug, although there has been some debate about its neurotoxic effects in humans. However, most studies have investigated subjects with heavy use patterns, and the effects of transient MDMA use are unclear. In this review, we therefore focus on subjects with moderate use patterns, in order to assess the evidence for harmful effects. We searched for studies applying neuroimaging techniques in man. Studies were included if they provided at least one group with an average of <50 lifetime episodes of ecstasy use or an average lifetime consumption of <100 ecstasy tablets. All studies published before July 2015 were included. Of the 250 studies identified in the database search, 19 were included. There is no convincing evidence that moderate MDMA use is associated with structural or functional brain alterations in neuroimaging measures. The lack of significant results was associated with high methodological heterogeneity in terms of dosages and co-consumption of other drugs, low quality of studies and small sample sizes. PMID:26746590

  12. Metabolic neuroimaging of the brain in diabetes mellitus and hypoglycaemia.

    PubMed

    Cheah, Yee-Seun; Amiel, Stephanie A

    2012-10-01

    Functional neuroimaging techniques can be used to study changes in regional brain activation, using changes in surrogate markers such as regional cerebral perfusion and rates of glucose uptake or metabolism. These approaches are shedding new light on two major health problems: the increasing burden of type 2 diabetes mellitus (T2DM), which is driven by the rising prevalence of insulin resistance and obesity; and recurrent intractable problematic hypoglycaemia, which is driven by the cognitive impairment that can occur in association with iatrogenic hypoglycaemic episodes. Some patients with diabetes mellitus lose awareness of being hypoglycaemic, which puts them at risk of severe hypoglycaemia as they are unlikely to take action to prevent the condition worsening. Involvement of corticolimbic brain and centres serving higher executive functions as well as the hypothalamus has been demonstrated in both situations and has implications for therapy. This Review describes the relevant principles of functional neuroimaging techniques and presents data supporting the notion that the dysregulation of central pathways involved in metabolic regulation, reward and appetite could contribute to problematic hypoglycaemia during therapy for diabetes mellitus and to insulin-resistant obesity and T2DM. Understanding these dysregulations could enable the development of novel clinical interventions.

  13. Structural Neuroimaging Markers of Cognitive Decline in Parkinson's Disease.

    PubMed

    Hanganu, Alexandru; Monchi, Oury

    2016-01-01

    Cognitive impairment in patients with Parkinson's disease is a major challenge since it has been established that 25 to 40% of patients will develop cognitive impairment early in the disease. Furthermore, it has been reported that up to 80% of Parkinsonian patients will eventually develop dementia. Thus, it is important to improve the diagnosing procedures in order to detect cognitive impairment at early stages of development and to delay as much as possible the developing of dementia. One major challenge is that patients with mild cognitive impairment exhibit measurable cognitive deficits according to recently established criteria, yet those deficits are not severe enough to interfere with daily living, hence being avoided by patients, and might be overseen by clinicians. Recent advances in neuroimaging brain analysis allowed the establishment of several anatomical markers that have the potential to be considered for early detection of cognitive impairment in Parkinsonian patients. This review aims to outline the neuroimaging possibilities in diagnosing cognitive impairment in patients with Parkinson's disease and to take into consideration the near-future possibilities of their implementation into clinical practice.

  14. A multi-subject, multi-modal human neuroimaging dataset

    PubMed Central

    Wakeman, Daniel G; Henson, Richard N

    2015-01-01

    We describe data acquired with multiple functional and structural neuroimaging modalities on the same nineteen healthy volunteers. The functional data include Electroencephalography (EEG), Magnetoencephalography (MEG) and functional Magnetic Resonance Imaging (fMRI) data, recorded while the volunteers performed multiple runs of hundreds of trials of a simple perceptual task on pictures of familiar, unfamiliar and scrambled faces during two visits to the laboratory. The structural data include T1-weighted MPRAGE, Multi-Echo FLASH and Diffusion-weighted MR sequences. Though only from a small sample of volunteers, these data can be used to develop methods for integrating multiple modalities from multiple runs on multiple participants, with the aim of increasing the spatial and temporal resolution above that of any one modality alone. They can also be used to integrate measures of functional and structural connectivity, and as a benchmark dataset to compare results across the many neuroimaging analysis packages. The data are freely available from https://openfmri.org/. PMID:25977808

  15. Structural Neuroimaging Markers of Cognitive Decline in Parkinson's Disease

    PubMed Central

    Hanganu, Alexandru; Monchi, Oury

    2016-01-01

    Cognitive impairment in patients with Parkinson's disease is a major challenge since it has been established that 25 to 40% of patients will develop cognitive impairment early in the disease. Furthermore, it has been reported that up to 80% of Parkinsonian patients will eventually develop dementia. Thus, it is important to improve the diagnosing procedures in order to detect cognitive impairment at early stages of development and to delay as much as possible the developing of dementia. One major challenge is that patients with mild cognitive impairment exhibit measurable cognitive deficits according to recently established criteria, yet those deficits are not severe enough to interfere with daily living, hence being avoided by patients, and might be overseen by clinicians. Recent advances in neuroimaging brain analysis allowed the establishment of several anatomical markers that have the potential to be considered for early detection of cognitive impairment in Parkinsonian patients. This review aims to outline the neuroimaging possibilities in diagnosing cognitive impairment in patients with Parkinson's disease and to take into consideration the near-future possibilities of their implementation into clinical practice. PMID:27190672

  16. Neuroimaging correlates of pharmacological and psychological treatments for specific phobia.

    PubMed

    Linares, Ila M; Chags, Marcos H N; Machado-de-Sousa, João P; Crippa, José A S; Hallak, Jaime E C

    2014-01-01

    Specific phobia is an anxiety disorder characterized by irrational fear and avoidance of specific things or situations, interfering significantly with the patients' daily life. Treatment for the disorder consists of both pharmacological and psychological approaches, mainly cognitive behavioral therapy (CBT). Neuroimaging techniques have been used in an attempt to improve our understanding of the neurobiology of SP and of the effects of treatment options available. This review describes the design and results of eight articles investigating the neuroimaging correlates of pharmacological and psychological treatments for SP. The studies show that CBT is effective in SP, leading to a reduction of anxiety symptoms that is accompanied by functional alterations in the brain. The results of pharmacological interventions for SP are less uniform, but suggest that the partial agonist of the NMDA (N-methyl D-aspartate) receptor DCS (D-cycloserine) can be used in combination with psychotherapy techniques for the achievement of quicker treatment response and that DCS modulates the function of structures implicated in the neurobiology of SP. Further research should explore the augmentation of CBT treatment with DCS in controlled trials.

  17. Neuroimaging in pediatric leukemia and lymphoma: differential diagnosis.

    PubMed

    Vázquez, Elida; Lucaya, Javier; Castellote, Amparo; Piqueras, Joaquim; Sainz, Pilar; Olivé, Teresa; Sánchez-Toledo, José; Ortega, Juan J

    2002-01-01

    Recent advances in therapy for pediatric hematologic neoplasms have greatly improved the prognosis but have resulted in an increased incidence of associated complications and toxic effects. The main neuroimaging features in pediatric patients with leukemia or lymphoma treated with chemotherapy or radiation therapy were retrospectively reviewed. To simplify the approach and facilitate differential diagnosis, the neuroimaging features have been classified into three main categories: central nervous system manifestations of primary disease, side effects of therapeutic procedures (radiation therapy, chemotherapy, bone marrow transplantation), and complications due to immunosuppression, particularly infections. Manifestations of primary disease include cerebrovascular complications (hemorrhage, cerebral infarction) and central nervous system involvement (infiltration of the meninges, parenchyma, bone marrow, orbit, and spine). Effects of radiation therapy include white matter disease, mineralizing microangiopathy, parenchymal brain volume loss, radiation-induced cryptic vascular malformations, and second neoplasms. Effects of chemotherapy and bone marrow transplantation include hemorrhage, dural venous thrombosis, white matter disease, reversible posterior leukoencephalopathy syndrome, and anterior lumbosacral radiculopathy. Both the underlying malignancy and antineoplastic therapy can cause immunosuppression. Fungi are the most frequent causal microorganisms in immunosuppressed patients with infection. Familiarity with the imaging findings is essential for proper diagnosis of neurologic symptoms in pediatric patients with oncohematologic disease. PMID:12432112

  18. Very poor outcome schizophrenia: Clinical and neuroimaging aspects

    PubMed Central

    Mitelman, Serge A.; Buchsbaum, Monte S.

    2009-01-01

    In spite of significant advances in treatment of patients with schizophrenia and continued efforts towards their deinstitutionalization, a considerable group of patients remain chronically hospitalized or otherwise dependent on others for basic necessities of life. It has been proposed that these patients belong to a distinct etiopathological subgroup, termed Kraepelinian, whose course of illness may be progressive and resistant to treatment. Indeed, longitudinal studies appear to show that elderly Kraepelinian patients follow a course of rapid cognitive and functional deterioration, commensurate with a dementing process, and that their poor functional status is closely correlated with the cognitive deterioration. Recent neuroimaging studies described a pattern of posteriorization of grey and white matter deficits with poor outcome in schizophrenia, and produced a constellation of findings implicating primary processing of visual and auditory information as central to the impaired functional status in this patient group. These studies are summarized in detail in this review and future directions for neuroimaging assessment of very poor outcome patients with schizophrenia are suggested. PMID:17671868

  19. Insulin action in the human brain: evidence from neuroimaging studies.

    PubMed

    Kullmann, S; Heni, M; Fritsche, A; Preissl, H

    2015-06-01

    Thus far, little is known about the action of insulin in the human brain. Nonetheless, recent advances in modern neuroimaging techniques, such as functional magnetic resonance imaging (fMRI) or magnetoencephalography (MEG), have made it possible to investigate the action of insulin in the brain in humans, providing new insights into the pathogenesis of brain insulin resistance and obesity. Using MEG, the clinical relevance of the action of insulin in the brain was first identified, linking cerebral insulin resistance with peripheral insulin resistance, genetic predisposition and weight loss success in obese adults. Although MEG is a suitable tool for measuring brain activity mainly in cortical areas, fMRI provides high spatial resolution for cortical as well as subcortical regions. Thus, the action of insulin can be detected within all eating behaviour relevant regions, which include regions deeply located within the brain, such as the hypothalamus, midbrain and brainstem, as well as regions within the striatum. In this review, we outline recent advances in the field of neuroimaging aiming to investigate the action of insulin in the human brain using different routes of insulin administration. fMRI studies have shown a significant insulin-induced attenuation predominantly in the occipital and prefrontal cortical regions and the hypothalamus, successfully localising insulin-sensitive brain regions in healthy, mostly normal-weight individuals. However, further studies are needed to localise brain areas affected by insulin resistance in obese individuals, which is an important prerequisite for selectively targeting brain insulin resistance in obesity.

  20. Neuronal oscillations in sleep: insights from functional neuroimaging.

    PubMed

    Dang-Vu, Thien Thanh

    2012-09-01

    Recent functional neuroimaging studies have investigated brain activity patterns during sleep in humans, beyond the conventionally defined sleep stages. These works have characterized the neural activations related to the major brain oscillations of sleep, that is, spindles and slow waves during non-rapid-eye-movement sleep and ponto-geniculo-occipital waves during rapid-eye-movement sleep. These phasic events have been found associated with increases of brain activity in specific neural networks, which identify structures involved in the generation of sleep oscillations. Most importantly, these results confirm that, even during the deepest stages of sleep, neuronal network activities are sustained and organized by spontaneous brain oscillations of sleep. The understanding of the neural mechanisms underlying sleep oscillations is fundamental since increasing evidence suggests a pivotal role for these rhythms in the functional properties of sleep. In particular, interactions between the sleeping brain and the surrounding environment are closely modulated by neuronal oscillations of sleep. Functional neuroimaging studies have demonstrated that spindles distort the transmission of auditory information to the cortex, therefore isolating the brain from external disturbances during sleep. In contrast, slow waves evoked by acoustic stimulation--and also termed K-complexes--are associated with larger auditory cortex activation, thus reflecting an enhanced processing of external information during sleep. Future brain imaging studies of sleep should further explore the contribution of neuronal oscillations to the off-line consolidation of memory during sleep.

  1. Multimodal Functional Neuroimaging: Integrating Functional MRI and EEG/MEG

    PubMed Central

    He, Bin; Liu, Zhongming

    2010-01-01

    Noninvasive functional neuroimaging, as an important tool for basic neuroscience research and clinical diagnosis, continues to face the need of improving the spatial and temporal resolution. While existing neuroimaging modalities might approach their limits in imaging capability mostly due to fundamental as well as technical reasons, it becomes increasingly attractive to integrate multiple complementary modalities in an attempt to significantly enhance the spatiotemporal resolution that cannot be achieved by any modality individually. Electrophysiological and hemodynamic/metabolic signals reflect distinct but closely coupled aspects of the underlying neural activity. Combining fMRI and EEG/MEG data allows us to study brain function from different perspectives. In this review, we start with an overview of the physiological origins of EEG/MEG and fMRI, as well as their fundamental biophysics and imaging principles; it is followed by a review of major progresses in understanding and modeling the neurovascular coupling, methodologies for the fMRI-EEG/MEG integration and EEG-fMRI simultaneous recording; finally, important remaining issues and perspectives (including brain connectivity imaging) are summarized. PMID:20634915

  2. Neuroimaging characteristics of ruptured aneurysm as predictors of outcome after aneurysmal subarachnoid hemorrhage: pooled analyses of the SAHIT cohort.

    PubMed

    Jaja, Blessing N R; Lingsma, Hester; Steyerberg, Ewout W; Schweizer, Tom A; Thorpe, Kevin E; Macdonald, R Loch

    2016-06-01

    OBJECT Neuroimaging characteristics of ruptured aneurysms are important to guide treatment selection, and they have been studied for their value as outcome predictors following aneurysmal subarachnoid hemorrhage (SAH). Despite multiple studies, the prognostic value of aneurysm diameter, location, and extravasated SAH clot on computed tomography scan remains debatable. The authors aimed to more precisely ascertain the relation of these factors to outcome. METHODS The data sets of studies included in the Subarachnoid Hemorrhage International Trialists (SAHIT) repository were analyzed including data on ruptured aneurysm location and diameter (7 studies, n = 9125) and on subarachnoid clot graded on the Fisher scale (8 studies; n = 9452) for the relation to outcome on the Glasgow Outcome Scale (GOS) at 3 months. Prognostic strength was quantified by fitting proportional odds logistic regression models. Univariable odds ratios (ORs) were pooled across studies using random effects models. Multivariable analyses were adjusted for fixed effect of study, age, neurological status on admission, other neuroimaging factors, and treatment modality. The neuroimaging predictors were assessed for their added incremental predictive value measured as partial R(2). RESULTS Spline plots indicated outcomes were worse at extremes of aneurysm size, i.e., less than 4 or greater than 9 mm. In between, aneurysm size had no effect on outcome (OR 1.03, 95% CI 0.98-1.09 for 9 mm vs 4 mm, i.e., 75th vs 25th percentile), except in those who were treated conservatively (OR 1.17, 95% CI 1.02-1.35). Compared with anterior cerebral artery aneurysms, posterior circulation aneurysms tended to result in slightly poorer outcome in patients who underwent endovascular coil embolization (OR 1.13, 95% CI 0.82-1.57) or surgical clipping (OR 1.32, 95% CI 1.10-1.57); the relation was statistically significant only in the latter. Fisher CT subarachnoid clot burden was related to outcome in a gradient manner. Each

  3. Neuroimaging Studies of Speech: An Overview of Techniques and Methodological Approaches.

    ERIC Educational Resources Information Center

    Fiez, Julie A.

    2001-01-01

    Discussion of how functional neuroimaging has been applied to the study of speech production first reviews neuroimaging methods and limitations, then describes two approaches to study of the relevant speech areas: comparison across different language production tasks and comparison of effects of different stimuli within a single task. Examples…

  4. Seeing responsibility: can neuroimaging teach us anything about moral and legal responsibility?

    PubMed

    Wasserman, David; Johnston, Josephine

    2014-01-01

    As imaging technologies help us understand the structure and function of the brain, providing insight into human capabilities as basic as vision and as complex as memory, and human conditions as impairing as depression and as fraught as psychopathy, some have asked whether they can also help us understand human agency. Specifically, could neuroimaging lead us to reassess the socially significant practice of assigning and taking responsibility? While responsibility itself is not a psychological process open to investigation through neuroimaging, decision-making is. Over the past decade, different researchers and scholars have sought to use neuroimaging (or the results of neuroimaging studies) to investigate what is going on in the brain when we make decisions. The results of this research raise the question whether neuroscience-especially now that it includes neuroimaging-can and should alter our understandings of responsibility and our related practice of holding people responsible. It is this question that we investigate here.

  5. The Status of the Quality Control in Acupuncture-Neuroimaging Studies

    PubMed Central

    Qiu, Ke; Jing, Miaomiao; Liu, Xiaoyan; Gao, Feifei; Liang, Fanrong; Zeng, Fang

    2016-01-01

    Using neuroimaging techniques to explore the central mechanism of acupuncture gains increasing attention, but the quality control of acupuncture-neuroimaging study remains to be improved. We searched the PubMed Database during 1995 to 2014. The original English articles with neuroimaging scan performed on human beings were included. The data involved quality control including the author, sample size, characteristics of the participant, neuroimaging technology, and acupuncture intervention were extracted and analyzed. The rigorous inclusion and exclusion criteria are important guaranty for the participants' homogeneity. The standard operation process of acupuncture and the stricter requirement for acupuncturist play significant role in quality control. More attention should be paid to the quality control in future studies to improve the reproducibility and reliability of the acupuncture-neuroimaging studies. PMID:27242911

  6. Neuroimaging and the school-based assessment of traumatic brain injury.

    PubMed

    Jantz, Paul B; Bigler, Erin D

    2014-01-01

    Advanced neuroimaging contributes to a greater understanding of brain pathology following a traumatic brain injury (TBI) and has the ability to guide neurorehabilitation decisions. When integrated with the school-based psychoeducational assessment of a child with a TBI, neuroimaging can provide a different perspective when interpreting educational and behavioral variables relevant to school-based neurorehabilitation. School psychologists conducting traditional psychoeducational assessments of children with TBI seldom obtain and integrate neuroimaging, despite its availability. This article presents contextual information on the medical assessment of TBI, major types of neuroimaging, and networks of the brain. A case study illustrates the value of incorporating neuroimaging into the standard school-based psychoeducational evaluations of children with traumatic brain injury. PMID:24473251

  7. Neuroimaging and the school-based assessment of traumatic brain injury.

    PubMed

    Jantz, Paul B; Bigler, Erin D

    2014-01-01

    Advanced neuroimaging contributes to a greater understanding of brain pathology following a traumatic brain injury (TBI) and has the ability to guide neurorehabilitation decisions. When integrated with the school-based psychoeducational assessment of a child with a TBI, neuroimaging can provide a different perspective when interpreting educational and behavioral variables relevant to school-based neurorehabilitation. School psychologists conducting traditional psychoeducational assessments of children with TBI seldom obtain and integrate neuroimaging, despite its availability. This article presents contextual information on the medical assessment of TBI, major types of neuroimaging, and networks of the brain. A case study illustrates the value of incorporating neuroimaging into the standard school-based psychoeducational evaluations of children with traumatic brain injury.

  8. More education, less administration: reflections of neuroimagers' attitudes to ethics through the qualitative looking glass.

    PubMed

    Kehagia, A A; Tairyan, K; Federico, C; Glover, G H; Illes, J

    2012-12-01

    In follow-up to a large-scale ethics survey of neuroscientists whose research involves neuroimaging, brain stimulation and imaging genetics, we conducted focus groups and interviews to explore their sense of responsibility about integrating ethics into neuroimaging and readiness to adopt new ethics strategies as part of their research. Safety, trust and virtue were key motivators for incorporating ethics into neuroimaging research. Managing incidental findings emerged as a predominant daily challenge for faculty, while student reports focused on the malleability of neuroimaging data and scientific integrity. The most frequently cited barrier was time and administrative burden associated with the ethics review process. Lack of scholarly training in ethics also emerged as a major barrier. Participants constructively offered remedies to these challenges: development and dissemination of best practices and standardized ethics review for minimally invasive neuroimaging protocols. Students in particular, urged changes to curricula to include early, focused training in ethics.

  9. The Status of the Quality Control in Acupuncture-Neuroimaging Studies.

    PubMed

    Qiu, Ke; Jing, Miaomiao; Sun, Ruirui; Yang, Jie; Liu, Xiaoyan; He, Zhaoxuan; Yin, Shuai; Lan, Ying; Cheng, Shirui; Gao, Feifei; Liang, Fanrong; Zeng, Fang

    2016-01-01

    Using neuroimaging techniques to explore the central mechanism of acupuncture gains increasing attention, but the quality control of acupuncture-neuroimaging study remains to be improved. We searched the PubMed Database during 1995 to 2014. The original English articles with neuroimaging scan performed on human beings were included. The data involved quality control including the author, sample size, characteristics of the participant, neuroimaging technology, and acupuncture intervention were extracted and analyzed. The rigorous inclusion and exclusion criteria are important guaranty for the participants' homogeneity. The standard operation process of acupuncture and the stricter requirement for acupuncturist play significant role in quality control. More attention should be paid to the quality control in future studies to improve the reproducibility and reliability of the acupuncture-neuroimaging studies. PMID:27242911

  10. Seeing responsibility: can neuroimaging teach us anything about moral and legal responsibility?

    PubMed

    Wasserman, David; Johnston, Josephine

    2014-01-01

    As imaging technologies help us understand the structure and function of the brain, providing insight into human capabilities as basic as vision and as complex as memory, and human conditions as impairing as depression and as fraught as psychopathy, some have asked whether they can also help us understand human agency. Specifically, could neuroimaging lead us to reassess the socially significant practice of assigning and taking responsibility? While responsibility itself is not a psychological process open to investigation through neuroimaging, decision-making is. Over the past decade, different researchers and scholars have sought to use neuroimaging (or the results of neuroimaging studies) to investigate what is going on in the brain when we make decisions. The results of this research raise the question whether neuroscience-especially now that it includes neuroimaging-can and should alter our understandings of responsibility and our related practice of holding people responsible. It is this question that we investigate here. PMID:24634084

  11. What Value "Value Added"?

    ERIC Educational Resources Information Center

    Richards, Andrew

    2015-01-01

    Two quantitative measures of school performance are currently used, the average points score (APS) at Key Stage 2 and value-added (VA), which measures the rate of academic improvement between Key Stage 1 and 2. These figures are used by parents and the Office for Standards in Education to make judgements and comparisons. However, simple…

  12. Towards structured sharing of raw and derived neuroimaging data across existing resources

    PubMed Central

    Keator, D.B.; Helmer, K.; Steffener, J.; Turner, J.A.; Van Erp, T.G.M.; Gadde, S.; Ashish, N.; Burns, G.A.; Nichols, B.N.

    2013-01-01

    Data sharing efforts increasingly contribute to the acceleration of scientific discovery. Neuroimaging data is accumulating in distributed domain-specific databases and there is currently no integrated access mechanism nor an accepted format for the critically important meta-data that is necessary for making use of the combined, available neuroimaging data. In this manuscript, we present work from the Derived Data Working Group, an open-access group sponsored by the Biomedical Informatics Research Network (BIRN) and the International Neuroimaging Coordinating Facility (INCF) focused on practical tools for distributed access to neuroimaging data. The working group develops models and tools facilitating the structured interchange of neuroimaging meta-data and is making progress towards a unified set of tools for such data and meta-data exchange. We report on the key components required for integrated access to raw and derived neuroimaging data as well as associated meta-data and provenance across neuroimaging resources. The components include (1) a structured terminology that provides semantic context to data, (2) a formal data model for neuroimaging with robust tracking of data provenance, (3) a web service-based application programming interface (API) that provides a consistent mechanism to access and query the data model, and (4) a provenance library that can be used for the extraction of provenance data by image analysts and imaging software developers. We believe that the framework and set of tools outlined in this manuscript have great potential for solving many of the issues the neuroimaging community faces when sharing raw and derived neuroimaging data across the various existing database systems for the purpose of accelerating scientific discovery. PMID:23727024

  13. Introducing ADS Labs

    NASA Astrophysics Data System (ADS)

    Accomazzi, Alberto; Henneken, E.; Grant, C. S.; Kurtz, M. J.; Di Milia, G.; Luker, J.; Thompson, D. M.; Bohlen, E.; Murray, S. S.

    2011-05-01

    ADS Labs is a platform that ADS is introducing in order to test and receive feedback from the community on new technologies and prototype services. Currently, ADS Labs features a new interface for abstract searches, faceted filtering of results, visualization of co-authorship networks, article-level recommendations, and a full-text search service. The streamlined abstract search interface provides a simple, one-box search with options for ranking results based on a paper relevancy, freshness, number of citations, and downloads. In addition, it provides advanced rankings based on collaborative filtering techniques. The faceted filtering interface allows users to narrow search results based on a particular property or set of properties ("facets"), allowing users to manage large lists and explore the relationship between them. For any set or sub-set of records, the co-authorship network can be visualized in an interactive way, offering a view of the distribution of contributors and their inter-relationships. This provides an immediate way to detect groups and collaborations involved in a particular research field. For a majority of papers in Astronomy, our new interface will provide a list of related articles of potential interest. The recommendations are based on a number of factors, including text similarity, citations, and co-readership information. The new full-text search interface allows users to find all instances of particular words or phrases in the body of the articles in our full-text archive. This includes all of the scanned literature in ADS as well as a select portion of the current astronomical literature, including ApJ, ApJS, AJ, MNRAS, PASP, A&A, and soon additional content from Springer journals. Fulltext search results include a list of the matching papers as well as a list of "snippets" of text highlighting the context in which the search terms were found. ADS Labs is available at http://adslabs.org

  14. The down syndrome biomarker initiative (DSBI) pilot: proof of concept for deep phenotyping of Alzheimer’s disease biomarkers in down syndrome

    PubMed Central

    Rafii, Michael S.; Wishnek, Hannah; Brewer, James B.; Donohue, Michael C.; Ness, Seth; Mobley, William C.; Aisen, Paul S.; Rissman, Robert A.

    2015-01-01

    To gain further knowledge on the preclinical phase of Alzheimer’s disease (AD), we sought to characterize cognitive performance, neuroimaging and plasma-based AD biomarkers in a cohort of non-demented adults with down syndrome (DS). The goal of the down syndrome biomarker Initiative (DSBI) pilot is to test feasibility of this approach for future multicenter studies. We enrolled 12 non-demented participants with DS between the ages of 30–60 years old. Participants underwent extensive cognitive testing, volumetric MRI, amyloid positron emission tomography (PET; 18F-florbetapir), fluorodeoxyglucose (FDG) PET (18F-fluorodeoxyglucose) and retinal amyloid imaging. In addition, plasma beta-amyloid (Aβ) species were measured and Apolipoprotein E (ApoE) genotyping was performed. Results from our multimodal analysis suggest greater hippocampal atrophy with amyloid load. Additionally, we identified an inverse relationship between amyloid load and regional glucose metabolism. Cognitive and functional measures did not correlate with amyloid load in DS but did correlate with regional FDG PET measures. Biomarkers of AD can be readily studied in adults with DS as in other preclinical AD populations. Importantly, all subjects in this feasibility study were able to complete all test procedures. The data indicate that a large, multicenter longitudinal study is feasible to better understand the trajectories of AD biomarkers in this enriched population. This trial is registered with ClinicalTrials.gov, number NCT02141971. PMID:26441570

  15. Structural neuroimaging in schizophrenia: from methods to insights to treatments.

    PubMed

    Shenton, Martha E; Whitford, Thomas J; Kubicki, Marek

    2010-01-01

    Historically, Kraepelin speculated that dementia praecox resulted from damage to the cerebral cortex, most notably the frontal and temporal cortices. It is only recently, however, that tools have been available to test this hypothesis. Now, more than a century later, we know that schizophrenia is a brain disorder. This knowledge comes from critical advances in imaging technology--including computerized axial tomography, magnetic resonance imaging, and diffusion imaging--all of which provide an unprecedented view of neuroanatomical structures, in vivo. Here, we review evidence for structural neuroimaging abnormalities, beginning with evidence for focal brain abnormalities, primarily in gray matter, and proceeding to the quest to identify abnormalities in brain systems and circuits by focusing on damage to white matter connections in the brain. We then review future prospects that need to be explored and pursued in order to translate our current knowledge into an understanding of the neurobiology of schizophrenia, which can then be translated into novel treatments. PMID:20954428

  16. Neuroimaging studies in schizophrenia: an overview of research from Asia.

    PubMed

    Narayanaswamy, Janardhanan C; Venkatasubramanian, Ganesan; Gangadhar, Bangalore N

    2012-10-01

    Neuroimaging studies in schizophrenia help clarify the neural substrates underlying the pathogenesis of this neuropsychiatric disorder. Contemporary brain imaging in schizophrenia is predominated by magnetic resonance imaging (MRI)-based research approaches. This review focuses on the various imaging studies from India and their relevance to the understanding of brain abnormalities in schizophrenia. The existing studies are predominantly comprised of structural MRI reports involving region-of-interest and voxel-based morphometry approaches, magnetic resonance spectroscopy and single-photon emission computed tomography/positron emission tomography (SPECT/PET) studies. Most of these studies are significant in that they have evaluated antipsychotic-naïve schizophrenia patients--a relatively difficult population to obtain in contemporary research. Findings of these studies offer robust support to the existence of significant brain abnormalities at very early stages of the disorder. In addition, theoretically relevant relationships between these brain abnormalities and developmental aberrations suggest possible neurodevelopmental basis for these brain deficits. PMID:23057977

  17. Neuroimaging examination of newborns in vertically acquired infections.

    PubMed

    Lanari, Marcello; Capretti, Maria Grazia; Lazzarotto, Tiziana

    2011-10-01

    Congenital/perinatal nervous system (CNS) infections are an important cause of mortality and morbidity in neonatal period, and long-term sequelae. Many pathogens can lead to infections frequently involving the CNS, with possible disruption of brain development, which often is related to gestational age of maternal infection. The mechanism of infection and damage is different among the infectious agents, leading to more specific pathologic findings. It is necessary in newborns with confirmed or suspected CNS infection to undergo investigation by neuroimaging techniques to help healthcare providers, give adequate treatment and follow-up care and counsel parents. Computed tomography, Magnetic Resonance Imaging and cerebral ultrasonography are fundamental tools in evaluating infants with suspected or proved congenital/perinatal infections. Each imaging technique has its advantages, disadvantages and limits, since they are sometimes complementary. PMID:21888526

  18. Neuroimaging studies of striatum in cognition part II: Parkinson's disease

    PubMed Central

    Hanganu, Alexandru; Provost, Jean-Sebastien; Monchi, Oury

    2015-01-01

    In recent years a gradual shift in the definition of Parkinson's disease (PD) has been established, from a classical akinetic-rigid movement disorder to a multi-system neurodegenerative disease. While the pathophysiology of PD is complex and goes much beyond the nigro-striatal degeneration, the striatum has been shown to be responsible for many cognitive functions. Patients with PD develop impairments in multiple cognitive domains and the PD model is probably the most extensively studied regarding striatum dysfunction and its influence on cognition. Up to 40% of PD patients present cognitive impairment even in the early stages of disease development. Thus, understanding the key patterns of striatum and connecting regions' influence on cognition will help develop more specific approaches to alleviate cognitive impairment and slow down its decline. This review focuses on the contribution of neuroimaging studies in understanding how striatum impairment affects cognition in PD. PMID:26500512

  19. Characteristics of the athletes' brain: evidence from neurophysiology and neuroimaging.

    PubMed

    Nakata, Hiroki; Yoshie, Michiko; Miura, Akito; Kudo, Kazutoshi

    2010-03-01

    We review research on athletes' brains based on data obtained using non-invasive neurophysiological and neuroimaging methods; these data pertain to cognitive processing of visual, auditory, and somatosensory (tactile) stimulation as well as to motor processing, including preparation, execution, and imagery. It has been generally accepted that athletes are faster, stronger, able to jump higher, more accurate, more efficient, more consistent, and more automatic in their sports performances than non-athletes. These claims have been substantiated by neuroscientific evidence of the mechanisms underlying the plastic adaptive changes in the neuronal circuits of the brains of athletes. Reinforced neural networks and plastic changes are induced by the acquisition and execution of compound motor skills during extensive daily physical training that requires quick stimulus discrimination, decision making, and specific attention. In addition, it is likely that the manner of neuronal modulation differs among sports. We also discuss several problems that should be addressed in future studies.

  20. Structural neuroimaging in schizophrenia from methods to insights to treatments

    PubMed Central

    Shenton, Martha E.; Whitford, Thomas J.; Kubicki, Marek

    2010-01-01

    Historically, Kraepelin speculated that dementia praecox resulted from damage to the cerebral cortex, most notably the frontal and temporal cortices. It is only recently, however, that tools have been available to test this hypothesis. Now, more than a century later, we know that schizophrenia is a brain disorder. This knowledge comes from critical advances in imaging technology- including computerized axial tomography, magnetic resonance imaging, and diffusion imaging - all of which provide an unprecedented view of neuroanatomical structures, in vivo. Here, we review evidence for structural neuroimaging abnormalities, beginning with evidence for focal brain abnormalities, primarily in gray matter, and proceeding to the quest to identify abnormalities in brain systems and circuits by focusing on damage to white matter connections in the brain. We then review future prospects that need to be explored and pursued in order to translate our current knowledge into an understanding of the neurobiology of schizophrenia, which can then be translated into novel treatments. PMID:20954428

  1. Neuroimaging biomarkers for Parkinson disease: facts and fantasy.

    PubMed

    Perlmutter, Joel S; Norris, Scott A

    2014-12-01

    In this grand rounds, we focus on development, validation, and application of neuroimaging biomarkers for Parkinson disease (PD). We cover whether such biomarkers can be used to identify presymptomatic individuals (probably yes), provide a measure of PD severity (in a limited fashion, but frequently done poorly), investigate pathophysiology of parkinsonian disorders (yes, if done carefully), play a role in differential diagnosis of parkinsonism (not well), and investigate pathology underlying cognitive impairment (yes, in conjunction with postmortem data). Along the way, we clarify several issues about definitions of biomarkers and surrogate endpoints. The goal of this lecture is to provide a basis for interpreting current literature and newly proposed clinical tools in PD. In the end, one should be able to critically distinguish fact from fantasy. PMID:25363872

  2. Neuroimaging of dreaming: state of the art and limitations.

    PubMed

    Kussé, Caroline; Muto, Vincenzo; Mascetti, Laura; Matarazzo, Luca; Foret, Ariane; Bourdiec, Anahita Shaffii-Le; Maquet, Pierre

    2010-01-01

    During the last two decades, functional neuroimaging has been used to characterize the regional brain function during sleep in humans, at the macroscopic systems level. In addition, the topography of brain activity, especially during rapid eye movement sleep, was thought to be compatible with the general features of dreams. In contrast, the neural correlates of dreams remain largely unexplored. This review examines the difficulties associated with the characterization of dream correlates. ἓν οἶδα ὅτι οὐδὲν οἶδα Σωκράτης (The only thing I know is that I know nothing) Socrates.

  3. Preclinical PET Neuroimaging of [11C]Bexarotene.

    PubMed

    Rotstein, Benjamin H; Placzek, Michael S; Krishnan, Hema S; Pekošak, Aleksandra; Collier, Thomas Lee; Wang, Changning; Liang, Steven H; Burstein, Ethan S; Hooker, Jacob M; Vasdev, Neil

    2016-01-01

    Activation of retinoid X receptors (RXRs) has been proposed as a therapeutic mechanism for the treatment of neurodegeneration, including Alzheimer's and Parkinson's diseases. We previously reported radiolabeling of a Food and Drug Administration-approved RXR agonist, bexarotene, by copper-mediated [(11)C]CO2 fixation and preliminary positron emission tomography (PET) neuroimaging that demonstrated brain permeability in nonhuman primate with regional binding distribution consistent with RXRs. In this study, the brain uptake and saturability of [(11)C]bexarotene were studied in rats and nonhuman primates by PET imaging under baseline and greater target occupancy conditions. [(11)C]Bexarotene displays a high proportion of nonsaturable uptake in the brain and is unsuitable for RXR occupancy measurements in the central nervous system. PMID:27553293

  4. On Aims and Methods in the Neuroimaging of Derived Relations

    PubMed Central

    Dickins, David W

    2005-01-01

    Ingenious and seemingly powerful technologies have been developed recently that enable the visualization in some detail of events in the brain concomitant upon the ongoing behavioral performance of a human participant. Measurement of such brain events offers at the very least a new set of dependent variables in relation to which the independent variables familiarly manipulated in the operant laboratory may be explored. Two related paradigms in which a start has been made in such research concern the derivation of novel or emergent relations from a baseline set of trained relations, and include the phenomenon of transitive inference (TI), observed in studies of stimulus equivalence (SE) and serial learning (SL) or seriation. This paper reviews some published and forthcoming neuroimaging studies of these and related phenomena, and considers how this line of research both demands and represents a welcome synthesis between types of question and levels of explanation in behavioral science that often have been seen as antithetical. PMID:16596975

  5. Motivating forces of human actions. Neuroimaging reward and social interaction.

    PubMed

    Walter, Henrik; Abler, Birgit; Ciaramidaro, Angela; Erk, Susanne

    2005-11-15

    In neuroeconomics, reward and social interaction are central concepts to understand what motivates human behaviour. Both concepts are investigated in humans using neuroimaging methods. In this paper, we provide an overview about these results and discuss their relevance for economic behaviour. For reward it has been shown that a system exists in humans that is involved in predicting rewards and thus guides behaviour, involving a circuit including the striatum, the orbitofrontal cortex and the amygdala. Recent studies on social interaction revealed a mentalizing system representing the mental states of others. A central part of this system is the medial prefrontal cortex, in particular the anterior paracingulate cortex. The reward as well as the mentalizing system is engaged in economic decision-making. We will discuss implications of this study for neuromarketing as well as general implications of these results that may help to provide deeper insights into the motivating forces of human behaviour.

  6. Neurobehavioral, neurologic, and neuroimaging characteristics of fetal alcohol spectrum disorders.

    PubMed

    Glass, Leila; Ware, Ashley L; Mattson, Sarah N

    2014-01-01

    Alcohol consumption during pregnancy can have deleterious consequences for the fetus, including changes in central nervous system development leading to permanent neurologic alterations and cognitive and behavioral deficits. Individuals affected by prenatal alcohol exposure, including those with and without fetal alcohol syndrome, are identified under the umbrella of fetal alcohol spectrum disorders (FASD). While studies of humans and animal models confirm that even low to moderate levels of exposure can have detrimental effects, critical doses of such exposure have yet to be specified and the most clinically significant and consistent consequences occur following heavy exposure. These consequences are pervasive, devastating, and can result in long-term dysfunction. This chapter summarizes the neurobehavioral, neurologic, and neuroimaging characteristics of FASD, focusing primarily on clinical research of individuals with histories of heavy prenatal alcohol exposure, although studies of lower levels of exposure, particularly prospective, longitudinal studies, will be discussed where relevant.

  7. Human Neuroimaging of Oxytocin and Vasopressin in Social Cognition

    PubMed Central

    Zink, Caroline F; Meyer-Lindenberg, Andreas

    2012-01-01

    The neuropeptides oxytocin and vasopressin have increasingly been identified as modulators of human social behaviors and associated with neuropsychiatric disorders characterized by social dysfunction, such as autism. Identifying the human brain regions that are impacted by oxytocin and vasopressin in a social context is essential to fully characterize the role of oxytocin and vasopressin in complex human social cognition. Advances in human non-invasive neuroimaging techniques and genetics have enabled scientists to begin to elucidate the neurobiological basis of the influence of oxytocin and vasopressin on human social behaviors. Here we review the findings to-date from investigations of the acute and chronic effects of oxytocin and vasopressin on neural activity underlying social cognitive processes using “pharmacological fMRI” and “imaging genetics”, respectively. PMID:22326707

  8. Atlas generated generalized ROIs for use in functional neuroimaging

    SciTech Connect

    Thurfjell, L. . Dept. of Neuroradiology and Clinical Neurophysiology); Bohm, C. . Dept. of Physics)

    1994-08-01

    The interpretation of functional neuroimaging data can, in many cases, be facilitated by comparison with simulated data corresponding to the measuring situation. A computerized brain atlas is used to provide information regarding the spatial extent of the object being imaged. This knowledge combined with information about the resolution of the imaging device expressed as point spread functions is used to calculate a simulated image of the object. The simulated image can be regarded as a generalized region of interest (ROI) containing information of the object as viewed by the specific instrument. Generalized ROIs are used to automatically determine boundaries or ordinary ROIs and to provide recovery coefficients to compensate for partial volume effects. Simulations can also be used to generate three-dimensional data sets where different activity levels have been assigned to different anatomical structures. These methods are presented in this paper and some experimental results are shown.

  9. Functional neuroimaging studies of reading and reading disability (developmental dyslexia).

    PubMed

    Pugh, K R; Mencl, W E; Jenner, A R; Katz, L; Frost, S J; Lee, J R; Shaywitz, S E; Shaywitz, B A

    2000-01-01

    Converging evidence from a number of neuroimaging studies, including our own, suggest that fluent word identification in reading is related to the functional integrity of two consolidated left hemisphere (LH) posterior systems: a dorsal (temporo-parietal) circuit and a ventral (occipito-temporal) circuit. This posterior system is functionally disrupted in developmental dyslexia. Reading disabled readers, relative to nonimpaired readers, demonstrate heightened reliance on both inferior frontal and right hemisphere posterior regions, presumably in compensation for the LH posterior difficulties. We propose a neurobiological account suggesting that for normally developing readers the dorsal circuit predominates at first, and is associated with analytic processing necessary for learning to integrate orthographic features with phonological and lexical-semantic features of printed words. The ventral circuit constitutes a fast, late-developing, word identification system which underlies fluent word recognition in skilled readers.

  10. Motivating forces of human actions. Neuroimaging reward and social interaction.

    PubMed

    Walter, Henrik; Abler, Birgit; Ciaramidaro, Angela; Erk, Susanne

    2005-11-15

    In neuroeconomics, reward and social interaction are central concepts to understand what motivates human behaviour. Both concepts are investigated in humans using neuroimaging methods. In this paper, we provide an overview about these results and discuss their relevance for economic behaviour. For reward it has been shown that a system exists in humans that is involved in predicting rewards and thus guides behaviour, involving a circuit including the striatum, the orbitofrontal cortex and the amygdala. Recent studies on social interaction revealed a mentalizing system representing the mental states of others. A central part of this system is the medial prefrontal cortex, in particular the anterior paracingulate cortex. The reward as well as the mentalizing system is engaged in economic decision-making. We will discuss implications of this study for neuromarketing as well as general implications of these results that may help to provide deeper insights into the motivating forces of human behaviour. PMID:16216683

  11. Neurobehavioral, neurologic, and neuroimaging characteristics of fetal alcohol spectrum disorders.

    PubMed

    Glass, Leila; Ware, Ashley L; Mattson, Sarah N

    2014-01-01

    Alcohol consumption during pregnancy can have deleterious consequences for the fetus, including changes in central nervous system development leading to permanent neurologic alterations and cognitive and behavioral deficits. Individuals affected by prenatal alcohol exposure, including those with and without fetal alcohol syndrome, are identified under the umbrella of fetal alcohol spectrum disorders (FASD). While studies of humans and animal models confirm that even low to moderate levels of exposure can have detrimental effects, critical doses of such exposure have yet to be specified and the most clinically significant and consistent consequences occur following heavy exposure. These consequences are pervasive, devastating, and can result in long-term dysfunction. This chapter summarizes the neurobehavioral, neurologic, and neuroimaging characteristics of FASD, focusing primarily on clinical research of individuals with histories of heavy prenatal alcohol exposure, although studies of lower levels of exposure, particularly prospective, longitudinal studies, will be discussed where relevant. PMID:25307589

  12. Causal interpretation rules for encoding and decoding models in neuroimaging.

    PubMed

    Weichwald, Sebastian; Meyer, Timm; Özdenizci, Ozan; Schölkopf, Bernhard; Ball, Tonio; Grosse-Wentrup, Moritz

    2015-04-15

    Causal terminology is often introduced in the interpretation of encoding and decoding models trained on neuroimaging data. In this article, we investigate which causal statements are warranted and which ones are not supported by empirical evidence. We argue that the distinction between encoding and decoding models is not sufficient for this purpose: relevant features in encoding and decoding models carry a different meaning in stimulus- and in response-based experimental paradigms.We show that only encoding models in the stimulus-based setting support unambiguous causal interpretations. By combining encoding and decoding models trained on the same data, however, we obtain insights into causal relations beyond those that are implied by each individual model type. We illustrate the empirical relevance of our theoretical findings on EEG data recorded during a visuo-motor learning task. PMID:25623501

  13. MTA index: a simple 2D-method for assessing atrophy of the medial temporal lobe using clinically available neuroimaging

    PubMed Central

    Menéndez-González, Manuel; López-Muñiz, Alfonso; Vega, José A.; Salas-Pacheco, José M.; Arias-Carrión, Oscar

    2014-01-01

    Background and purpose: Despite a strong correlation to severity of AD pathology, the measurement of medial temporal lobe atrophy (MTA) is not being widely used in daily clinical practice as a criterion in the diagnosis of prodromal and probable AD. This is mainly because the methods available to date are sophisticated and difficult to implement for routine use in most hospitals—volumetric methods—or lack objectivity—visual rating scales. In this pilot study we aim to describe a new, simple and objective method for measuring the rate of MTA in relation to the global atrophy using clinically available neuroimaging and describe the rationale behind this method. Description: This method consists of calculating a ratio with the area of 3 regions traced manually on one single coronal MRI slide at the level of the interpeduncular fossa: (1) the medial temporal lobe (MTL) region (A); (2) the parenchima within the medial temporal region, that includes the hippocampus and the parahippocampal gyrus—the fimbria taenia and plexus choroideus are excluded—(B); and (3) the body of the ipsilateral lateral ventricle (C). Therefrom we can compute the ratio “Medial Temporal Atrophy index” at both sides as follows: MTAi = (A − B)× 10/C. Conclusions: The MTAi is a simple 2D-method for measuring the relative extent of atrophy in the MTL in relation to the global brain atrophy. This method can be useful for a more accurate diagnosis of AD in routine clinical practice. Further studies are needed to assess the usefulness of MTAi in the diagnosis of early AD, in tracking the progression of AD and in the differential diagnosis of AD with other dementias. PMID:24715861

  14. What can functional neuroimaging tell the experimental psychologist?

    PubMed

    Henson, Richard

    2005-02-01

    I argue here that functional neuroimaging data--which I restrict to the haemodynamic techniques of fMRI and PET--can inform psychological theorizing, provided one assumes a "systematic" function-structure mapping in the brain. In this case, imaging data simply comprise another dependent variable, along with behavioural data, that can be used to test competing theories. In particular, I distinguish two types of inference: function-to-structure deduction and structure-to-function induction. With the former inference, a qualitatively different pattern of activity over the brain under two experimental conditions implies at least one different function associated with changes in the independent variable. With the second type of inference, activity of the same brain region(s) under two conditions implies a common function, possibly not predicted a priori. I illustrate these inferences with imaging studies of recognition memory, short-term memory, and repetition priming. I then consider in greater detail what is meant by a "systematic" function-structure mapping and argue that, particularly for structure-to-function induction, this entails a one-to-one mapping between functional and structural units, although the structural unit may be a network of interacting regions and care must be taken over the appropriate level of functional/structural abstraction. Nonetheless, the assumption of a systematic function-structure mapping is a "working hypothesis" that, in common with other scientific fields, cannot be proved on independent grounds and is probably best evaluated by the success of the enterprise as a whole. I also consider statistical issues such as the definition of a qualitative difference and methodological issues such as the relationship between imaging and behavioural data. I finish by reviewing various objections to neuroimaging, including neophrenology, functionalism, and equipotentiality, and by observing some criticisms of current practice in the imaging

  15. The anatomy of language: contributions from functional neuroimaging

    PubMed Central

    PRICE, CATHY J.

    2000-01-01

    This article illustrates how functional neuroimaging can be used to test the validity of neurological and cognitive models of language. Three models of language are described: the 19th Century neurological model which describes both the anatomy and cognitive components of auditory and visual word processing, and 2 20th Century cognitive models that are not constrained by anatomy but emphasise 2 different routes to reading that are not present in the neurological model. A series of functional imaging studies are then presented which show that, as predicted by the 19th Century neurologists, auditory and visual word repetition engage the left posterior superior temporal and posterior inferior frontal cortices. More specifically, the roles Wernicke and Broca assigned to these regions lie respectively in the posterior superior temporal sulcus and the anterior insula. In addition, a region in the left posterior inferior temporal cortex is activated for word retrieval, thereby providing a second route to reading, as predicted by the 20th Century cognitive models. This region and its function may have been missed by the 19th Century neurologists because selective damage is rare. The angular gyrus, previously linked to the visual word form system, is shown to be part of a distributed semantic system that can be accessed by objects and faces as well as speech. Other components of the semantic system include several regions in the inferior and middle temporal lobes. From these functional imaging results, a new anatomically constrained model of word processing is proposed which reconciles the anatomical ambitions of the 19th Century neurologists and the cognitive finesse of the 20th Century cognitive models. The review focuses on single word processing and does not attempt to discuss how words are combined to generate sentences or how several languages are learned and interchanged. Progress in unravelling these and other related issues will depend on the integration of

  16. Methods for identifying subject-specific abnormalities in neuroimaging data.

    PubMed

    Mayer, Andrew R; Bedrick, Edward J; Ling, Josef M; Toulouse, Trent; Dodd, Andrew

    2014-11-01

    Algorithms that are capable of capturing subject-specific abnormalities (SSA) in neuroimaging data have long been an area of focus for diverse neuropsychiatric conditions such as multiple sclerosis, schizophrenia, and traumatic brain injury. Several algorithms have been proposed that define SSA in patients (i.e., comparison group) relative to image intensity levels derived from healthy controls (HC) (i.e., reference group) based on extreme values. However, the assumptions underlying these approaches have not always been fully validated, and may be dependent on the statistical distributions of the transformed data. The current study evaluated variations of two commonly used techniques ("pothole" method and standardization with an independent reference group) for identifying SSA using simulated data (derived from normal, t and chi-square distributions) and fractional anisotropy maps derived from 50 HC. Results indicated substantial group-wise bias in the estimation of extreme data points using the pothole method, with the degree of bias being inversely related to sample size. Statistical theory was utilized to develop a distribution-corrected z-score (DisCo-Z) threshold, with additional simulations demonstrating elimination of the bias and a more consistent estimation of extremes based on expected distributional properties. Data from previously published studies examining SSA in mild traumatic brain injury were then re-analyzed using the DisCo-Z method, with results confirming the evidence of group-wise bias. We conclude that the benefits of identifying SSA in neuropsychiatric research are substantial, but that proposed SSA approaches require careful implementation under the different distributional properties that characterize neuroimaging data. PMID:24931496

  17. Neural correlates of the LSD experience revealed by multimodal neuroimaging.

    PubMed

    Carhart-Harris, Robin L; Muthukumaraswamy, Suresh; Roseman, Leor; Kaelen, Mendel; Droog, Wouter; Murphy, Kevin; Tagliazucchi, Enzo; Schenberg, Eduardo E; Nest, Timothy; Orban, Csaba; Leech, Robert; Williams, Luke T; Williams, Tim M; Bolstridge, Mark; Sessa, Ben; McGonigle, John; Sereno, Martin I; Nichols, David; Hellyer, Peter J; Hobden, Peter; Evans, John; Singh, Krish D; Wise, Richard G; Curran, H Valerie; Feilding, Amanda; Nutt, David J

    2016-04-26

    Lysergic acid diethylamide (LSD) is the prototypical psychedelic drug, but its effects on the human brain have never been studied before with modern neuroimaging. Here, three complementary neuroimaging techniques: arterial spin labeling (ASL), blood oxygen level-dependent (BOLD) measures, and magnetoencephalography (MEG), implemented during resting state conditions, revealed marked changes in brain activity after LSD that correlated strongly with its characteristic psychological effects. Increased visual cortex cerebral blood flow (CBF), decreased visual cortex alpha power, and a greatly expanded primary visual cortex (V1) functional connectivity profile correlated strongly with ratings of visual hallucinations, implying that intrinsic brain activity exerts greater influence on visual processing in the psychedelic state, thereby defining its hallucinatory quality. LSD's marked effects on the visual cortex did not significantly correlate with the drug's other characteristic effects on consciousness, however. Rather, decreased connectivity between the parahippocampus and retrosplenial cortex (RSC) correlated strongly with ratings of "ego-dissolution" and "altered meaning," implying the importance of this particular circuit for the maintenance of "self" or "ego" and its processing of "meaning." Strong relationships were also found between the different imaging metrics, enabling firmer inferences to be made about their functional significance. This uniquely comprehensive examination of the LSD state represents an important advance in scientific research with psychedelic drugs at a time of growing interest in their scientific and therapeutic value. The present results contribute important new insights into the characteristic hallucinatory and consciousness-altering properties of psychedelics that inform on how they can model certain pathological states and potentially treat others. PMID:27071089

  18. Neural correlates of the LSD experience revealed by multimodal neuroimaging.

    PubMed

    Carhart-Harris, Robin L; Muthukumaraswamy, Suresh; Roseman, Leor; Kaelen, Mendel; Droog, Wouter; Murphy, Kevin; Tagliazucchi, Enzo; Schenberg, Eduardo E; Nest, Timothy; Orban, Csaba; Leech, Robert; Williams, Luke T; Williams, Tim M; Bolstridge, Mark; Sessa, Ben; McGonigle, John; Sereno, Martin I; Nichols, David; Hellyer, Peter J; Hobden, Peter; Evans, John; Singh, Krish D; Wise, Richard G; Curran, H Valerie; Feilding, Amanda; Nutt, David J

    2016-04-26

    Lysergic acid diethylamide (LSD) is the prototypical psychedelic drug, but its effects on the human brain have never been studied before with modern neuroimaging. Here, three complementary neuroimaging techniques: arterial spin labeling (ASL), blood oxygen level-dependent (BOLD) measures, and magnetoencephalography (MEG), implemented during resting state conditions, revealed marked changes in brain activity after LSD that correlated strongly with its characteristic psychological effects. Increased visual cortex cerebral blood flow (CBF), decreased visual cortex alpha power, and a greatly expanded primary visual cortex (V1) functional connectivity profile correlated strongly with ratings of visual hallucinations, implying that intrinsic brain activity exerts greater influence on visual processing in the psychedelic state, thereby defining its hallucinatory quality. LSD's marked effects on the visual cortex did not significantly correlate with the drug's other characteristic effects on consciousness, however. Rather, decreased connectivity between the parahippocampus and retrosplenial cortex (RSC) correlated strongly with ratings of "ego-dissolution" and "altered meaning," implying the importance of this particular circuit for the maintenance of "self" or "ego" and its processing of "meaning." Strong relationships were also found between the different imaging metrics, enabling firmer inferences to be made about their functional significance. This uniquely comprehensive examination of the LSD state represents an important advance in scientific research with psychedelic drugs at a time of growing interest in their scientific and therapeutic value. The present results contribute important new insights into the characteristic hallucinatory and consciousness-altering properties of psychedelics that inform on how they can model certain pathological states and potentially treat others.

  19. Neural correlates of the LSD experience revealed by multimodal neuroimaging

    PubMed Central

    Carhart-Harris, Robin L.; Muthukumaraswamy, Suresh; Roseman, Leor; Kaelen, Mendel; Droog, Wouter; Murphy, Kevin; Tagliazucchi, Enzo; Schenberg, Eduardo E.; Nest, Timothy; Orban, Csaba; Leech, Robert; Williams, Luke T.; Williams, Tim M.; Bolstridge, Mark; Sessa, Ben; McGonigle, John; Sereno, Martin I.; Nichols, David; Hobden, Peter; Evans, John; Singh, Krish D.; Wise, Richard G.; Curran, H. Valerie; Feilding, Amanda; Nutt, David J.

    2016-01-01

    Lysergic acid diethylamide (LSD) is the prototypical psychedelic drug, but its effects on the human brain have never been studied before with modern neuroimaging. Here, three complementary neuroimaging techniques: arterial spin labeling (ASL), blood oxygen level-dependent (BOLD) measures, and magnetoencephalography (MEG), implemented during resting state conditions, revealed marked changes in brain activity after LSD that correlated strongly with its characteristic psychological effects. Increased visual cortex cerebral blood flow (CBF), decreased visual cortex alpha power, and a greatly expanded primary visual cortex (V1) functional connectivity profile correlated strongly with ratings of visual hallucinations, implying that intrinsic brain activity exerts greater influence on visual processing in the psychedelic state, thereby defining its hallucinatory quality. LSD’s marked effects on the visual cortex did not significantly correlate with the drug’s other characteristic effects on consciousness, however. Rather, decreased connectivity between the parahippocampus and retrosplenial cortex (RSC) correlated strongly with ratings of “ego-dissolution” and “altered meaning,” implying the importance of this particular circuit for the maintenance of “self” or “ego” and its processing of “meaning.” Strong relationships were also found between the different imaging metrics, enabling firmer inferences to be made about their functional significance. This uniquely comprehensive examination of the LSD state represents an important advance in scientific research with psychedelic drugs at a time of growing interest in their scientific and therapeutic value. The present results contribute important new insights into the characteristic hallucinatory and consciousness-altering properties of psychedelics that inform on how they can model certain pathological states and potentially treat others. PMID:27071089

  20. Two Virasoro symmetries in stringy warped AdS3

    NASA Astrophysics Data System (ADS)

    Compère, Geoffrey; Guica, Monica; Rodriguez, Maria J.

    2014-12-01

    We study three-dimensional consistent truncations of type IIB supergravity which admit warped AdS3 solutions. These theories contain subsectors that have no bulk dynamics. We show that the symplectic form for these theories, when restricted to the non-dynamical subsectors, equals the symplectic form for pure Einstein gravity in AdS3. Consequently, for each consistent choice of boundary conditions in AdS3, we can define a consistent phase space in warped AdS3 with identical conserved charges. This way, we easily obtain a Virasoro × Virasoro asymptotic symmetry algebra in warped AdS3; two different types of Virasoro × Kač-Moody symmetries are also consistent alternatives.

  1. The Road Ahead to Cure Alzheimer’s Disease: Development of Biological Markers and Neuroimaging Methods for Prevention Trials Across all Stages and Target Populations

    PubMed Central

    Cavedo, E.; Lista, S.; Khachaturian, Z.; Aisen, P.; Amouyel, P.; Herholz, K.; Jack, C.R.; Sperling, R.; Cummings, J.; Blennow, K.; O’Bryant, S.; Frisoni, G.B.; Khachaturian, A.; Kivipelto, M.; Klunk, W.; Broich, K.; Andrieu, S.; de Schotten, M. Thiebaut; Mangin, J.-F.; Lammertsma, A.A.; Johnson, K.; Teipel, S.; Drzezga, A.; Bokde, A.; Colliot, O.; Bakardjian, H.; Zetterberg, H.; Dubois, B.; Vellas, B.; Schneider, L.S.; Hampel, H.

    2015-01-01

    Alzheimer’s disease (AD) is a slowly progressing non-linear dynamic brain disease in which pathophysiological abnormalities, detectable in vivo by biological markers, precede overt clinical symptoms by many years to decades. Use of these biomarkers for the detection of early and preclinical AD has become of central importance following publication of two international expert working group’s revised criteria for the diagnosis of AD dementia, mild cognitive impairment (MCI) due to AD, prodromal AD and preclinical AD. As a consequence of matured research evidence six AD biomarkers are sufficiently validated and partly qualified to be incorporated into operationalized clinical diagnostic criteria and use in primary and secondary prevention trials. These biomarkers fall into two molecular categories: biomarkers of amyloid-beta (Aβ) deposition and plaque formation as well as of tau-protein related hyperphosphorylation and neurodegeneration. Three of the six gold-standard (“core feasible) biomarkers are neuroimaging measures and three are cerebrospinal fluid (CSF) analytes. CSF Aβ1-42 (Aβ1-42), also expressed as Aβ1-42 : Aβ1-40 ratio, T-tau, and P-tau Thr181 & Thr231 proteins have proven diagnostic accuracy and risk enhancement in prodromal MCI and AD dementia. Conversely, having all three biomarkers in the normal range rules out AD. Intermediate conditions require further patient follow-up. Magnetic resonance imaging (MRI) at increasing field strength and resolution allows detecting the evolution of distinct types of structural and functional abnormality pattern throughout early to late AD stages. Anatomical or volumetric MRI is the most widely used technique and provides local and global measures of atrophy. The revised diagnostic criteria for “prodromal AD” and “mild cognitive impairment due to AD” include hippocampal atrophy (as the fourth validated biomarker), which is considered an indicator of regional neuronal injury. Advanced image analysis

  2. Leading Change, Adding Value.

    PubMed

    Evans, Nick

    2016-09-12

    Essential facts Leading Change, Adding Value is NHS England's new nursing and midwifery framework. It is designed to build on Compassion in Practice (CiP), which was published 3 years ago and set out the 6Cs: compassion, care, commitment, courage, competence and communication. CiP established the values at the heart of nursing and midwifery, while the new framework sets out how staff can help transform the health and care sectors to meet the aims of the NHS England's Five Year Forward View. PMID:27615573

  3. Targeting modulates audiences' brain and behavioral responses to safe sex video ads.

    PubMed

    Wang, An-Li; Lowen, Steven B; Shi, Zhenhao; Bissey, Bryn; Metzger, David S; Langleben, Daniel D

    2016-10-01

    Video ads promoting condom use are a key component of media campaigns to stem the HIV epidemic. Recent neuroimaging studies in the context of smoking cessation, point to personal relevance as one of the key variables that determine the effectiveness of public health messages. While minority men who have sex with men (MSM) are at the highest risk of HIV infection, most safe-sex ads feature predominantly Caucasian actors in heterosexual scenarios. We compared brain respons of 45 African American MSM to safe sex ads that were matched (i.e. 'Targeted') to participants' sexual orientation and race, and 'Untargeted' ads that were un matched for these characteristics. Ad recall, perceived 'convincingness' and attitudes towards condom use were also assessed. We found that Targeted ads were better remembered than the Untargeted ads but perceived as equally convincing. Targeted ads engaged brain regions involved in self-referential processing and memory, including the amygdala, hippocampus, temporal and medial prefrontal cortices (MPFC) and the precuneus. Connectivity between MPFC and precuneus and middle temporal gyrus was stronger when viewing Targeted ads. Our results suggest that targeting may increase cognitive processing of safe sex ads and justify further prospective studies linking brain response to media public health interventions and clinical outcomes. PMID:27217112

  4. Targeting modulates audiences' brain and behavioral responses to safe sex video ads.

    PubMed

    Wang, An-Li; Lowen, Steven B; Shi, Zhenhao; Bissey, Bryn; Metzger, David S; Langleben, Daniel D

    2016-10-01

    Video ads promoting condom use are a key component of media campaigns to stem the HIV epidemic. Recent neuroimaging studies in the context of smoking cessation, point to personal relevance as one of the key variables that determine the effectiveness of public health messages. While minority men who have sex with men (MSM) are at the highest risk of HIV infection, most safe-sex ads feature predominantly Caucasian actors in heterosexual scenarios. We compared brain respons of 45 African American MSM to safe sex ads that were matched (i.e. 'Targeted') to participants' sexual orientation and race, and 'Untargeted' ads that were un matched for these characteristics. Ad recall, perceived 'convincingness' and attitudes towards condom use were also assessed. We found that Targeted ads were better remembered than the Untargeted ads but perceived as equally convincing. Targeted ads engaged brain regions involved in self-referential processing and memory, including the amygdala, hippocampus, temporal and medial prefrontal cortices (MPFC) and the precuneus. Connectivity between MPFC and precuneus and middle temporal gyrus was stronger when viewing Targeted ads. Our results suggest that targeting may increase cognitive processing of safe sex ads and justify further prospective studies linking brain response to media public health interventions and clinical outcomes.

  5. Nonlinear realization of local symmetries of AdS space

    SciTech Connect

    Clark, T.E.; Love, S.T.; Nitta, Muneto; Veldhuis, T. ter

    2005-10-15

    Coset methods are used to construct the action describing the dynamics associated with the spontaneous breaking of the local symmetries of AdS{sub d+1} space due to the embedding of an AdS{sub d} brane. The resulting action is an SO(2,d) invariant AdS form of the Einstein-Hilbert action, which in addition to the AdS{sub d} gravitational vielbein, also includes a massive vector field localized on the brane. Its long wavelength dynamics is the same as a massive Abelian vector field coupled to gravity in AdS{sub d} space.

  6. Human African trypanosomiasis with 7-year incubation period: clinical, laboratory and neuroimaging findings.

    PubMed

    Wengert, Oliver; Kopp, Marcel; Siebert, Eberhard; Stenzel, Werner; Hegasy, Guido; Suttorp, Norbert; Stich, August; Zoller, Thomas

    2014-06-01

    Human African trypanosomiasis (HAT), also referred to as "sleeping sickness", is caused by the parasite Trypanosoma brucei. Diagnosing imported HAT outside endemic areas is difficult and diagnosis is often delayed. We report a case of imported human African trypanosomiasis caused by Trypanosoma brucei gambiense with an unusually long incubation period of at least 7 years. A 33 year old male African patient, a former resident of Cameroon, presented with a 4-month history of progressive personality changes. A few weeks before presentation the patient had first been admitted to a psychiatric ward and received antidepressant treatment, until a lumbar puncture showed pleocytosis and then antibiotic treatment for suspected neuroborreliosis was initiated. The patient continued to deteriorate during antibiotic treatment and became increasingly lethargic. Under antiparasitic and anti-inflammatory treatment, the condition of the patient gradually improved over the following months and he recovered completely after 24 months of follow-up. This well-documented case illustrates typical difficulties in establishing the correct diagnosis outside endemic areas and provides an overview of typical clinical, neuropathological and neuroimaging findings in T. b. gambiense trypanosomiasis, guiding the clinician in establishing the correct diagnosis in this rare disease.

  7. Neuroimaging Studies of Normal Brain Development and Their Relevance for Understanding Childhood Neuropsychiatric Disorders

    ERIC Educational Resources Information Center

    Marsh, Rachel; Gerber, Andrew J.; Peterson, Bradley S.

    2008-01-01

    Neuroimaging findings which identify normal brain development trajectories are presented. Results show that early brain development begins with the neural tube formation and ends with myelintation. How disturbances in brain development patterns are related to childhood psychiatric disorders is examined.

  8. How can neuroimaging facilitate the diagnosis and stratification of patients with psychosis?

    PubMed Central

    Kempton, Matthew J.; McGuire, Philip

    2015-01-01

    Early diagnosis and treatment of patients with psychosis are associated with improved outcome in terms of future functioning, symptoms and treatment response. Identifying neuroimaging biomarkers for illness onset and treatment response would lead to immediate clinical benefits. In this review we discuss if neuroimaging may be utilised to diagnose patients with psychosis, predict those who will develop the illness in those at high risk, and stratify patients. State-of-the-art developments in the field are critically examined including multicentre studies, longitudinal designs, multimodal imaging and machine learning as well as some of the challenges in utilising future neuroimaging biomarkers in clinical trials. As many of these developments are already being applied in neuroimaging studies of Alzheimer׳s disease, we discuss what lessons have been learned from this field and how they may be applied to research in psychosis. PMID:25092428

  9. Fooled by the brain: re-examining the influence of neuroimages.

    PubMed

    Schweitzer, N J; Baker, D A; Risko, Evan F

    2013-12-01

    A series of highly-cited experiments published in 2008 demonstrated a biasing effect of neuroimages on lay perceptions of scientific research. More recent work, however, has questioned this bias, particularly within legal contexts in which neuroscientific evidence is proffered by one of the parties. The present research moves away from the legal framework and describes five experiments that re-examine this effect. Experiments 1 through 4 present conceptual and direct replications of some of the original 2008 experiments, and find no evidence of a neuroimage bias. A fifth experiment is reported that confirms that, when laypeople are allowed multiple points of reference (e.g., when directly comparing neuroimagery to other graphical depictions of neurological data), a neuroimage bias can be observed. Together these results suggest that, under the right conditions, a neuroimage might be able to bias judgments of scientific information, but the scope of this effect may be limited to certain contexts.

  10. Hope and doubt in the promise of neuroimaging: The case of autism spectrum disorder.

    PubMed

    Bertorelli, Thomas Eugene

    2016-09-01

    Although neuroimaging is currently not a component of the diagnostic process for autism spectrum disorders, some scientists hail these technologies for their promise to one day replace behaviorally based psychiatric diagnostic techniques. This article examines how psychiatrists understand the potential use of neuroimaging technologies within the context of clinical practice. Drawing on 10 semi-structured interviews with child and adolescent psychiatrists, I describe the hope and doubt that comprise their discourse of ambivalence. This analysis demonstrates that the uses and meanings of neuroimaging technologies are rearticulated in ongoing debates in the field of psychiatry regarding the role of the biopsychiatric model in the diagnosis and treatment of mental illness. This study highlights issues surrounding the perceived biopsychiatric focus of neuroimaging technologies within clinical practice, concerns regarding misdirected research attention, and the ways in which understandings of future utility mediate perceptions of technological utility. PMID:27474754

  11. Dressing phases of AdS3/CFT2

    NASA Astrophysics Data System (ADS)

    Borsato, Riccardo; Ohlsson Sax, Olof; Sfondrini, Alessandro; Stefański, Bogdan, Jr.; Torrielli, Alessandro

    2013-09-01

    We determine the all-loop dressing phases of the AdS3/CFT2 integrable system related to type IIB string theory on AdS3×S3×T4 by solving the recently found crossing relations and studying their singularity structure. The two resulting phases present a novel structure with respect to the ones appearing in AdS5/CFT4 and AdS4/CFT3. In the strongly coupled regime, their leading order reduces to the universal Arutyunov-Frolov-Staudacher phase as expected. We also compute their subleading order and compare it with recent one-loop perturbative results and comment on their weak-coupling expansion.

  12. Bubbling geometries for AdS2× S2

    NASA Astrophysics Data System (ADS)

    Lunin, Oleg

    2015-10-01

    We construct BPS geometries describing normalizable excitations of AdS2×S2. All regular horizon-free solutions are parameterized by two harmonic functions in R 3 with sources along closed curves. This local structure is reminiscent of the "bubbling solutions" for the other AdS p ×S q cases, however, due to peculiar asymptotic properties of AdS2, one copy of R 3 does not cover the entire space, and we discuss the procedure for analytic continuation, which leads to a nontrivial topological structure of the new geometries. We also study supersymmetric brane probes on the new geometries, which represent the AdS2×S2 counterparts of the giant gravitons.

  13. Neuroimaging and neurocognitive correlates of aggression and violence in schizophrenia.

    PubMed

    Weiss, Elisabeth M

    2012-01-01

    Individuals diagnosed with major mental disorders such as schizophrenia are more likely to have engaged in violent behavior than mentally healthy members of the same communities. Although aggressive acts can have numerous causes, research about the underlying neurobiology of violence and aggression in schizophrenia can lead to a better understanding of the heterogeneous nature of that behavior and can assist in developing new treatment strategies. The purpose of this paper is to review the recent literature and discuss some of the neurobiological correlates of aggression and violence. The focus will be on schizophrenia, and the results of neuroimaging and neuropsychological studies that have directly investigated brain functioning and/or structure in aggressive and violent samples will be discussed as well as other domains that might predispose to aggression and violence such as deficits in responding to the emotional expressions of others, impulsivity, and psychopathological symptoms. Finally gender differences regarding aggression and violence are discussed. In this context several methodological and conceptional issues that limited the comparison of these studies will be addressed. PMID:24278673

  14. Choroid plexus calcification: clinical, neuroimaging and histopathological correlations in schizophrenia.

    PubMed

    Marinescu, Ileana; Udriştoiu, I; Marinescu, D

    2013-01-01

    Schizophrenia is recognized as a psychiatric disorder that causes the most pronounced disturbances of cognition and social integration. In the etiopathogenesis of the disease, genetic, neurobiological and vascular factors are involved. Functional integrity of the brain can be correlated with the integrity of the blood-brain barrier (BBB), and the dysfunction of this barrier is an indicator that suggests neurodevelopmental abnormalities, injuries of various etiologies and dysfunctions within the small vessels of the brain that disrupt the calcium homeostasis. Neuroimaging shows that in patients with poor evolution, cognitive dysfunction and therapeutic resistance, the presence of choroid plexus calcification associated with hippocampal, frontal, temporoparietal and cerebellar atrophies. Antipsychotics with high capacity to block D2 dopamine receptors (haloperidol model) can aggravate apoptotic mechanisms of the brain areas involved in cognition and disrupts the functional integrity of the BBB due to decreased of choroid plexus blood flow because of the narrowing of cerebral small vessels. Choroid plexus calcification may be a predictive indicator of poor evolution or of a neurodegenerative type. PMID:23771083

  15. Neuroimaging and Neurocognitive Correlates of Aggression and Violence in Schizophrenia

    PubMed Central

    Weiss, Elisabeth M.

    2012-01-01

    Individuals diagnosed with major mental disorders such as schizophrenia are more likely to have engaged in violent behavior than mentally healthy members of the same communities. Although aggressive acts can have numerous causes, research about the underlying neurobiology of violence and aggression in schizophrenia can lead to a better understanding of the heterogeneous nature of that behavior and can assist in developing new treatment strategies. The purpose of this paper is to review the recent literature and discuss some of the neurobiological correlates of aggression and violence. The focus will be on schizophrenia, and the results of neuroimaging and neuropsychological studies that have directly investigated brain functioning and/or structure in aggressive and violent samples will be discussed as well as other domains that might predispose to aggression and violence such as deficits in responding to the emotional expressions of others, impulsivity, and psychopathological symptoms. Finally gender differences regarding aggression and violence are discussed. In this context several methodological and conceptional issues that limited the comparison of these studies will be addressed. PMID:24278673

  16. Age of onset of schizophrenia: perspectives from structural neuroimaging studies.

    PubMed

    Gogtay, Nitin; Vyas, Nora S; Testa, Renee; Wood, Stephen J; Pantelis, Christos

    2011-05-01

    Many of the major neuropsychiatric illnesses, including schizophrenia, have a typical age of onset in late adolescence. Late adolescence may reflect a critical period in brain development making it particularly vulnerable for the onset of psychopathology. Neuroimaging studies that focus on this age range may provide unique insights into the onset and course of psychosis. In this review, we examine the evidence from 2 unique longitudinal cohorts that span the ages from early childhood through young adulthood; a study of childhood-onset schizophrenia where patients and siblings are followed from ages 6 through to their early twenties, and an ultra-high risk study where subjects (mean age of 19 years) are studied before and after the onset of psychosis. From the available evidence, we make an argument that subtle, regionally specific, and genetically influenced alterations during developmental age windows influence the course of psychosis and the resultant brain phenotype. The importance of examining trajectories of development and the need for future combined approaches, using multimodal imaging together with molecular studies is discussed. PMID:21505117

  17. The glutamate hypothesis of schizophrenia: neuroimaging and drug development.

    PubMed

    Egerton, Alice; Stone, James M

    2012-06-01

    Over the last 50 years, evidence for central involvement of glutamatergic neurotransmission in the pathophysiology of schizophrenia has accumulated. Recent advances in neuroimaging technology now allow several components of glutamatergic neurotransmission to be assessed in the living human brain. Positron emission tomography (PET) or single photon emission tomography (SPET) in combination with select radiotracers allows visualization of glutamatergic receptors in vivo, and magnetic resonance (MR) - based techniques allow mapping of the effects of glutamatergic agents on regional brain activation, and the measurement of regional glutamate concentrations. These imaging studies have provided evidence for regional glutamatergic abnormalities in psychosis, and are beginning to describe both the evolution of these abnormalities over the course of the illness and their response to therapeutic intervention. In parallel, advances in small animal imaging and the development of animal models have provided a platform to explore the neuropathological consequences of glutamatergic abnormality, and the potential antipsychotic efficacy of novel compounds. The molecular diversity of the glutamatergic system has driven the design of several compounds targeting aspects of glutamatergic transmission, and clinical trials have yielded encouraging results. Here, we review the contribution of imaging studies to date in understanding glutamatergic abnormalities in psychosis, and discuss the potential of new glutamatergic compounds for treatment of the disorder. PMID:22283750

  18. Neurocognition and neuroimaging of persistent negative symptoms of schizophrenia.

    PubMed

    Hovington, Cindy L; Lepage, Martin

    2012-01-01

    Negative symptoms have been a conundrum to researchers and clinicians alike since having first been identified by Bleuler and Kraepelin. The term 'negative symptoms' has been scrutinized with regards to what it encompasses. Negative symptomatology has been categorized into distinct subdomains, including primary symptoms, secondary symptoms, deficit syndrome and, more recently, persistent negative symptoms (PNS). Although there have been some theories put forward with regards to negative symptoms, there are still discordant findings regarding PNS. Thus, this article aimed to review the structural, functional and cognitive correlates of PNS in an attempt to better understand these specific negative symptoms in schizophrenia. According to the reviewed literature, deficit syndrome appears to have similar neurocognitive and structural deficits as PNS; however, some minor distinctions may suggest that PNS are a separate subtype of negative symptoms. White matter decrements in the frontal lobe and gray matter reductions in the temporal lobe may be related more specifically to PNS. Furthermore, unlike deficit syndrome, structural abnormalities in the frontal and temporal lobe also appear to be related to PNS in patients with first-episode schizophrenia. Cognitive domains, such as memory, are impaired and appear to be predominantly related to PNS. Hence, PNS do appear to have neuroimaging and neurocognitive correlates and warrant further research. PMID:22243045

  19. Functional neuroimaging of acute oculomotor deficits in concussed athletes.

    PubMed

    Johnson, Brian; Zhang, Kai; Hallett, Mark; Slobounov, Semyon

    2015-09-01

    In the pursuit to better understand the neural underpinnings of oculomotor deficits following concussion we performed a battery of oculomotor tests while performing simultaneous functional magnetic resonance imaging (fMRI). Based on the increasing evidence that concussion can disrupt multiple brain functional networks, including the oculomotor control networks, a series of classic saccadic and smooth pursuit tasks were implemented. Nine concussed athletes were tested within seven days of injury along with nine age and sex matched healthy normal volunteers. Both behavioral and fMRI data revealed differential results between the concussed and normal volunteer groups. Concussed subjects displayed longer latency time in the saccadic tasks, worse position errors, and fewer numbers of self-paced saccades compared to normal volunteer subjects. Furthermore, the concussed group showed recruitment of additional brain regions and larger activation sites as evidenced by fMRI. As a potential diagnostic and management tool for concussion, oculomotor testing shows promise, and here we try to understand the reasons for this disrupted performance with the aide of advanced neuroimaging tools. PMID:25179246

  20. Neuroimaging studies on recognition of personally familiar people.

    PubMed

    Sugiura, Motoaki

    2014-01-01

    From an evolutionary viewpoint, readiness to engage in appropriate behavior toward a recognized person seems to be inherent in the human brain. In support of this hypothesis, functional neuroimaging studies have demonstrated activation in regions relevant to relationship-appropriate behavior during the recognition of personally familiar (PF) people. Recognition of friends and colleagues activates regions involved in real-time communication, including the regions for inference about the other's mental state, autobiographical memory retrieval, and self-referential processes. Recognition of people related by romantic love, maternal love, and lost love induces activation in regions involved in motivational, reward, and affective processes, reflecting behavioral readiness for mating, caretaking, and yearning, respectively. The involvement of motor-associated cortices during recognition of a personal enemy may reflect readiness for attack or defense. Self-recognition in a body-related modality uniquely activates sensory and motor association cortices reflecting the sensorimotor origin of the bodily self-concept, with social cognitive processes being suppressed or context dependent. Issues and future directions are also discussed. PMID:24389212

  1. Neurodegeneration with brain iron accumulation - clinical syndromes and neuroimaging.

    PubMed

    Schipper, Hyman M

    2012-03-01

    Iron participates in a wide array of cellular functions and is essential for normal neural development and physiology. However, if inappropriately managed, the transition metal is capable of generating neurotoxic reactive oxygen species. A number of hereditary conditions perturb body iron homeostasis and some, collectively referred to as neurodegeneration with brain iron accumulation (NBIA), promote pathological deposition of the metal predominantly or exclusively within the central nervous system (CNS). In this article, we discuss seven NBIA disorders with emphasis on the clinical syndromes and neuroimaging. The latter primarily entails magnetic resonance scanning using iron-sensitive sequences. The conditions considered are Friedreich ataxia (FA), pantothenate kinase 2-associated neurodegeneration (PKAN), PLA2G6-associated neurodegeneration (PLAN), FA2H-associated neurodegeneration (FAHN), Kufor-Rakeb disease (KRD), aceruloplasminemia, and neuroferritinopathy. An approach to differential diagnosis and the status of iron chelation therapy for several of these entities are presented. This article is part of a Special Issue entitled: Imaging Brain Aging and Neurodegenerative disease.

  2. Bootstrap Enhanced Penalized Regression for Variable Selection with Neuroimaging Data.

    PubMed

    Abram, Samantha V; Helwig, Nathaniel E; Moodie, Craig A; DeYoung, Colin G; MacDonald, Angus W; Waller, Niels G

    2016-01-01

    Recent advances in fMRI research highlight the use of multivariate methods for examining whole-brain connectivity. Complementary data-driven methods are needed for determining the subset of predictors related to individual differences. Although commonly used for this purpose, ordinary least squares (OLS) regression may not be ideal due to multi-collinearity and over-fitting issues. Penalized regression is a promising and underutilized alternative to OLS regression. In this paper, we propose a nonparametric bootstrap quantile (QNT) approach for variable selection with neuroimaging data. We use real and simulated data, as well as annotated R code, to demonstrate the benefits of our proposed method. Our results illustrate the practical potential of our proposed bootstrap QNT approach. Our real data example demonstrates how our method can be used to relate individual differences in neural network connectivity with an externalizing personality measure. Also, our simulation results reveal that the QNT method is effective under a variety of data conditions. Penalized regression yields more stable estimates and sparser models than OLS regression in situations with large numbers of highly correlated neural predictors. Our results demonstrate that penalized regression is a promising method for examining associations between neural predictors and clinically relevant traits or behaviors. These findings have important implications for the growing field of functional connectivity research, where multivariate methods produce numerous, highly correlated brain networks. PMID:27516732

  3. [The neurobiological dimension of meditation--results from neuroimaging studies].

    PubMed

    Neumann, Norbert-Ullrich; Frasch, Karel

    2006-12-01

    Meditation in general can be understood as a state of complete and unintentional silent and motionless concentration on an activity, an item or an idea. Subjectively, meditative experience is said to be fundamentally different from "normal" mental states and is characterized by terms like timelessness, boundlessness and lack of self-experience. In recent years, several fMRI- and PET-studies about meditation which are presented in this paper have been published. Due to different methods, especially different meditation types, the results are hardly comparable. Nevertheless, the data suggest the hypothesis of a "special" neural activity during meditative states being different from that during calm alertness. Main findings were increased activation in frontal, prefrontal and cingulate areas which may represent the mental state of altered self-experience. In the present studies, a considerable lack of scientific standards has to be stated making it of just casuistic value. Today's improved neurobiological examination methods - especially neuroimaging techniques - may contribute to enlighten the phenomenon of qualitatively different states of consciousness.

  4. Hemimegalencephaly: Clinical, EEG, neuroimaging, and IMP-SPECT correlation

    SciTech Connect

    Konkol, R.J.; Maister, B.H.; Wells, R.G.; Sty, J.R. )

    1990-11-01

    Iofetamine-single photon emission computed tomography (IMP-SPECT) was performed on 2 girls (5 1/2 and 6 years of age) with histories of intractable seizures, developmental delay, and unilateral hemiparesis secondary to hemimegalencephaly. Electroencephalography (EEG) revealed frequent focal discharges in 1 patient, while a nearly continuous burst suppression pattern over the malformed hemisphere was recorded in the other. IMP-SPECT demonstrated a good correlation with neuroimaging studies. In spite of the different EEG patterns, which had been proposed to predict contrasting clinical outcomes, both IMP-SPECT scans disclosed a similar decrease in tracer uptake in the malformed hemisphere. These results are consistent with the pattern of decreased tracer uptake found in other interictal studies of focal seizures without cerebral malformations. In view of recent recommendations for hemispherectomy in these patients, we suggest that the IMP-SPECT scan be used to compliment EEG as a method to define the extent of abnormality which may be more relevant to long-term prognosis than EEG alone.

  5. Vestibular migraine pathophysiology: insights from structural and functional neuroimaging.

    PubMed

    Tedeschi, Gioacchino; Russo, Antonio; Conte, Francesca; Laura, Marcuccio; Tessitore, Alessandro

    2015-05-01

    Vestibular migraine (VM) has been increasingly recognized as a frequent cause of episodic vertigo, affecting up to 1 % of the general population, with female preponderance. Recently, both the Bárány Society and the Migraine Classification Subcommittee of the International Headache Society have proposed original diagnostic criteria for VM, which have been included in the recent edition of the ICHD-3 beta version. VM diagnosis implies that vestibular symptoms are present during a migraine attack, with or without headache, in the absence of objectively demonstrated interictal vestibulopathy. Nevertheless, despite a growing body of literature, there is still an ongoing debate regarding whether VM origin is principally central or peripheral. However, during the past few years, the extensive application of advanced MRI techniques has contributed to significantly improve the understanding VM pathophysiology. Functional and structural abnormalities have been detected in brain areas involved in multisensory vestibular control and central vestibular processing in patients with VM. In this brief review, we will focus on these recent neuroimaging findings.

  6. Functional neuroimaging for addiction medicine: From mechanisms to practical considerations.

    PubMed

    Ekhtiari, Hamed; Faghiri, Ashkan; Oghabian, Mohammad-Ali; Paulus, Martin P

    2016-01-01

    During last 20 years, neuroimaging with functional magnetic resonance imaging (fMRI) in people with drug addictions has introduced a wide range of quantitative biomarkers from brain's regional or network level activities during different cognitive functions. These quantitative biomarkers could be potentially used for assessment, planning, prediction, and monitoring for "addiction medicine" during screening, acute intoxication, admission to a program, completion of an acute program, admission to a long-term program, and postgraduation follow-up. In this chapter, we have briefly reviewed main neurocognitive targets for fMRI studies associated with addictive behaviors, main study types using fMRI among drug dependents, and potential applications for fMRI in addiction medicine. Main challenges and limitations for extending fMRI studies and evidences aiming at clinical applications in addiction medicine are also discussed. There is still a significant gap between available evidences from group-based fMRI studies and personalized decisions during daily practices in addiction medicine. It will be important to fill this gap with large-scale clinical trials and longitudinal studies using fMRI measures with a well-defined strategic plan for the future. PMID:26822357

  7. Age of Onset of Schizophrenia: Perspectives From Structural Neuroimaging Studies

    PubMed Central

    Gogtay, Nitin; Vyas, Nora S.; Testa, Renee; Wood, Stephen J.; Pantelis, Christos

    2011-01-01

    Many of the major neuropsychiatric illnesses, including schizophrenia, have a typical age of onset in late adolescence. Late adolescence may reflect a critical period in brain development making it particularly vulnerable for the onset of psychopathology. Neuroimaging studies that focus on this age range may provide unique insights into the onset and course of psychosis. In this review, we examine the evidence from 2 unique longitudinal cohorts that span the ages from early childhood through young adulthood; a study of childhood-onset schizophrenia where patients and siblings are followed from ages 6 through to their early twenties, and an ultra-high risk study where subjects (mean age of 19 years) are studied before and after the onset of psychosis. From the available evidence, we make an argument that subtle, regionally specific, and genetically influenced alterations during developmental age windows influence the course of psychosis and the resultant brain phenotype. The importance of examining trajectories of development and the need for future combined approaches, using multimodal imaging together with molecular studies is discussed. PMID:21505117

  8. On the role of general system theory for functional neuroimaging

    PubMed Central

    Stephan, Klaas Enno

    2004-01-01

    One of the most important goals of neuroscience is to establish precise structure–function relationships in the brain. Since the 19th century, a major scientific endeavour has been to associate structurally distinct cortical regions with specific cognitive functions. This was traditionally accomplished by correlating microstructurally defined areas with lesion sites found in patients with specific neuropsychological symptoms. Modern neuroimaging techniques with high spatial resolution have promised an alternative approach, enabling non-invasive measurements of regionally specific changes of brain activity that are correlated with certain components of a cognitive process. Reviewing classic approaches towards brain structure–function relationships that are based on correlational approaches, this article argues that these approaches are not sufficient to provide an understanding of the operational principles of a dynamic system such as the brain but must be complemented by models based on general system theory. These models reflect the connectional structure of the system under investigation and emphasize context-dependent couplings between the system elements in terms of effective connectivity. The usefulness of system models whose parameters are fitted to measured functional imaging data for testing hypotheses about structure–function relationships in the brain and their potential for clinical applications is demonstrated by several empirical examples. PMID:15610393

  9. Neuroimaging of scuba diving injuries to the CNS.

    PubMed

    Warren, L P; Djang, W T; Moon, R E; Camporesi, E M; Sallee, D S; Anthony, D C; Massey, E W; Burger, P C; Heinz, E R

    1988-11-01

    Diving accidents related to barotrauma constitute a unique subset of ischemic insults to the CNS. Victims may demonstrate components of arterial gas embolism, which has a propensity for cerebral involvement, and/or decompression sickness, with primarily spinal cord involvement. Fourteen patients with diving-related barotrauma were studied with MR imaging of the brain and spinal cord and with CT of the brain. In four patients with presumed cerebral gas embolism, cranial MR was abnormal in three patients while CT was abnormal in only one. Twelve patients had decompression sickness and spinal cord symptoms. MR documented spinal cord abnormalities in three patients. However, scans obtained early in our study were frequently limited by technical constraints. MR of the brain is more sensitive than conventional CT scanning techniques in detecting and characterizing foci of cerebral ischemia caused by embolic barotrauma to the CNS. Although spinal MR may be less successful in the localization of spinal cord lesions related to decompression sickness, these lesions were previously undetectable by other neuroimaging methods.

  10. Neuroimaging and obesity: current knowledge and future directions

    PubMed Central

    Carnell, S.; Gibson, C.; Benson, L.; Ochner, C. N.; Geliebter, A.

    2011-01-01

    Summary Neuroimaging is becoming increasingly common in obesity research as investigators try to understand the neurological underpinnings of appetite and body weight in humans. Positron emission tomography (PET), functional magnetic resonance imaging (fMRI) and magnetic resonance imaging (MRI) studies examining responses to food intake and food cues, dopamine function and brain volume in lean vs. obese individuals are now beginning to coalesce in identifying irregularities in a range of regions implicated in reward (e.g. striatum, orbitofrontal cortex, insula), emotion and memory (e.g. amygdala, hippocampus), homeostatic regulation of intake (e.g. hypothalamus), sensory and motor processing (e.g. insula, precentral gyrus), and cognitive control and attention (e.g. prefrontal cortex, cingulate). Studies of weight change in children and adolescents, and those at high genetic risk for obesity, promise to illuminate causal processes. Studies examining specific eating behaviours (e.g. external eating, emotional eating, dietary restraint) are teaching us about the distinct neural networks that drive components of appetite, and contribute to the phenotype of body weight. Finally, innovative investigations of appetite-related hormones, including studies of abnormalities (e.g. leptin deficiency) and interventions (e.g. leptin replacement, bariatric surgery), are shedding light on the interactive relationship between gut and brain. The dynamic distributed vulnerability model of eating behaviour in obesity that we propose has scientific and practical implications. PMID:21902800

  11. A cognitive neurobiological account of deception: evidence from functional neuroimaging.

    PubMed Central

    Spence, Sean A; Hunter, Mike D; Farrow, Tom F D; Green, Russell D; Leung, David H; Hughes, Catherine J; Ganesan, Venkatasubramanian

    2004-01-01

    An organism may use misinformation, knowingly (through deception) or unknowingly (as in the case of camouflage), to gain advantage in a competitive environment. From an evolutionary perspective, greater tactical deception occurs among primates closer to humans, with larger neocortices. In humans, the onset of deceptive behaviours in childhood exhibits a developmental trajectory, which may be regarded as 'normal' in the majority and deficient among a minority with certain neurodevelopmental disorders (e.g. autism). In the human adult, deception and lying exhibit features consistent with their use of 'higher' or 'executive' brain systems. Accurate detection of deception in humans may be of particular importance in forensic practice, while an understanding of its cognitive neurobiology may have implications for models of 'theory of mind' and social cognition, and societal notions of responsibility, guilt and mitigation. In recent years, functional neuroimaging techniques (especially functional magnetic resonance imaging) have been used to study deception. Though few in number, and using very different experimental protocols, studies published in the peer-reviewed literature exhibit certain consistencies. Attempted deception is associated with activation of executive brain regions (particularly prefrontal and anterior cingulate cortices), while truthful responding has not been shown to be associated with any areas of increased activation (relative to deception). Hence, truthful responding may comprise a relative 'baseline' in human cognition and communication. The subject who lies may necessarily engage 'higher' brain centres, consistent with a purpose or intention (to deceive). While the principle of executive control during deception remains plausible, its precise anatomy awaits elucidation. PMID:15590616

  12. Developing High-Density Diffuse Optical Tomography for Neuroimaging

    NASA Astrophysics Data System (ADS)

    White, Brian Richard

    Clinicians who care for brain-injured patients and premature infants desire a bedside monitor of brain function. A decade ago, there was hope that optical imaging would be able to fill this role, as it combined fMRI's ability to construct cortical maps with EEG's portable, cap-based systems. However, early optical systems had poor imaging performance, and the momentum for the technique slowed. In our lab, we develop diffuse optical tomography (DOT), which is a more advanced method of performing optical imaging. My research has been to pioneer the in vivo use of DOT for advanced neuroimaging by (1) quantifying the advantages of DOT through both in silico simulation and in vivo performance metrics, (2) restoring confidence in the technique with the first retinotopic mapping of the visual cortex (a benchmark for fMRI and PET), and (3) creating concepts and methods for the clinical translation of DOT. Hospitalized patients are unable to perform complicated neurological tasks, which has motivated us to develop the first DOT methods for resting-state brain mapping with functional connectivity. Finally, in collaboration with neonatologists, I have extended these methods with proof-of-principle imaging of brain-injured premature infants. This work establishes DOT's improvements in imaging performance and readies it for multiple clinical and research roles.

  13. Bootstrap Enhanced Penalized Regression for Variable Selection with Neuroimaging Data

    PubMed Central

    Abram, Samantha V.; Helwig, Nathaniel E.; Moodie, Craig A.; DeYoung, Colin G.; MacDonald, Angus W.; Waller, Niels G.

    2016-01-01

    Recent advances in fMRI research highlight the use of multivariate methods for examining whole-brain connectivity. Complementary data-driven methods are needed for determining the subset of predictors related to individual differences. Although commonly used for this purpose, ordinary least squares (OLS) regression may not be ideal due to multi-collinearity and over-fitting issues. Penalized regression is a promising and underutilized alternative to OLS regression. In this paper, we propose a nonparametric bootstrap quantile (QNT) approach for variable selection with neuroimaging data. We use real and simulated data, as well as annotated R code, to demonstrate the benefits of our proposed method. Our results illustrate the practical potential of our proposed bootstrap QNT approach. Our real data example demonstrates how our method can be used to relate individual differences in neural network connectivity with an externalizing personality measure. Also, our simulation results reveal that the QNT method is effective under a variety of data conditions. Penalized regression yields more stable estimates and sparser models than OLS regression in situations with large numbers of highly correlated neural predictors. Our results demonstrate that penalized regression is a promising method for examining associations between neural predictors and clinically relevant traits or behaviors. These findings have important implications for the growing field of functional connectivity research, where multivariate methods produce numerous, highly correlated brain networks. PMID:27516732

  14. Neuroimaging techniques for memory detection: scientific, ethical, and legal issues.

    PubMed

    Meegan, Daniel V

    2008-01-01

    There is considerable interest in the use of neuroimaging techniques for forensic purposes. Memory detection techniques, including the well-publicized Brain Fingerprinting technique (Brain Fingerprinting Laboratories, Inc., Seattle WA), exploit the fact that the brain responds differently to sensory stimuli to which it has been exposed before. When a stimulus is specifically associated with a crime, the resulting brain activity should differentiate between someone who was present at the crime and someone who was not. This article reviews the scientific literature on three such techniques: priming, old/new, and P300 effects. The forensic potential of these techniques is evaluated based on four criteria: specificity, automaticity, encoding flexibility, and longevity. This article concludes that none of the techniques are devoid of forensic potential, although much research is yet to be done. Ethical issues, including rights to privacy and against self-incrimination, are discussed. A discussion of legal issues concludes that current memory detection techniques do not yet meet United States standards of legal admissibility.

  15. Bootstrap Enhanced Penalized Regression for Variable Selection with Neuroimaging Data.

    PubMed

    Abram, Samantha V; Helwig, Nathaniel E; Moodie, Craig A; DeYoung, Colin G; MacDonald, Angus W; Waller, Niels G

    2016-01-01

    Recent advances in fMRI research highlight the use of multivariate methods for examining whole-brain connectivity. Complementary data-driven methods are needed for determining the subset of predictors related to individual differences. Although commonly used for this purpose, ordinary least squares (OLS) regression may not be ideal due to multi-collinearity and over-fitting issues. Penalized regression is a promising and underutilized alternative to OLS regression. In this paper, we propose a nonparametric bootstrap quantile (QNT) approach for variable selection with neuroimaging data. We use real and simulated data, as well as annotated R code, to demonstrate the benefits of our proposed method. Our results illustrate the practical potential of our proposed bootstrap QNT approach. Our real data example demonstrates how our method can be used to relate individual differences in neural network connectivity with an externalizing personality measure. Also, our simulation results reveal that the QNT method is effective under a variety of data conditions. Penalized regression yields more stable estimates and sparser models than OLS regression in situations with large numbers of highly correlated neural predictors. Our results demonstrate that penalized regression is a promising method for examining associations between neural predictors and clinically relevant traits or behaviors. These findings have important implications for the growing field of functional connectivity research, where multivariate methods produce numerous, highly correlated brain networks.

  16. Decoding Continuous Variables from Neuroimaging Data: Basic and Clinical Applications

    PubMed Central

    Cohen, Jessica R.; Asarnow, Robert F.; Sabb, Fred W.; Bilder, Robert M.; Bookheimer, Susan Y.; Knowlton, Barbara J.; Poldrack, Russell A.

    2011-01-01

    The application of statistical machine learning techniques to neuroimaging data has allowed researchers to decode the cognitive and disease states of participants. The majority of studies using these techniques have focused on pattern classification to decode the type of object a participant is viewing, the type of cognitive task a participant is completing, or the disease state of a participant's brain. However, an emerging body of literature is extending these classification studies to the decoding of values of continuous variables (such as age, cognitive characteristics, or neuropsychological state) using high-dimensional regression methods. This review details the methods used in such analyses and describes recent results. We provide specific examples of studies which have used this approach to answer novel questions about age and cognitive and disease states. We conclude that while there is still much to learn about these methods, they provide useful information about the relationship between neural activity and age, cognitive state, and disease state, which could not have been obtained using traditional univariate analytical methods. PMID:21720520

  17. Chronic methamphetamine abuse and corticostriatal deficits revealed by neuroimaging.

    PubMed

    London, Edythe D; Kohno, Milky; Morales, Angelica M; Ballard, Michael E

    2015-12-01

    Despite aggressive efforts to contain it, methamphetamine use disorder continues to be major public health problem; and with generic behavioral therapies still the mainstay of treatment for methamphetamine abuse, rates of attrition and relapse remain high. This review summarizes the findings of structural, molecular, and functional neuroimaging studies of methamphetamine abusers, focusing on cortical and striatal abnormalities and their potential contributions to cognitive and behavioral phenotypes that can serve to promote compulsive drug use. These studies indicate that individuals with a history of chronic methamphetamine abuse often display several signs of corticostriatal dysfunction, including abnormal gray- and white-matter integrity, monoamine neurotransmitter system deficiencies, neuroinflammation, poor neuronal integrity, and aberrant patterns of brain connectivity and function, both when engaged in cognitive tasks and at rest. More importantly, many of these neural abnormalities were found to be linked with certain addiction-related phenotypes that may influence treatment response (e.g., poor self-control, cognitive inflexibility, maladaptive decision-making), raising the possibility that they may represent novel therapeutic targets.

  18. Applying neuroimaging to detect neuroanatomical dysconnectivity in psychosis.

    PubMed

    O'Donoghue, S; Cannon, D M; Perlini, C; Brambilla, P; McDonald, C

    2015-08-01

    This editorial discusses the application of a novel brain imaging analysis technique in the assessment of neuroanatomical dysconnectivity in psychotic illnesses. There has long been a clinical interest in psychosis as a disconnection syndrome. In recent years graph theory metrics have been applied to functional and structural imaging datasets to derive measures of brain connectivity, which represent the efficiency of brain networks. These metrics can be derived from structural neuroimaging datasets acquired using diffusion imaging whereby cortical structures are parcellated into nodes and white matter tracts represent edges connecting these nodes. Furthermore neuroanatomical measures of connectivity may be decoupled from measures of physiological connectivity as assessed using functional imaging, underpinning the need for multi-modal imaging approaches to probe brain networks. Studies to date have reported a number of structural brain connectivity abnormalities associated with schizophrenia that carry potential as illness biomarkers. Structural connectivity abnormalities have also been reported in well patients with bipolar disorder and in unaffected relatives of patients with schizophrenia. Such connectivity metrics may represent clinically relevant biomarkers in studies employing a longitudinal design of illness course in psychosis. PMID:25672250

  19. Neuroimaging of tic genesis: Present status and future perspectives.

    PubMed

    Worbe, Yulia; Lehericy, Stephane; Hartmann, Andreas

    2015-08-01

    Tics are hyperkinetic movements that are distinctive by their variety in semiology and duration and by their ability to be modulated by cognitive control. They are the hallmark of Gilles de la Tourette syndrome. Despite the variety of clinical presentations in this syndrome, dysfunction of cortico-striato-pallido-thalamo-cortical networks is suggested as a core pathophysiological mechanism. We review recent structural and functional neuroimaging studies that focused on the anatomical substrate of tics and their possible genesis. These studies showed a consistent relationship between structural and functional abnormalities within motor cortico-basal ganglia circuits and occurrence of tics. The failure of top-down cortical control over motor pathways because of the atypical trajectory of brain development could be a possible mechanism of tic genesis. Occurrence of tics results in several adaptive mechanisms, including modification of cortico-striatal network activity (reduced functional activation of the primary motor cortex) and neurochemical (increased γ-aminobutyric acid concentrations in the supplementary motor area) and microstructural white matter pathways rearrangements.

  20. A Functional Approach to Deconvolve Dynamic Neuroimaging Data

    PubMed Central

    Jiang, Ci-Ren; Aston, John A. D.; Wang, Jane-Ling

    2016-01-01

    Positron emission tomography (PET) is an imaging technique which can be used to investigate chemical changes in human biological processes such as cancer development or neurochemical reactions. Most dynamic PET scans are currently analyzed based on the assumption that linear first-order kinetics can be used to adequately describe the system under observation. However, there has recently been strong evidence that this is not the case. To provide an analysis of PET data which is free from this compartmental assumption, we propose a nonparametric deconvolution and analysis model for dynamic PET data based on functional principal component analysis. This yields flexibility in the possible deconvolved functions while still performing well when a linear compartmental model setup is the true data generating mechanism. As the deconvolution needs to be performed on only a relative small number of basis functions rather than voxel by voxel in the entire three-dimensional volume, the methodology is both robust to typical brain imaging noise levels while also being computationally efficient. The new methodology is investigated through simulations in both one-dimensional functions and 2D images and also applied to a neuroimaging study whose goal is the quantification of opioid receptor concentration in the brain. PMID:27226673

  1. Neurochemistry of schizophrenia: the contribution of neuroimaging postmortem pathology and neurochemistry in schizophrenia.

    PubMed

    Dean, B

    2012-01-01

    The advent of molecular neuroimaging has greatly impacted on understanding the neurochemical changes occurring in the CNS from subjects with psychiatric disorders, especially schizophrenia. This review focuses on the outcomes from studies using positron emission tomography and single photon emission computer tomography that have measure levels of neurotransmitter receptors and transporters in the CNS from subjects with schizophrenia. One outcome from such studies is the confirmation of a number of findings using postmortem tissue, but in the case of neuroimaging, using drug na�ve and drug free subjects. These findings add weight to the argument that findings from postmortem studies are not an artifact of tissue processing or a simple drug effect. However, there are some important unique findings from studies using neuroimaging studies. These include evidence to suggest that in schizophrenia there are alterations in dopamine synthesis and release, which are not accompanied by an appropriate down-regulation of dopamine D2 receptors. There are also data that would support the notion that decreased levels of serotonin 2A receptors may be an early marker of the onset of schizophrenia. Whilst there is a clear need for on-going development of neuroimaging ligands to expand the number of targets that can be studied and to increase cohort sizes in neuroimaging studies to give power to the analyses of the resulting data, current studies show that existing neuroimaging studies have already extended our understanding of the underlying pathophysiology of psychiatric disorders such as schizophrenia. PMID:23279177

  2. Responsible Reporting: Neuroimaging News in the Age of Responsible Research and Innovation.

    PubMed

    de Jong, Irja Marije; Kupper, Frank; Arentshorst, Marlous; Broerse, Jacqueline

    2016-08-01

    Besides offering opportunities in both clinical and non-clinical domains, the application of novel neuroimaging technologies raises pressing dilemmas. 'Responsible Research and Innovation' (RRI) aims to stimulate research and innovation activities that take ethical and social considerations into account from the outset. We previously identified that Dutch neuroscientists interpret "responsible innovation" as educating the public on neuroimaging technologies via the popular press. Their aim is to mitigate (neuro)hype, an aim shared with the wider emerging RRI community. Here, we present results of a media-analysis undertaken to establish whether the body of articles in the Dutch popular press presents balanced conversations on neuroimaging research to the public. We found that reporting was mostly positive and framed in terms of (healthcare) progress. There was rarely a balance between technology opportunities and limitations, and even fewer articles addressed societal or ethical aspects of neuroimaging research. Furthermore, neuroimaging metaphors seem to favour oversimplification. Current reporting is therefore more likely to enable hype than to mitigate it. How can neuroscientists, given their self-ascribed social responsibility, address this conundrum? We make a case for a collective and shared responsibility among neuroscientists, journalists and other stakeholders, including funders, committed to responsible reporting on neuroimaging research.

  3. Heads in the Cloud: A Primer on Neuroimaging Applications of High Performance Computing.

    PubMed

    Shatil, Anwar S; Younas, Sohail; Pourreza, Hossein; Figley, Chase R

    2015-01-01

    With larger data sets and more sophisticated analyses, it is becoming increasingly common for neuroimaging researchers to push (or exceed) the limitations of standalone computer workstations. Nonetheless, although high-performance computing platforms such as clusters, grids and clouds are already in routine use by a small handful of neuroimaging researchers to increase their storage and/or computational power, the adoption of such resources by the broader neuroimaging community remains relatively uncommon. Therefore, the goal of the current manuscript is to: 1) inform prospective users about the similarities and differences between computing clusters, grids and clouds; 2) highlight their main advantages; 3) discuss when it may (and may not) be advisable to use them; 4) review some of their potential problems and barriers to access; and finally 5) give a few practical suggestions for how interested new users can start analyzing their neuroimaging data using cloud resources. Although the aim of cloud computing is to hide most of the complexity of the infrastructure management from end-users, we recognize that this can still be an intimidating area for cognitive neuroscientists, psychologists, neurologists, radiologists, and other neuroimaging researchers lacking a strong computational background. Therefore, with this in mind, we have aimed to provide a basic introduction to cloud computing in general (including some of the basic terminology, computer architectures, infrastructure and service models, etc.), a practical overview of the benefits and drawbacks, and a specific focus on how cloud resources can be used for various neuroimaging applications.

  4. Heads in the Cloud: A Primer on Neuroimaging Applications of High Performance Computing.

    PubMed

    Shatil, Anwar S; Younas, Sohail; Pourreza, Hossein; Figley, Chase R

    2015-01-01

    With larger data sets and more sophisticated analyses, it is becoming increasingly common for neuroimaging researchers to push (or exceed) the limitations of standalone computer workstations. Nonetheless, although high-performance computing platforms such as clusters, grids and clouds are already in routine use by a small handful of neuroimaging researchers to increase their storage and/or computational power, the adoption of such resources by the broader neuroimaging community remains relatively uncommon. Therefore, the goal of the current manuscript is to: 1) inform prospective users about the similarities and differences between computing clusters, grids and clouds; 2) highlight their main advantages; 3) discuss when it may (and may not) be advisable to use them; 4) review some of their potential problems and barriers to access; and finally 5) give a few practical suggestions for how interested new users can start analyzing their neuroimaging data using cloud resources. Although the aim of cloud computing is to hide most of the complexity of the infrastructure management from end-users, we recognize that this can still be an intimidating area for cognitive neuroscientists, psychologists, neurologists, radiologists, and other neuroimaging researchers lacking a strong computational background. Therefore, with this in mind, we have aimed to provide a basic introduction to cloud computing in general (including some of the basic terminology, computer architectures, infrastructure and service models, etc.), a practical overview of the benefits and drawbacks, and a specific focus on how cloud resources can be used for various neuroimaging applications. PMID:27279746

  5. Heads in the Cloud: A Primer on Neuroimaging Applications of High Performance Computing

    PubMed Central

    Shatil, Anwar S.; Younas, Sohail; Pourreza, Hossein; Figley, Chase R.

    2015-01-01

    With larger data sets and more sophisticated analyses, it is becoming increasingly common for neuroimaging researchers to push (or exceed) the limitations of standalone computer workstations. Nonetheless, although high-performance computing platforms such as clusters, grids and clouds are already in routine use by a small handful of neuroimaging researchers to increase their storage and/or computational power, the adoption of such resources by the broader neuroimaging community remains relatively uncommon. Therefore, the goal of the current manuscript is to: 1) inform prospective users about the similarities and differences between computing clusters, grids and clouds; 2) highlight their main advantages; 3) discuss when it may (and may not) be advisable to use them; 4) review some of their potential problems and barriers to access; and finally 5) give a few practical suggestions for how interested new users can start analyzing their neuroimaging data using cloud resources. Although the aim of cloud computing is to hide most of the complexity of the infrastructure management from end-users, we recognize that this can still be an intimidating area for cognitive neuroscientists, psychologists, neurologists, radiologists, and other neuroimaging researchers lacking a strong computational background. Therefore, with this in mind, we have aimed to provide a basic introduction to cloud computing in general (including some of the basic terminology, computer architectures, infrastructure and service models, etc.), a practical overview of the benefits and drawbacks, and a specific focus on how cloud resources can be used for various neuroimaging applications. PMID:27279746

  6. [Value-Added--Adding Economic Value in the Food Industry].

    ERIC Educational Resources Information Center

    Welch, Mary A., Ed.

    1989-01-01

    This booklet focuses on the economic concept of "value added" to goods and services. A student activity worksheet illustrates how the steps involved in processing food are examples of the concept of value added. The booklet further links food processing to the idea of value added to the Gross National Product (GNP). Discussion questions, a student…

  7. Overcoming the effects of false positives and threshold bias in graph theoretical analyses of neuroimaging data

    PubMed Central

    Drakesmith, M.; Caeyenberghs, K.; Dutt, A.; Lewis, G.; David, A.S.; Jones, D.K.

    2015-01-01

    Graph theory (GT) is a powerful framework for quantifying topological features of neuroimaging-derived functional and structural networks. However, false positive (FP) connections arise frequently and influence the inferred topology of networks. Thresholding is often used to overcome this problem, but an appropriate threshold often relies on a priori assumptions, which will alter inferred network topologies. Four common network metrics (global efficiency, mean clustering coefficient, mean betweenness and smallworldness) were tested using a model tractography dataset. It was found that all four network metrics were significantly affected even by just one FP. Results also show that thresholding effectively dampens the impact of FPs, but at the expense of adding significant bias to network metrics. In a larger number (n = 248) of tractography datasets, statistics were computed across random group permutations for a range of thresholds, revealing that statistics for network metrics varied significantly more than for non-network metrics (i.e., number of streamlines and number of edges). Varying degrees of network atrophy were introduced artificially to half the datasets, to test sensitivity to genuine group differences. For some network metrics, this atrophy was detected as significant (p < 0.05, determined using permutation testing) only across a limited range of thresholds. We propose a multi-threshold permutation correction (MTPC) method, based on the cluster-enhanced permutation correction approach, to identify sustained significant effects across clusters of thresholds. This approach minimises requirements to determine a single threshold a priori. We demonstrate improved sensitivity of MTPC-corrected metrics to genuine group effects compared to an existing approach and demonstrate the use of MTPC on a previously published network analysis of tractography data derived from a clinical population. In conclusion, we show that there are large biases and instability

  8. Neuroimaging and Neuromodulation: Complementary Approaches for Identifying the Neuronal Correlates of Tinnitus

    PubMed Central

    Langguth, Berthold; Schecklmann, Martin; Lehner, Astrid; Landgrebe, Michael; Poeppl, Timm Benjamin; Kreuzer, Peter Michal; Schlee, Winfried; Weisz, Nathan; Vanneste, Sven; De Ridder, Dirk

    2012-01-01

    An inherent limitation of functional imaging studies is their correlational approach. More information about critical contributions of specific brain regions can be gained by focal transient perturbation of neural activity in specific regions with non-invasive focal brain stimulation methods. Functional imaging studies have revealed that tinnitus is related to alterations in neuronal activity of central auditory pathways. Modulation of neuronal activity in auditory cortical areas by repetitive transcranial magnetic stimulation (rTMS) can reduce tinnitus loudness and, if applied repeatedly, exerts therapeutic effects, confirming the relevance of auditory cortex activation for tinnitus generation and persistence. Measurements of oscillatory brain activity before and after rTMS demonstrate that the same stimulation protocol has different effects on brain activity in different patients, presumably related to interindividual differences in baseline activity in the clinically heterogeneous study cohort. In addition to alterations in auditory pathways, imaging techniques also indicate the involvement of non-auditory brain areas, such as the fronto-parietal “awareness” network and the non-tinnitus-specific distress network consisting of the anterior cingulate cortex, anterior insula, and amygdale. Involvement of the hippocampus and the parahippocampal region putatively reflects the relevance of memory mechanisms in the persistence of the phantom percept and the associated distress. Preliminary studies targeting the dorsolateral prefrontal cortex, the dorsal anterior cingulate cortex, and the parietal cortex with rTMS and with transcranial direct current stimulation confirm the relevance of the mentioned non-auditory networks. Available data indicate the important value added by brain stimulation as a complementary approach to neuroimaging for identifying the neuronal correlates of the various clinical aspects of tinnitus. PMID:22509155

  9. Overcoming the effects of false positives and threshold bias in graph theoretical analyses of neuroimaging data.

    PubMed

    Drakesmith, M; Caeyenberghs, K; Dutt, A; Lewis, G; David, A S; Jones, D K

    2015-09-01

    Graph theory (GT) is a powerful framework for quantifying topological features of neuroimaging-derived functional and structural networks. However, false positive (FP) connections arise frequently and influence the inferred topology of networks. Thresholding is often used to overcome this problem, but an appropriate threshold often relies on a priori assumptions, which will alter inferred network topologies. Four common network metrics (global efficiency, mean clustering coefficient, mean betweenness and smallworldness) were tested using a model tractography dataset. It was found that all four network metrics were significantly affected even by just one FP. Results also show that thresholding effectively dampens the impact of FPs, but at the expense of adding significant bias to network metrics. In a larger number (n=248) of tractography datasets, statistics were computed across random group permutations for a range of thresholds, revealing that statistics for network metrics varied significantly more than for non-network metrics (i.e., number of streamlines and number of edges). Varying degrees of network atrophy were introduced artificially to half the datasets, to test sensitivity to genuine group differences. For some network metrics, this atrophy was detected as significant (p<0.05, determined using permutation testing) only across a limited range of thresholds. We propose a multi-threshold permutation correction (MTPC) method, based on the cluster-enhanced permutation correction approach, to identify sustained significant effects across clusters of thresholds. This approach minimises requirements to determine a single threshold a priori. We demonstrate improved sensitivity of MTPC-corrected metrics to genuine group effects compared to an existing approach and demonstrate the use of MTPC on a previously published network analysis of tractography data derived from a clinical population. In conclusion, we show that there are large biases and instability induced

  10. Searching for disease-modifying drugs in AD: can we combine neuropsychological tools with biological markers?

    PubMed

    Caraci, Filippo; Castellano, Sabrina; Salomone, Salvatore; Drago, Filippo; Bosco, Paolo; Di Nuovo, Santo

    2014-02-01

    Drug discovery efforts in Alzheimer's disease (AD) have been directed in the last ten years to develop "disease-modifying drugs" able to exert neuroprotective effects in an early phase of AD pathogenesis. Unfortunately several candidate disease-modifying drugs have failed in Phase III clinical trials conducted in mild to moderate AD for different methodological difficulties, such as the time course of treatment in relation to development of disease as well as the appropriate use of validated biological and neuropsychological markers. Mild cognitive impairment (MCI) has been considered a precursor of AD. Much effort is now directed to identify the most appropriate and sensitive markers which can predict the progression from MCI to AD, such as neuroimaging markers (e.g. hippocampal atrophy and amyloid positron emission tomography imaging), cerebrospinal fluid markers (i.e. association of elevated tau with low levels of amyloid β -peptide(1-42) and neuropsychological markers (i.e. episodic memory deficits and executive dysfunction). Recent studies demonstrate that the combination of these different biomarkers significantly increases the chance to predict the conversion into AD within 24 months. These biomarkers will be essential in the future to analyze clinical efficacy of disease-modifying drugs in MCI patients at high risk to develop AD. In the present review we analyze recent evidence on the combination of neuropsychological and biological markers in AD as a new tool to track disease progression in early AD as well as the response to disease-modifying drugs. PMID:24040795

  11. Action growth for AdS black holes

    NASA Astrophysics Data System (ADS)

    Cai, Rong-Gen; Ruan, Shan-Ming; Wang, Shao-Jiang; Yang, Run-Qiu; Peng, Rong-Hui

    2016-09-01

    Recently a Complexity-Action (CA) duality conjecture has been proposed, which relates the quantum complexity of a holographic boundary state to the action of a Wheeler-DeWitt (WDW) patch in the anti-de Sitter (AdS) bulk. In this paper we further investigate the duality conjecture for stationary AdS black holes and derive some exact results for the growth rate of action within the Wheeler-DeWitt (WDW) patch at late time approximation, which is supposed to be dual to the growth rate of quantum complexity of holographic state. Based on the results from the general D-dimensional Reissner-Nordström (RN)-AdS black hole, rotating/charged Bañados-Teitelboim-Zanelli (BTZ) black hole, Kerr-AdS black hole and charged Gauss-Bonnet-AdS black hole, we present a universal formula for the action growth expressed in terms of some thermodynamical quantities associated with the outer and inner horizons of the AdS black holes. And we leave the conjecture unchanged that the stationary AdS black hole in Einstein gravity is the fastest computer in nature.

  12. [Functional Neuroimaging Pilot Study of Borderline Personality Disorder in Adolescents].

    PubMed

    LeBoeuf, Amélie; Guilé, Jean-Marc; Labelle, Réal; Luck, David

    2016-01-01

    Borderline personality disorder (BPD) is being increasingly recognized by clinicians working with adolescents, and the reliability and validity of the diagnosis have been established in the adolescent population. Adolescence is known to be a period of high risk for BPD development as most patients identify the onset of their symptoms to be in the adolescent period. As with other mental health disorders, personality disorder, are thought to result from the interaction between biological and environmental factors. Functional neuroimaging studies are reporting an increasing amount of data on abnormal neuronal functions in BPD adult patients. However, no functional neuroimaging studies have been conducted in adolescents with BPD.Objectives This pilot project aims to evaluate the feasibility of a functional magnetic resonance imaging (fMRI) study coupled with clinical and psychological measures in adolescent girls with a diagnosis of BPD. It also aims to identify neuronal regions of interest (ROI) for the study of BPD in adolescent girls.Method Six female adolescents meeting DSM-IV criteria for BPD and 6 female adolescents without psychiatric disorder were recruited. Both groups were evaluated for BPD symptoms, depressive symptoms, impulsivity, affective lability, and other potential psychiatric comorbidities. We used fMRI to compare patterns of regional brain activation between these two groups as they viewed 20 positive, 20 negative and 20 neutral emotion-inducing pictures, which were presented in random order.Results Participants were recruited over a period of 22 months. The protocol was well tolerated by participants. Mean age of the BPD group and control group was 15.8 ± 0.9 years-old and 15.5 ± 1.2 years-old respectively. Psychiatric comorbidity and use of medication was common among participants in the BPD group. This group showed higher impulsivity and affective lability scores. For the fMRI task, BPD patients demonstrated greater differences in activation

  13. Enhanced photoacoustic neuroimaging with gold nanorods and PEBBLEs

    NASA Astrophysics Data System (ADS)

    Witte, Russell S.; Kim, K.; Agarwal, A.; Fan, W.; Kopelman, R.; Kotov, N.; Kipke, D.; O'Donnell, M.

    2008-02-01

    Photoacoustic (PA) imaging provides excellent optical contrast with decent penetration and high spatial resolution, making it attractive for a variety of neural applications. We evaluated optical contrast agents with high absorption in the near infrared (NIR) as potential enhancers for PA neuroimaging: optical dyes, gold nanorods (GNRs) and PEBBLEs loaded with indocyanine green. Two PA systems were developed to test these agents in excised neural tissue and in vivo mouse brain. Lobster nerves were stained with the agents for 30 minutes and placed in a hybrid nerve chamber capable of electrical stimulation and recording, optical spectroscopy and PA imaging. Contrast agents boosted the PA signal by at least 30 dB using NIR illumination from a tunable pulsed laser. Photobleaching may be a limiting factor for optical dyes-the PA signal decreased steadily with laser illumination. The second setup enabled in vivo transcranial imaging of the mouse brain. A custom clinical ultrasound scanner and a 10-MHz linear array provided near real-time images during and after an injection of 2 nM gold nanorods into the tail vein. The peak PA signal from the brain vasculature was enhanced by up to 2 dB at 710 nm. Temporal dynamics of the PA signal were also consistent with mixing of the GNRs in the blood. These studies provide a baseline for enhanced PA imaging in neural tissue. The smart contrast agents employed in this study can be further engineered for molecular targeting and controlled drug delivery with potential treatment for a myriad of neural disorders.

  14. DeID - a data sharing tool for neuroimaging studies.

    PubMed

    Song, Xuebo; Wang, James; Wang, Anlin; Meng, Qingping; Prescott, Christian; Tsu, Loretta; Eckert, Mark A

    2015-01-01

    Funding institutions and researchers increasingly expect that data will be shared to increase scientific integrity and provide other scientists with the opportunity to use the data with novel methods that may advance understanding in a particular field of study. In practice, sharing human subject data can be complicated because data must be de-identified prior to sharing. Moreover, integrating varied data types collected in a study can be challenging and time consuming. For example, sharing data from structural imaging studies of a complex disorder requires the integration of imaging, demographic and/or behavioral data in a way that no subject identifiers are included in the de-identified dataset and with new subject labels or identification values that cannot be tracked back to the original ones. We have developed a Java program that users can use to remove identifying information in neuroimaging datasets, while still maintaining the association among different data types from the same subject for further studies. This software provides a series of user interaction wizards to allow users to select data variables to be de-identified, implements functions for auditing and validation of de-identified data, and enables the user to share the de-identified data in a single compressed package through various communication protocols, such as FTPS and SFTP. DeID runs with Windows, Linux, and Mac operating systems and its open architecture allows it to be easily adapted to support a broader array of data types, with the goal of facilitating data sharing. DeID can be obtained at http://www.nitrc.org/projects/deid. PMID:26441500

  15. Functional and molecular neuroimaging of menopause and hormone replacement therapy

    PubMed Central

    Comasco, Erika; Frokjaer, Vibe G.; Sundström-Poromaa, Inger

    2014-01-01

    The level of gonadal hormones to which the female brain is exposed considerably changes across the menopausal transition, which in turn, is likely to be of great relevance for neurodegenerative diseases and psychiatric disorders. However, the neurobiological consequences of these hormone fluctuations and of hormone replacement therapy in the menopause have only begun to be understood. The present review summarizes the findings of thirty-five studies of human brain function, including functional magnetic resonance imaging, positron and single-photon computed emission tomography studies, in peri- and postmenopausal women treated with estrogen, or estrogen-progestagen replacement therapy. Seven studies using gonadotropin-releasing hormone agonist intervention as a model of hormonal withdrawal are also included. Cognitive paradigms are employed by the majority of studies evaluating the effect of unopposed estrogen or estrogen-progestagen treatment on peri- and postmenopausal women's brain. In randomized-controlled trials, estrogen treatment enhances activation of fronto-cingulate regions during cognitive functioning, though in many cases no difference in cognitive performance was present. Progestagens seems to counteract the effects of estrogens. Findings on cognitive functioning during acute ovarian hormone withdrawal suggest a decrease in activation of the left inferior frontal gyrus, thus essentially corroborating the findings in postmenopausal women. Studies of the cholinergic and serotonergic systems indicate these systems as biological mediators of hormonal influences on the brain. More, hormonal replacement appears to increase cerebral blood flow in several cortical regions. On the other hand, studies on emotion processing in postmenopausal women are lacking. These results call for well-powered randomized-controlled multi-modal prospective neuroimaging studies as well as investigation on the related molecular mechanisms of effects of menopausal hormonal

  16. Boosting bioluminescence neuroimaging: an optimized protocol for brain studies.

    PubMed

    Aswendt, Markus; Adamczak, Joanna; Couillard-Despres, Sebastien; Hoehn, Mathias

    2013-01-01

    Bioluminescence imaging is widely used for optical cell tracking approaches. However, reliable and quantitative bioluminescence of transplanted cells in the brain is highly challenging. In this study we established a new bioluminescence imaging protocol dedicated for neuroimaging, which increases sensitivity especially for noninvasive tracking of brain cell grafts. Different D-Luciferin concentrations (15, 150, 300 and 750 mg/kg), injection routes (i.v., i.p., s.c.), types of anesthesia (Isoflurane, Ketamine/Xylazine, Pentobarbital) and timing of injection were compared using DCX-Luc transgenic mice for brain specific bioluminescence. Luciferase kinetics was quantitatively evaluated for maximal photon emission, total photon emission and time-to-peak. Photon emission followed a D-Luciferin dose-dependent relation without saturation, but with delay in time-to-peak increasing for increasing concentrations. The comparison of intravenous, subcutaneous and intraperitoneal substrate injection reflects expected pharmacokinetics with fastest and highest photon emission for intravenous administration. Ketamine/Xylazine and Pentobarbital anesthesia showed no significant beneficial effect on maximal photon emission. However, a strong difference in outcome was observed by injecting the substrate pre Isoflurane anesthesia. This protocol optimization for brain specific bioluminescence imaging comprises injection of 300 mg/kg D-Luciferin pre Isoflurane anesthesia as an efficient and stable method with a signal gain of approx. 200% (compared to 150 mg/kg post Isoflurane). Gain in sensitivity by the novel imaging protocol was quantitatively assessed by signal-to-noise calculations of luciferase-expressing neural stem cells grafted into mouse brains (transplantation of 3,000-300,000 cells). The optimized imaging protocol lowered the detection limit from 6,000 to 3,000 cells by a gain in signal-to-noise ratio.

  17. Multiple sclerosis in malaysia: demographics, clinical features, and neuroimaging characteristics.

    PubMed

    Viswanathan, S; Rose, N; Masita, A; Dhaliwal, J S; Puvanarajah, S D; Rafia, M H; Muda, S

    2013-01-01

    Background. Multiple sclerosis (MS) is an uncommon disease in multiracial Malaysia. Diagnosing patients with idiopathic inflammatory demyelinating diseases has been greatly aided by the evolution in diagnostic criterion, the identification of new biomarkers, and improved accessibility to neuroimaging in the country. Objectives. To investigate the spectrum of multiple sclerosis in Malaysia. Methods. Retrospective analysis with longitudinal follow-up of patients referred to a single tertiary medical center with neurology services in Malaysia. Results. Out of 245 patients with idiopathic inflammatory demyelinating disease, 104 patients had multiple sclerosis. Female to male ratio was 5 : 1. Mean age at onset was 28.6 ± 9.9 years. The Malays were the predominant racial group affected followed by the Chinese, Indians, and other indigenous groups. Subgroup analysis revealed more Chinese having neuromyelitis optica and its spectrum disorders rather than multiple sclerosis. Positive family history was reported in 5%. Optic neuritis and myelitis were the commonest presentations at onset of disease, and relapsing remitting course was the commonest disease pattern observed. Oligoclonal band positivity was 57.6%. At disease onset, 61.5% and 66.4% fulfilled the 2005 and 2010 McDonald's criteria for dissemination in space. Mean cord lesion length was 1.86 ± 1.65 vertebral segments in the relapsing remitting group as opposed to 6.25 ± 5.18 vertebral segments in patients with neuromyelitis optica and its spectrum disorders. Conclusion. The spectrum of multiple sclerosis in Malaysia has changed over the years. Further advancement in diagnostic criteria will no doubt continue to contribute to the evolution of this disease here. PMID:24455266

  18. Neuroimaging Findings in Cryptogenic Stroke Patients with and without PFO

    PubMed Central

    Thaler, David E.; Ruthazer, Robin; Di Angelantonio, Emanuele; Di Tullio, Marco R.; Donovan, Jennifer S.; Elkind, Mitchell S. V.; Griffith, John; Homma, Shunichi; Jaigobin, Cheryl; Mas, Jean-Louis; Mattle, Heinrich P.; Michel, Patrik; Mono, Marie-Luise; Nedeltchev, Krassen; Papetti, Federica; Serena, Joaquín; Weimar, Christian; Kent, David M.

    2013-01-01

    BACKGROUND Patent foramen ovale (PFO) and cryptogenic stroke (CS) are commonly associated but some PFOs are incidental. Specific radiological findings associated with PFO may be more likely to indicate a PFO-related etiology. We examined whether specific radiological findings are associated with PFO among subjects with CS and known PFO status. METHODS We analyzed the Risk of Paradoxical Embolism (RoPE) database of subjects with CS and known PFO status, for associations between PFO and: 1) index stroke seen on imaging, 2) index stroke size, 3) index stroke location, 4) multiple index strokes, and 5) prior stroke on baseline imaging. We also compared imaging with purported “high risk” echocardiographic features. RESULTS Subjects (n=2680) were significantly more likely to have a PFO if their index stroke was large (OR 1.36, p=0.0025), seen on index imaging (OR 1.53, p=0.003), and superficially located (OR 1.54, p<0.0001). A prior stroke on baseline imaging was associated with not having a PFO (OR 0.66, p<0.0001). Finding multiple index strokes was unrelated to PFO status (OR 1.21, p=0.161). No echocardiographic variables were related to PFO status. CONCLUSIONS This is the largest study to report the radiological characteristics of patients with CS and known PFO status. Strokes that were large, radiologically apparent, superficially located, or unassociated with prior radiological infarcts were more likely to be PFO associated than were unapparent, smaller, or deep strokes, and those accompanied by chronic infarcts. There was no association between PFO and multiple acute strokes nor between specific echocardiographic PFO features with neuroimaging findings. PMID:23339957

  19. Neuroimaging with magnetoencephalography: A dynamic view of brain pathophysiology.

    PubMed

    Wilson, Tony W; Heinrichs-Graham, Elizabeth; Proskovec, Amy L; McDermott, Timothy J

    2016-09-01

    Magnetoencephalography (MEG) is a noninvasive, silent, and totally passive neurophysiological imaging method with excellent temporal resolution (∼1 ms) and good spatial precision (∼3-5 mm). In a typical experiment, MEG data are acquired as healthy controls or patients with neurologic or psychiatric disorders perform a specific cognitive task, or receive sensory stimulation. The resulting data are generally analyzed using standard electrophysiological methods, coupled with advanced image reconstruction algorithms. To date, the total number of MEG instruments and associated users is significantly smaller than comparable human neuroimaging techniques, although this is likely to change in the near future with advances in the technology. Despite this small base, MEG research has made a significant impact on several areas of translational neuroscience, largely through its unique capacity to quantify the oscillatory dynamics of activated brain circuits in humans. This review focuses on the clinical areas where MEG imaging has arguably had the greatest impact in regard to the identification of aberrant neural dynamics at the regional and network level, monitoring of disease progression, determining how efficacious pharmacologic and behavioral interventions modulate neural systems, and the development of neural markers of disease. Specifically, this review covers recent advances in understanding the abnormal neural oscillatory dynamics that underlie Parkinson's disease, autism spectrum disorders, human immunodeficiency virus (HIV)-associated neurocognitive disorders, cerebral palsy, attention-deficit hyperactivity disorder, cognitive aging, and post-traumatic stress disorder. MEG imaging has had a major impact on how clinical neuroscientists understand the brain basis of these disorders, and its translational influence is rapidly expanding with new discoveries and applications emerging continuously. PMID:26874219

  20. On Statistical Analysis of Neuroimages with Imperfect Registration

    PubMed Central

    Kim, Won Hwa; Ravi, Sathya N.; Johnson, Sterling C.; Okonkwo, Ozioma C.; Singh, Vikas

    2016-01-01

    A variety of studies in neuroscience/neuroimaging seek to perform statistical inference on the acquired brain image scans for diagnosis as well as understanding the pathological manifestation of diseases. To do so, an important first step is to register (or co-register) all of the image data into a common coordinate system. This permits meaningful comparison of the intensities at each voxel across groups (e.g., diseased versus healthy) to evaluate the effects of the disease and/or use machine learning algorithms in a subsequent step. But errors in the underlying registration make this problematic, they either decrease the statistical power or make the follow-up inference tasks less effective/accurate. In this paper, we derive a novel algorithm which offers immunity to local errors in the underlying deformation field obtained from registration procedures. By deriving a deformation invariant representation of the image, the downstream analysis can be made more robust as if one had access to a (hypothetical) far superior registration procedure. Our algorithm is based on recent work on scattering transform. Using this as a starting point, we show how results from harmonic analysis (especially, non-Euclidean wavelets) yields strategies for designing deformation and additive noise invariant representations of large 3-D brain image volumes. We present a set of results on synthetic and real brain images where we achieve robust statistical analysis even in the presence of substantial deformation errors; here, standard analysis procedures significantly under-perform and fail to identify the true signal. PMID:27042168

  1. Functional neuroimaging insights into the physiology of human sleep.

    PubMed

    Dang-Vu, Thien Thanh; Schabus, Manuel; Desseilles, Martin; Sterpenich, Virginie; Bonjean, Maxime; Maquet, Pierre

    2010-12-01

    Functional brain imaging has been used in humans to noninvasively investigate the neural mechanisms underlying the generation of sleep stages. On the one hand, REM sleep has been associated with the activation of the pons, thalamus, limbic areas, and temporo-occipital cortices, and the deactivation of prefrontal areas, in line with theories of REM sleep generation and dreaming properties. On the other hand, during non-REM (NREM) sleep, decreases in brain activity have been consistently found in the brainstem, thalamus, and in several cortical areas including the medial prefrontal cortex (MPFC), in agreement with a homeostatic need for brain energy recovery. Benefiting from a better temporal resolution, more recent studies have characterized the brain activations related to phasic events within specific sleep stages. In particular, they have demonstrated that NREM sleep oscillations (spindles and slow waves) are indeed associated with increases in brain activity in specific subcortical and cortical areas involved in the generation or modulation of these waves. These data highlight that, even during NREM sleep, brain activity is increased, yet regionally specific and transient. Besides refining the understanding of sleep mechanisms, functional brain imaging has also advanced the description of the functional properties of sleep. For instance, it has been shown that the sleeping brain is still able to process external information and even detect the pertinence of its content. The relationship between sleep and memory has also been refined using neuroimaging, demonstrating post-learning reactivation during sleep, as well as the reorganization of memory representation on the systems level, sometimes with long-lasting effects on subsequent memory performance. Further imaging studies should focus on clarifying the role of specific sleep patterns for the processing of external stimuli, as well as the consolidation of freshly encoded information during sleep.

  2. Superstring theory in AdS(3) and plane waves

    NASA Astrophysics Data System (ADS)

    Son, John Sang Won

    This thesis is devoted to the study of string theory in AdS 3 and its applications to recent developments in string theory. The difficulties associated with formulating a consistent string theory in AdS3 and its underlying SL(2, R) WZW model are explained. We describe how these difficulties can be overcome by assuming that the SL(2, R) WZW model contains spectral flow symmetry. The existence of spectral flow symmetry in the fully quantum treatment is proved by a calculation of the one-loop string partition function. We consider Euclidean AdS 3 with the time direction periodically identified, and compute the torus partition function in this background. The string spectrum can be reproduced by viewing the one-loop calculation as the free energy of a gas of strings, thus providing a rigorous proof of the results based on spectral flow arguments. Next, we turn to spacetimes that are quotients of AdS 3, which include the BTZ black hole and conical spaces. Strings propagating in the conical space are described by taking an orbifold of strings in AdS3. We show that the twisted states of these orbifolds can be obtained by fractional spectral flow. We show that the shift in the ground state energy usually associated with orbifold twists is absent in this case, and offer a unified framework in which to view spectral flow. Lastly, we consider the RNS superstrings in AdS 3 x S3 x M , where M may be K3 or T 4, based on supersymmetric extensions of SL(2, R) and SU(2) WZW models. We construct the physical states and calculate the spectrum. A subsector of this theory describes strings propagating in the six dimensional plane wave obtained by the Penrose limit of AdS3 x S3 x M . We reproduce the plane wave spectrum by taking J and the radius to infinity. We show that the plane wave spectrum actually coincides with the large J spectrum at fixed radius, i.e. in AdS3 x S3. Relation to some recent topics of interest such as the Frolov-Tseytlin string and strings with critical tension

  3. Nipype: a flexible, lightweight and extensible neuroimaging data processing framework in python.

    PubMed

    Gorgolewski, Krzysztof; Burns, Christopher D; Madison, Cindee; Clark, Dav; Halchenko, Yaroslav O; Waskom, Michael L; Ghosh, Satrajit S

    2011-01-01

    Current neuroimaging software offer users an incredible opportunity to analyze their data in different ways, with different underlying assumptions. Several sophisticated software packages (e.g., AFNI, BrainVoyager, FSL, FreeSurfer, Nipy, R, SPM) are used to process and analyze large and often diverse (highly multi-dimensional) data. However, this heterogeneous collection of specialized applications creates several issues that hinder replicable, efficient, and optimal use of neuroimaging analysis approaches: (1) No uniform access to neuroimaging analysis software and usage information; (2) No framework for comparative algorithm development and dissemination; (3) Personnel turnover in laboratories often limits methodological continuity and training new personnel takes time; (4) Neuroimaging software packages do not address computational efficiency; and (5) Methods sections in journal articles are inadequate for reproducing results. To address these issues, we present Nipype (Neuroimaging in Python: Pipelines and Interfaces; http://nipy.org/nipype), an open-source, community-developed, software package, and scriptable library. Nipype solves the issues by providing Interfaces to existing neuroimaging software with uniform usage semantics and by facilitating interaction between these packages using Workflows. Nipype provides an environment that encourages interactive exploration of algorithms, eases the design of Workflows within and between packages, allows rapid comparative development of algorithms and reduces the learning curve necessary to use different packages. Nipype supports both local and remote execution on multi-core machines and clusters, without additional scripting. Nipype is Berkeley Software Distribution licensed, allowing anyone unrestricted usage. An open, community-driven development philosophy allows the software to quickly adapt and address the varied needs of the evolving neuroimaging community, especially in the context of increasing demand for

  4. Nipype: a flexible, lightweight and extensible neuroimaging data processing framework in python.

    PubMed

    Gorgolewski, Krzysztof; Burns, Christopher D; Madison, Cindee; Clark, Dav; Halchenko, Yaroslav O; Waskom, Michael L; Ghosh, Satrajit S

    2011-01-01

    Current neuroimaging software offer users an incredible opportunity to analyze their data in different ways, with different underlying assumptions. Several sophisticated software packages (e.g., AFNI, BrainVoyager, FSL, FreeSurfer, Nipy, R, SPM) are used to process and analyze large and often diverse (highly multi-dimensional) data. However, this heterogeneous collection of specialized applications creates several issues that hinder replicable, efficient, and optimal use of neuroimaging analysis approaches: (1) No uniform access to neuroimaging analysis software and usage information; (2) No framework for comparative algorithm development and dissemination; (3) Personnel turnover in laboratories often limits methodological continuity and training new personnel takes time; (4) Neuroimaging software packages do not address computational efficiency; and (5) Methods sections in journal articles are inadequate for reproducing results. To address these issues, we present Nipype (Neuroimaging in Python: Pipelines and Interfaces; http://nipy.org/nipype), an open-source, community-developed, software package, and scriptable library. Nipype solves the issues by providing Interfaces to existing neuroimaging software with uniform usage semantics and by facilitating interaction between these packages using Workflows. Nipype provides an environment that encourages interactive exploration of algorithms, eases the design of Workflows within and between packages, allows rapid comparative development of algorithms and reduces the learning curve necessary to use different packages. Nipype supports both local and remote execution on multi-core machines and clusters, without additional scripting. Nipype is Berkeley Software Distribution licensed, allowing anyone unrestricted usage. An open, community-driven development philosophy allows the software to quickly adapt and address the varied needs of the evolving neuroimaging community, especially in the context of increasing demand for

  5. Clinical and neuroimaging differences between posterior cortical atrophy and typical amnestic Alzheimer’s disease patients at an early disease stage

    PubMed Central

    Peng, Guoping; Wang, Jianqin; Feng, Zhan; Liu, Ping; Zhang, Yafei; He, Fangping; Chen, Zhongqin; Zhao, Kui; Luo, Benyan

    2016-01-01

    To identify clinical and neuroimaging characteristics between posterior cortical atrophy (PCA) and typical amnestic Alzheimer’s disease (tAD) patients at an early disease stage, 16 PCA and 13 age-matched tAD patients were enrolled. Compared with tAD patients, PCA patients showed higher mean recognition and recall test scores, and lower mean calculation, spatial attention, shape discrimination, and writing test scores. Mean right hippocampal volume was larger in PCA patients compared with tAD patients, while cortical gray matter (GM) volume of bilateral parietal and occipital lobes was smaller in PCA patients. Further, when compared with tAD patients, significant hypometabolism was observed in bilateral parietal and occipital lobes, particularly the right occipitotemporal junction in PCA patients. Additionally, there were significant positive correlations in recognition and recall scores with hippocampal volumes. In PCA patients, calculation and visuospatial ability scores are positively associated with GM volume of parietal and occipital lobes. And only spatial attention and shape discrimination scores are positively associated with regional glucose metabolism of parietal and occipital lobes. Therefore, PCA patients display better recognition and recall scores, which are associated with larger hippocampal volumes and poorer performance in visual spatial tasks because of marked GM atrophy and hypometabolism of parietal and occipital lobes. PMID:27377199

  6. Entanglement entropy for free scalar fields in AdS

    NASA Astrophysics Data System (ADS)

    Sugishita, Sotaro

    2016-09-01

    We compute entanglement entropy for free massive scalar fields in anti-de Sitter (AdS) space. The entangling surface is a minimal surface whose boundary is a sphere at the boundary of AdS. The entropy can be evaluated from the thermal free energy of the fields on a topological black hole by using the replica method. In odd-dimensional AdS, exact expressions of the Rényi entropy S n are obtained for arbitrary n. We also evaluate 1-loop corrections coming from the scalar fields to holographic entanglement entropy. Applying the results, we compute the leading difference of entanglement entropy between two holographic CFTs related by a renormalization group flow triggered by a double trace deformation. The difference is proportional to the shift of a central charge under the flow.

  7. Asymptotically AdS spacetimes with a timelike Kasner singularity

    NASA Astrophysics Data System (ADS)

    Ren, Jie

    2016-07-01

    Exact solutions to Einstein's equations for holographic models are presented and studied. The IR geometry has a timelike cousin of the Kasner singularity, which is the less generic case of the BKL (Belinski-Khalatnikov-Lifshitz) singularity, and the UV is asymptotically AdS. This solution describes a holographic RG flow between them. The solution's appearance is an interpolation between the planar AdS black hole and the AdS soliton. The causality constraint is always satisfied. The entanglement entropy and Wilson loops are discussed. The boundary condition for the current-current correlation function and the Laplacian in the IR is examined. There is no infalling wave in the IR, but instead, there is a normalizable solution in the IR. In a special case, a hyperscaling-violating geometry is obtained after a dimensional reduction.

  8. New massive gravity and AdS(4) counterterms.

    PubMed

    Jatkar, Dileep P; Sinha, Aninda

    2011-04-29

    We show that the recently proposed Dirac-Born-Infeld extension of new massive gravity emerges naturally as a counterterm in four-dimensional anti-de Sitter space (AdS(4)). The resulting on-shell Euclidean action is independent of the cutoff at zero temperature. We also find that the same choice of counterterm gives the usual area law for the AdS(4) Schwarzschild black hole entropy in a cutoff-independent manner. The parameter values of the resulting counterterm action correspond to a c=0 theory in the context of the duality between AdS(3) gravity and two-dimensional conformal field theory. We rewrite this theory in terms of the gauge field that is used to recast 3D gravity as a Chern-Simons theory. PMID:21635026

  9. Detailed ultraviolet asymptotics for AdS scalar field perturbations

    NASA Astrophysics Data System (ADS)

    Evnin, Oleg; Jai-akson, Puttarak

    2016-04-01

    We present a range of methods suitable for accurate evaluation of the leading asymptotics for integrals of products of Jacobi polynomials in limits when the degrees of some or all polynomials inside the integral become large. The structures in question have recently emerged in the context of effective descriptions of small amplitude perturbations in anti-de Sitter (AdS) spacetime. The limit of high degree polynomials corresponds in this situation to effective interactions involving extreme short-wavelength modes, whose dynamics is crucial for the turbulent instabilities that determine the ultimate fate of small AdS perturbations. We explicitly apply the relevant asymptotic techniques to the case of a self-interacting probe scalar field in AdS and extract a detailed form of the leading large degree behavior, including closed form analytic expressions for the numerical coefficients appearing in the asymptotics.

  10. Holography and AdS4 self-gravitating dyons

    NASA Astrophysics Data System (ADS)

    Lugo, A. R.; Moreno, E. F.; Schaposnik, F. A.

    2010-11-01

    We present a self-gravitating dyon solution of the Einstein-Yang-Mills-Higgs equations of motion in asymptotically AdS space. The back reaction of gauge and Higgs fields on the space-time geometry leads to the metric of an asymptotically AdS black hole. Using the gauge/gravity correspondence we analyze relevant properties of the finite temperature quantum field theory defined on the boundary. In particular we identify an order operator, characterize a phase transition of the dual theory on the border and also compute the expectation value of the finite temperature Wilson loop.

  11. AdS box graphs, unitarity and operator product expansions

    NASA Astrophysics Data System (ADS)

    Hoffmann, L.; Mesref, L.; Rühl, W.

    2000-11-01

    We develop a method of singularity analysis for conformal graphs which, in particular, is applicable to the holographic image of AdS supergravity theory. It can be used to determine the critical exponents for any such graph in a given channel. These exponents determine the towers of conformal blocks that are exchanged in this channel. We analyze the scalar AdS box graph and show that it has the same critical exponents as the corresponding CFT box graph. Thus pairs of external fields couple to the same exchanged conformal blocks in both theories. This is looked upon as a general structural argument supporting the Maldacena hypothesis.

  12. Phases of global AdS black holes

    NASA Astrophysics Data System (ADS)

    Basu, Pallab; Krishnan, Chethan; Subramanian, P. N. Bala

    2016-06-01

    We study the phases of gravity coupled to a charged scalar and gauge field in an asymptotically Anti-de Sitter spacetime ( AdS 4) in the grand canonical ensemble. For the conformally coupled scalar, an intricate phase diagram is charted out between the four relevant solutions: global AdS, boson star, Reissner-Nordstrom black hole and the hairy black hole. The nature of the phase diagram undergoes qualitative changes as the charge of the scalar is changed, which we discuss. We also discuss the new features that arise in the extremal limit.

  13. Integration of a neuroimaging processing pipeline into a pan-canadian computing grid

    NASA Astrophysics Data System (ADS)

    Lavoie-Courchesne, S.; Rioux, P.; Chouinard-Decorte, F.; Sherif, T.; Rousseau, M.-E.; Das, S.; Adalat, R.; Doyon, J.; Craddock, C.; Margulies, D.; Chu, C.; Lyttelton, O.; Evans, A. C.; Bellec, P.

    2012-02-01

    The ethos of the neuroimaging field is quickly moving towards the open sharing of resources, including both imaging databases and processing tools. As a neuroimaging database represents a large volume of datasets and as neuroimaging processing pipelines are composed of heterogeneous, computationally intensive tools, such open sharing raises specific computational challenges. This motivates the design of novel dedicated computing infrastructures. This paper describes an interface between PSOM, a code-oriented pipeline development framework, and CBRAIN, a web-oriented platform for grid computing. This interface was used to integrate a PSOM-compliant pipeline for preprocessing of structural and functional magnetic resonance imaging into CBRAIN. We further tested the capacity of our infrastructure to handle a real large-scale project. A neuroimaging database including close to 1000 subjects was preprocessed using our interface and publicly released to help the participants of the ADHD-200 international competition. This successful experiment demonstrated that our integrated grid-computing platform is a powerful solution for high-throughput pipeline analysis in the field of neuroimaging.

  14. [Functional neuroimaging in the diagnosis of patients with Parkinsonism: Update and recommendations for clinical use].

    PubMed

    Arbizu, J; Luquin, M R; Abella, J; de la Fuente-Fernández, R; Fernandez-Torrón, R; García-Solís, D; Garrastachu, P; Jiménez-Hoyuela, J M; Llaneza, M; Lomeña, F; Lorenzo-Bosquet, C; Martí, M J; Martinez-Castrillo, J C; Mir, P; Mitjavila, M; Ruiz-Martínez, J; Vela, L

    2014-01-01

    Functional Neuroimaging has been traditionally used in research for patients with different Parkinsonian syndromes. However, the emergence of commercial radiotracers together with the availability of single photon emission computed tomography (SPECT) and, more recently, positron emission tomography (PET) have made them available for clinical practice. Particularly, the development of clinical evidence achieved by functional neuroimaging techniques over the past two decades have motivated a progressive inclusion of several biomarkers in the clinical diagnostic criteria for neurodegenerative diseases that occur with Parkinsonism. However, the wide range of radiotracers designed to assess the involvement of different pathways in the neurodegenerative process underlying Parkinsonian syndromes (dopaminergic nigrostriatal pathway integrity, basal ganglia and cortical neuronal activity, myocardial sympathetic innervation), and the different neuroimaging techniques currently available (scintigraphy, SPECT and PET), have generated some controversy concerning the best neuroimaging test that should be indicated for the differential diagnosis of Parkinsonism. In this article, a panel of nuclear medicine and neurology experts has evaluated the functional neuroimaging techniques emphazising practical considerations related to the diagnosis of patients with uncertain origin parkinsonism and the assessment Parkinson's disease progression.

  15. Relationships between cognitive performance, neuroimaging, and vascular disease: the DHS-Mind Study

    PubMed Central

    Hsu, Fang-Chi; Raffield, Laura M.; Hugenschmidt, Christina E.; Cox, Amanda; Xu, Jianzhao; Carr, J. Jeffery; Freedman, Barry I.; Maldjian, Joseph A.; Williamson, Jeff D.; Bowden, Donald W.

    2015-01-01

    Background Type 2 diabetes mellitus increases risk for cognitive decline and dementia; elevated burdens of vascular disease are hypothesized to contribute to this risk. These relationships were examined in the Diabetes Heart Study-Mind using a battery of cognitive tests, neuroimaging measures, and subclinical cardiovascular disease (CVD) burden assessed by coronary artery calcified plaque (CAC). We hypothesized that CAC would attenuate the association between neuroimaging measures and cognition performance. Methods Associations were examined using marginal models in this family-based cohort of 572 European Americans from 263 families. All models were adjusted for age, gender, education, type 2 diabetes, and hypertension, with some neuroimaging measures additionally adjusted for intracranial volume. Results Higher total brain volume (TBV) was associated with better performance on the Digit Symbol Substitution Task (DSST) and Semantic Fluency (both p≤7.0 x 10−4). Higher gray matter volume (GMV) was associated with better performance on the Modified Mini-Mental State Examination and Semantic Fluency (both p≤9.0 x 10−4). Adjusting for CAC caused minimal changes to the results. Conclusions Relationships exist between neuroimaging measures and cognitive performance in a type 2 diabetes-enriched European American cohort. Associations were minimally attenuated after adjusting for subclinical CVD. Additional work is needed to understand how subclinical CVD burden interacts with other factors and impacts relationships between neuroimaging and cognitive testing measures. PMID:26185004

  16. Heritability and Genetic Association Analysis of Neuroimaging Measures in the Diabetes Heart Study

    PubMed Central

    Raffield, Laura M; Cox, Amanda J; Hugenschmidt, Christina E; Freedman, Barry I; Langefeld, Carl D; Williamson, Jeff D; Hsu, Fang-Chi; Maldjian, Joseph A; Bowden, Donald W

    2014-01-01

    Patients with type 2 diabetes are at increased risk of age-related cognitive decline and dementia. Neuroimaging measures such as white matter lesion volume, brain volume, and fractional anisotropy may reflect the pathogenesis of these cognitive declines, and genetic factors may contribute to variability in these measures. This study examined multiple neuroimaging measures in 465 participants from 238 families with extensive genotype data in the type 2 diabetes enriched Diabetes Heart Study-Mind cohort. Heritability of these phenotypes and their association with candidate single nucleotide polymorphisms (SNPs) and SNP data from genome-and exome-wide arrays was explored. All neuroimaging measures analysed were significantly heritable (ĥ2 =0.55–0.99 in unadjusted models). Seventeen candidate SNPs (from 16 genes/regions) associated with neuroimaging phenotypes in prior studies showed no significant evidence of association. A missense variant (rs150706952, A432V) in PLEKHG4B from the exome-wide array was significantly associated with white matter mean diffusivity (p=3.66×10−7) and gray matter mean diffusivity (p=2.14×10−7). This analysis suggests genetic factors contribute to variation in neuroimaging measures in a population enriched for metabolic disease and other associated comorbidities. PMID:25523635

  17. Reading the Freudian theory of sexual drives from a functional neuroimaging perspective

    PubMed Central

    Stoléru, Serge

    2014-01-01

    One of the essential tasks of neuropsychoanalysis is to investigate the neural correlates of sexual drives. Here, we consider the four defining characteristics of sexual drives as delineated by Freud: their pressure, aim, object, and source. We systematically examine the relations between these characteristics and the four-component neurophenomenological model that we have proposed based on functional neuroimaging studies, which comprises a cognitive, a motivational, an emotional and an autonomic/neuroendocrine component. Functional neuroimaging studies of sexual arousal (SA) have thrown a new light on the four fundamental characteristics of sexual drives by identifying their potential neural correlates. While these studies are essentially consistent with the Freudian model of drives, the main difference emerging between the functional neuroimaging perspective on sexual drives and the Freudian theory relates to the source of drives. From a functional neuroimaging perspective, sources of sexual drives, conceived by psychoanalysis as processes of excitation occurring in a peripheral organ, do not seem, at least in adult subjects, to be an essential part of the determinants of SA. It is rather the central processing of visual or genital stimuli that gives to these stimuli their sexually arousing and sexually pleasurable character. Finally, based on functional neuroimaging results, some possible improvements to the psychoanalytic theory of sexual drives are suggested. PMID:24672467

  18. [Functional neuroimaging in the diagnosis of patients with Parkinsonism: Update and recommendations for clinical use].

    PubMed

    Arbizu, J; Luquin, M R; Abella, J; de la Fuente-Fernández, R; Fernandez-Torrón, R; García-Solís, D; Garrastachu, P; Jiménez-Hoyuela, J M; Llaneza, M; Lomeña, F; Lorenzo-Bosquet, C; Martí, M J; Martinez-Castrillo, J C; Mir, P; Mitjavila, M; Ruiz-Martínez, J; Vela, L

    2014-01-01

    Functional Neuroimaging has been traditionally used in research for patients with different Parkinsonian syndromes. However, the emergence of commercial radiotracers together with the availability of single photon emission computed tomography (SPECT) and, more recently, positron emission tomography (PET) have made them available for clinical practice. Particularly, the development of clinical evidence achieved by functional neuroimaging techniques over the past two decades have motivated a progressive inclusion of several biomarkers in the clinical diagnostic criteria for neurodegenerative diseases that occur with Parkinsonism. However, the wide range of radiotracers designed to assess the involvement of different pathways in the neurodegenerative process underlying Parkinsonian syndromes (dopaminergic nigrostriatal pathway integrity, basal ganglia and cortical neuronal activity, myocardial sympathetic innervation), and the different neuroimaging techniques currently available (scintigraphy, SPECT and PET), have generated some controversy concerning the best neuroimaging test that should be indicated for the differential diagnosis of Parkinsonism. In this article, a panel of nuclear medicine and neurology experts has evaluated the functional neuroimaging techniques emphazising practical considerations related to the diagnosis of patients with uncertain origin parkinsonism and the assessment Parkinson's disease progression. PMID:24731551

  19. CAN NEUROIMAGING HELP US TO UNDERSTAND AND CLASSIFY SOMATOFORM DISORDERS? A SYSTEMATIC AND CRITICAL REVIEW

    PubMed Central

    Browning, Michael; Fletcher, Paul; Sharpe, Michael

    2011-01-01

    Objective Debate about the nature of the somatoform disorders and their current diagnostic classification has been stimulated by the anticipation of new editions of the DSM and ICD diagnostic classifications. In the current paper we systematically review the literature on the neuroimaging of somatoform disorders and related conditions with the aim of addressing two specific questions: Is there evidence of altered neural function or structure that is specifically associated with somatoform disorders? What conclusions can we draw from these findings about the etiology of somatoform disorders? Methods Studies reporting neuroimaging findings in patients with a somatoform disorder, or a functional somatic syndrome (such as Fibromyalgia) were found using Pubmed, PsycINFO and EMBASE database searches. Reported structural and functional neuroimaging findings were then extracted to form a narrative review. Results A relatively mature literature on symptoms of pain, and less developed literatures on conversion and fatigue symptoms were identified. The available evidence indicates that, when compared to non-clinical groups, somatoform diagnoses are associated with increased activity of limbic regions in response to painful stimuli and a generalized decrease in grey matter density; however methodological considerations restrict the interpretation of these findings. Conclusions While the neuroimaging literature has provided evidence about the possible mechanisms underlying somatoform disorders this is not yet sufficient to provide a basis for classification. By adopting a wider variety of experimental designs and a more dynamic approach to diagnosis there is every reason to be hopeful that neuroimaging data will play a significant role in future taxonomies. PMID:21217095

  20. Neuroimaging as a biomarker in symptom validity and performance validity testing.

    PubMed

    Bigler, Erin D

    2015-09-01

    How neuropsychological assessment findings are deemed valid has been a topic of numerous articles but few have addressed any role that neuroimaging studies could provide. Within military and various clinical samples of individuals undergoing neuropsychological evaluations, high levels of failure on measures of symptom validity testing (SVT) and/or performance validity testing (PVT) have been reported. Where 'failure' is defined as a below cut-score performance on some pre-determined set-point on a SVT/PVT measure, are such failures always indicative of invalid test findings or are there other explanations, especially based on informative neuroimaging findings? This review starts with the premise that even though the SVT/PVT task is designed to be simple and easy to perform, it nonetheless requires intact frontoparietal attention, working memory and task engagement (motivation) networks. If there is damage or pathology within any aspect of these networks as demonstrated by neuroimaging findings, the patient may perform below the cut-point as a result of the underlying damage or pathophysiology. The argument is made that neuroimaging findings should be considered as to where SVT/PVT cut-points are established and there should be much greater flexibility in SVT/PVT measures based on other personal, demographic and neuroimaging information. Several case studies are used to demonstrate these points.

  1. ABrIL - Advanced Brain Imaging Lab : a cloud based computation environment for cooperative neuroimaging projects.

    PubMed

    Neves Tafula, Sérgio M; Moreira da Silva, Nádia; Rozanski, Verena E; Silva Cunha, João Paulo

    2014-01-01

    Neuroscience is an increasingly multidisciplinary and highly cooperative field where neuroimaging plays an important role. Neuroimaging rapid evolution is demanding for a growing number of computing resources and skills that need to be put in place at every lab. Typically each group tries to setup their own servers and workstations to support their neuroimaging needs, having to learn from Operating System management to specific neuroscience software tools details before any results can be obtained from each setup. This setup and learning process is replicated in every lab, even if a strong collaboration among several groups is going on. In this paper we present a new cloud service model - Brain Imaging Application as a Service (BiAaaS) - and one of its implementation - Advanced Brain Imaging Lab (ABrIL) - in the form of an ubiquitous virtual desktop remote infrastructure that offers a set of neuroimaging computational services in an interactive neuroscientist-friendly graphical user interface (GUI). This remote desktop has been used for several multi-institution cooperative projects with different neuroscience objectives that already achieved important results, such as the contribution to a high impact paper published in the January issue of the Neuroimage journal. The ABrIL system has shown its applicability in several neuroscience projects with a relatively low-cost, promoting truly collaborative actions and speeding up project results and their clinical applicability.

  2. Linking neuroimaging signals to behavioral responses in single cases: Challenges and opportunities.

    PubMed

    Sander, Tilmann H; Zhou, Bin

    2016-09-01

    Despite rapid progress both in psychology and neuroimaging, there is still a convergence gap between the results of these two scientific disciplines. This is particularly unsatisfactory, as the variability between single subjects needs to be understood both for basic science and for patient diagnostics in, for example, the field of age-related cognitive changes. Active and passive behaviors are the observables in psychology and can be studied alone or in combination with the neuroimaging approach. Various physical signatures of brain activity are the observables in neuroimaging and can be measured concurrent with behaviors. Despite the intrinsic relationship between behaviors and the corresponding neuroimaging patterns and the obvious advantages in integrating behavioral and neuroimaging measurements, the results of combined studies can be difficult to interpret. Experiments are often optimized to yield either a novel behavioral or a novel physiological result, but rarely designed for a better match between the two. Since integrating the results is probably a key to future progress in clinical psychology and basic research, an attempt is made here to identify some difficulties and to provide some ideas for future research. PMID:27678481

  3. The forecaster's added value

    NASA Astrophysics Data System (ADS)

    Turco, M.; Milelli, M.

    2009-09-01

    skill scores of two competitive forecast. It is important to underline that the conclusions refer to the analysis of the Piemonte operational alert system, so they cannot be directly taken as universally true. But we think that some of the main lessons that can be derived from this study could be useful for the meteorological community. In details, the main conclusions are the following: - despite the overall improvement in global scale and the fact that the resolution of the limited area models has increased considerably over recent years, the QPF produced by the meteorological models involved in this study has not improved enough to allow its direct use, that is, the subjective HQPF continues to offer the best performance; - in the forecast process, the step where humans have the largest added value with respect to mathematical models, is the communication. In fact the human characterisation and communication of the forecast uncertainty to end users cannot be replaced by any computer code; - eventually, although there is no novelty in this study, we would like to show that the correct application of appropriated statistical techniques permits a better definition and quantification of the errors and, mostly important, allows a correct (unbiased) communication between forecasters and decision makers.

  4. The Road Ahead to Cure Alzheimer’s Disease: Development of Biological Markers and Neuroimaging Methods for Prevention Trials Across all Stages and Target Populations

    PubMed Central

    Cavedo, E.; Lista, S.; Khachaturian, Z.; Aisen, P.; Amouyel, P.; Herholz, K.; Jack, C.R.; Sperling, R.; Cummings, J.; Blennow, K.; O’Bryant, S.; Frisoni, G.B.; Khachaturian, A.; Kivipelto, M.; Klunk, W.; Broich, K.; Andrieu, S.; de Schotten, M. Thiebaut; Mangin, J.-F.; Lammertsma, A.A.; Johnson, K.; Teipel, S.; Drzezga, A.; Bokde, A.; Colliot, O.; Bakardjian, H.; Zetterberg, H.; Dubois, B.; Vellas, B.; Schneider, L.S.; Hampel, H.

    2015-01-01

    Alzheimer’s disease (AD) is a slowly progressing non-linear dynamic brain disease in which pathophysiological abnormalities, detectable in vivo by biological markers, precede overt clinical symptoms by many years to decades. Use of these biomarkers for the detection of early and preclinical AD has become of central importance following publication of two international expert working group’s revised criteria for the diagnosis of AD dementia, mild cognitive impairment (MCI) due to AD, prodromal AD and preclinical AD. As a consequence of matured research evidence six AD biomarkers are sufficiently validated and partly qualified to be incorporated into operationalized clinical diagnostic criteria and use in primary and secondary prevention trials. These biomarkers fall into two molecular categories: biomarkers of amyloid-beta (Aβ) deposition and plaque formation as well as of tau-protein related hyperphosphorylation and neurodegeneration. Three of the six gold-standard (“core feasible) biomarkers are neuroimaging measures and three are cerebrospinal fluid (CSF) analytes. CSF Aβ1-42 (Aβ1-42), also expressed as Aβ1-42 : Aβ1-40 ratio, T-tau, and P-tau Thr181 & Thr231 proteins have proven diagnostic accuracy and risk enhancement in prodromal MCI and AD dementia. Conversely, having all three biomarkers in the normal range rules out AD. Intermediate conditions require further patient follow-up. Magnetic resonance imaging (MRI) at increasing field strength and resolution allows detecting the evolution of distinct types of structural and functional abnormality pattern throughout early to late AD stages. Anatomical or volumetric MRI is the most widely used technique and provides local and global measures of atrophy. The revised diagnostic criteria for “prodromal AD” and “mild cognitive impairment due to AD” include hippocampal atrophy (as the fourth validated biomarker), which is considered an indicator of regional neuronal injury. Advanced image analysis

  5. Detecting Neuroimaging Biomarkers for Psychiatric Disorders: Sample Size Matters

    PubMed Central

    Schnack, Hugo G.; Kahn, René S.

    2016-01-01

    In a recent review, it was suggested that much larger cohorts are needed to prove the diagnostic value of neuroimaging biomarkers in psychiatry. While within a sample, an increase of diagnostic accuracy of schizophrenia (SZ) with number of subjects (N) has been shown, the relationship between N and accuracy is completely different between studies. Using data from a recent meta-analysis of machine learning (ML) in imaging SZ, we found that while low-N studies can reach 90% and higher accuracy, above N/2 = 50 the maximum accuracy achieved steadily drops to below 70% for N/2 > 150. We investigate the role N plays in the wide variability in accuracy results in SZ studies (63–97%). We hypothesize that the underlying cause of the decrease in accuracy with increasing N is sample heterogeneity. While smaller studies more easily include a homogeneous group of subjects (strict inclusion criteria are easily met; subjects live close to study site), larger studies inevitably need to relax the criteria/recruit from large geographic areas. A SZ prediction model based on a heterogeneous group of patients with presumably a heterogeneous pattern of structural or functional brain changes will not be able to capture the whole variety of changes, thus being limited to patterns shared by most patients. In addition to heterogeneity (sample size), we investigate other factors influencing accuracy and introduce a ML effect size. We derive a simple model of how the different factors, such as sample heterogeneity and study setup determine this ML effect size, and explain the variation in prediction accuracies found from the literature, both in cross-validation and independent sample testing. From this, we argue that smaller-N studies may reach high prediction accuracy at the cost of lower generalizability to other samples. Higher-N studies, on the other hand, will have more generalization power, but at the cost of lower accuracy. In conclusion, when comparing results from different

  6. Detecting Neuroimaging Biomarkers for Psychiatric Disorders: Sample Size Matters.

    PubMed

    Schnack, Hugo G; Kahn, René S

    2016-01-01

    In a recent review, it was suggested that much larger cohorts are needed to prove the diagnostic value of neuroimaging biomarkers in psychiatry. While within a sample, an increase of diagnostic accuracy of schizophrenia (SZ) with number of subjects (N) has been shown, the relationship between N and accuracy is completely different between studies. Using data from a recent meta-analysis of machine learning (ML) in imaging SZ, we found that while low-N studies can reach 90% and higher accuracy, above N/2 = 50 the maximum accuracy achieved steadily drops to below 70% for N/2 > 150. We investigate the role N plays in the wide variability in accuracy results in SZ studies (63-97%). We hypothesize that the underlying cause of the decrease in accuracy with increasing N is sample heterogeneity. While smaller studies more easily include a homogeneous group of subjects (strict inclusion criteria are easily met; subjects live close to study site), larger studies inevitably need to relax the criteria/recruit from large geographic areas. A SZ prediction model based on a heterogeneous group of patients with presumably a heterogeneous pattern of structural or functional brain changes will not be able to capture the whole variety of changes, thus being limited to patterns shared by most patients. In addition to heterogeneity (sample size), we investigate other factors influencing accuracy and introduce a ML effect size. We derive a simple model of how the different factors, such as sample heterogeneity and study setup determine this ML effect size, and explain the variation in prediction accuracies found from the literature, both in cross-validation and independent sample testing. From this, we argue that smaller-N studies may reach high prediction accuracy at the cost of lower generalizability to other samples. Higher-N studies, on the other hand, will have more generalization power, but at the cost of lower accuracy. In conclusion, when comparing results from different

  7. Vulnerability of Welders to Manganese Exposure – A Neuroimaging Study

    PubMed Central

    Zaiyang, Long; Yue-Ming, Jiang; Xiang-Rong, Li; William, Fadel; Jun, Xu; Chien-Lin, Yeh; Li-Ling, Long; Hai-Lan, Luo; Jaroslaw, Harezlak; James B, Murdoch; Wei, Zheng; Ulrike, Dydak

    2014-01-01

    Increased manganese (Mn) exposure is known to cause cognitive, psychiatric and motor deficits. Mn exposure occurs in different occupational settings, where the airborne Mn level and the size of respirable particulates may vary considerably. Recently the importance of the role of the cerebral cortex in Mn toxicity has been highlighted, especially in Mn-induced neuropsychological effects. In this study we used magnetic resonance imaging (MRI) to evaluate brain Mn accumulation using T1 signal intensity indices and to examine changes in brain iron content using T2* contrast, as well as magnetic resonance spectroscopy (MRS) to measure exposure-induced metabolite changes non-invasively in cortical and deep brain regions in Mn-exposed welders, Mn-exposed smelter workers and control factory workers with no measurable exposure to Mn. MRS data as well as T1 signal intensity indices and T2* values were acquired from the frontal cortex, posterior cingulate cortex, hippocampus, and thalamus. Smelters were exposed to higher air Mn levels and had a longer duration of exposure, which was reflected in higher Mn levels in erythrocytes and urine than in welders. Nonetheless, welders had more significant metabolic differences compared to controls than did the smelter workers, especially in the frontal cortex. T1 hyperintensities in the globus pallidus were observed in both Mn-exposed groups, but only welders showed significantly higher thalamic and hippocampal T1 hyperintensities, as well as significantly reduced T2* values in the frontal cortex. Our results indicate that (1) the cerebral cortex, in particular the frontal cortex, is clearly involved in Mn neurotoxic effects and (2) in spite of the lower air Mn levels and shorter duration of exposure, welders exhibit more extensive neuroimaging changes compared to controls than smelters, including measurable deposition of Mn in more brain areas. These results indicate that the type of exposure (particulate sizes, dust versus fume) and

  8. Vulnerability of welders to manganese exposure--a neuroimaging study.

    PubMed

    Long, Zaiyang; Jiang, Yue-Ming; Li, Xiang-Rong; Fadel, William; Xu, Jun; Yeh, Chien-Lin; Long, Li-Ling; Luo, Hai-Lan; Harezlak, Jaroslaw; Murdoch, James B; Zheng, Wei; Dydak, Ulrike

    2014-12-01

    Increased manganese (Mn) exposure is known to cause cognitive, psychiatric and motor deficits. Mn exposure occurs in different occupational settings, where the airborne Mn level and the size of respirable particulates may vary considerably. Recently the importance of the role of the cerebral cortex in Mn toxicity has been highlighted, especially in Mn-induced neuropsychological effects. In this study we used magnetic resonance imaging (MRI) to evaluate brain Mn accumulation using T1 signal intensity indices and to examine changes in brain iron content using T2* contrast, as well as magnetic resonance spectroscopy (MRS) to measure exposure-induced metabolite changes non-invasively in cortical and deep brain regions in Mn-exposed welders, Mn-exposed smelter workers and control factory workers with no measurable exposure to Mn. MRS data as well as T1 signal intensity indices and T2* values were acquired from the frontal cortex, posterior cingulate cortex, hippocampus, and thalamus. Smelters were exposed to higher air Mn levels and had a longer duration of exposure, which was reflected in higher Mn levels in erythrocytes and urine than in welders. Nonetheless, welders had more significant metabolic differences compared to controls than did the smelter workers, especially in the frontal cortex. T1 hyperintensities in the globus pallidus were observed in both Mn-exposed groups, but only welders showed significantly higher thalamic and hippocampal T1 hyperintensities, as well as significantly reduced T2* values in the frontal cortex. Our results indicate that (1) the cerebral cortex, in particular the frontal cortex, is clearly involved in Mn neurotoxic effects and (2) in spite of the lower air Mn levels and shorter duration of exposure, welders exhibit more extensive neuroimaging changes compared to controls than smelters, including measurable deposition of Mn in more brain areas. These results indicate that the type of exposure (particulate sizes, dust versus fume) and

  9. Multi-Parametric Neuroimaging Reproducibility: A 3T Resource Study

    PubMed Central

    Landman, Bennett A.; Huang, Alan J.; Gifford, Aliya; Vikram, Deepti S.; Lim, Issel Anne L.; Farrell, Jonathan A.D.; Bogovic, John A.; Hua, Jun; Chen, Min; Jarso, Samson; Smith, Seth A.; Joel, Suresh; Mori, Susumu; Pekar, James J.; Barker, Peter B.; Prince, Jerry L.; van Zijl, Peter C.M.

    2010-01-01

    richness of the joint distribution of intensities across imaging methods can be best assessed within the context of a particular analysis approach as opposed to a summary table. As such, all imaging data and analysis routines have been made publicly and freely available. This effort provides the neuroimaging community with a resource for optimization of algorithms that exploit the diversity of modern MRI modalities. Additionally, it establishes a baseline for continuing development and optimization of multi-parametric imaging protocols. PMID:21094686

  10. Neuroimaging studies of the striatum in cognition Part I: healthy individuals

    PubMed Central

    Provost, Jean-Sebastien; Hanganu, Alexandru; Monchi, Oury

    2015-01-01

    The striatum has traditionally mainly been associated with playing a key role in the modulation of motor functions. Indeed, lesion studies in animals and studies of some neurological conditions in humans have brought further evidence to this idea. However, better methods of investigation have raised concerns about this notion, and it was proposed that the striatum could also be involved in different types of functions including cognitive ones. Although the notion was originally a matter of debate, it is now well-accepted that the caudate nucleus contributes to cognition, while the putamen could be involved in motor functions, and to some extent in cognitive functions as well. With the arrival of modern neuroimaging techniques in the early 1990, knowledge supporting the cognitive aspect of the striatum has greatly increased, and a substantial number of scientific papers were published studying the role of the striatum in healthy individuals. For the first time, it was possible to assess the contribution of specific areas of the brain during the execution of a cognitive task. Neuroanatomical studies have described functional loops involving the striatum and the prefrontal cortex suggesting a specific interaction between these two structures. This review examines the data up to date and provides strong evidence for a specific contribution of the fronto-striatal regions in different cognitive processes, such as set-shifting, self-initiated responses, rule learning, action-contingency, and planning. Finally, a new two-level functional model involving the prefrontal cortex and the dorsal striatum is proposed suggesting an essential role of the dorsal striatum in selecting between competing potential responses or actions, and in resolving a high level of ambiguity. PMID:26500513

  11. Image quality associated with the use of an MR-compatible incubator in neonatal neuroimaging

    PubMed Central

    O’Regan, K; Filan, P; Pandit, N; Maher, M; Fanning, N

    2012-01-01

    Objectives MRI in the neonate poses significant challenges associated with patient transport and monitoring, and the potential for diminished image quality owing to patient motion. The objective of this study was to evaluate the usefulness of a dedicated MR-compatible incubator with integrated radiofrequency coils in improving image quality of MRI studies of the brain acquired in term and preterm neonates using standard MRI equipment. Methods Subjective and objective analyses of image quality of neonatal brain MR examinations were performed before and after the introduction of an MR-compatible incubator. For all studies, the signal-to-noise ratio (SNR) was calculated, image quality was graded (1–3) and each was assessed for image artefact (e.g. motion). Student's t-test and the Mann–Whitney U-test were used to compare mean SNR values. Results 39 patients were included [mean gestational age 39 weeks (range 30–42 weeks); mean postnatal age 13 days (range 1–56 days); mean weight 3.5 kg (range 1.4–4.5 kg)]. Following the introduction of the MR-compatible incubator, diagnostic quality scans increased from 50 to 89% and motion artefact decreased from 73 to 44% of studies. SNR did not increase initially, but, when using MR sequences and parameters specifically tailored for neonatal brain imaging, SNR increased from 70 to 213 (p=0.001). Conclusion Use of an MR-compatible incubator in neonatal neuroimaging provides a safe environment for MRI of the neonate and also facilitates patient monitoring and transport. When specifically tailored MR protocols are used, this results in improved image quality. PMID:22457402

  12. Multiple tasks and neuroimaging modalities increase the likelihood of detecting covert awareness in patients with disorders of consciousness.

    PubMed

    Gibson, Raechelle M; Fernández-Espejo, Davinia; Gonzalez-Lara, Laura E; Kwan, Benjamin Y; Lee, Donald H; Owen, Adrian M; Cruse, Damian

    2014-01-01

    Minimal or inconsistent behavioral responses to command make it challenging to accurately diagnose the level of awareness of a patient with a Disorder of consciousness (DOC). By identifying markers of mental imagery being covertly performed to command, functional neuroimaging (fMRI), electroencephalography (EEG) has shown that some of these patients are aware despite their lack of behavioral responsiveness. We report the findings of behavioral, fMRI, and EEG approaches to detecting command-following in a group of patients with DOC. From an initial sample of 14 patients, complete data across all tasks was obtained in six cases. Behavioral evaluations were performed with the Coma Recovery Scale-Revised. Both fMRI and EEG evaluations involved the completion of previously validated mental imagery tasks-i.e., motor imagery (EEG and fMRI) and spatial navigation imagery (fMRI). One patient exhibited statistically significant evidence of motor imagery in both the fMRI and EEG tasks, despite being unable to follow commands behaviorally. Two behaviorally non-responsive patients produced appropriate activation during the spatial navigation fMRI task. However, neither of these patients successfully completed the motor imagery tasks, likely due to specific motor area damage in at least one of these cases. A further patient demonstrated command following only in the EEG motor imagery task, and two patients did not demonstrate command following in any of the behavioral, EEG, or fMRI assessments. Due to the heterogeneity of etiology and pathology in this group, DOC patients vary in terms of their suitability for some forms of neuroimaging, the preservation of specific neural structures, and the cognitive resources that may be available to them. Assessments of a range of cognitive abilities supported by spatially-distinct brain regions and indexed by multiple neural signatures are therefore required in order to accurately characterize a patient's level of residual cognition and

  13. D-branes on AdS flux compactifications

    NASA Astrophysics Data System (ADS)

    Koerber, Paul; Martucci, Luca

    2008-01-01

    We study D-branes in Script N = 1 flux compactifications to AdS4. We derive their supersymmetry conditions and express them in terms of background generalized calibrations. Basically because AdS has a boundary, the analysis of stability is more subtle and qualitatively different from the usual case of Minkowski compactifications. For instance, stable D-branes filling AdS4 may wrap trivial internal cycles. Our analysis gives a geometric realization of the four-dimensional field theory approach of Freedman and collaborators. Furthermore, the one-to-one correspondence between the supersymmetry conditions of the background and the existence of generalized calibrations for D-branes is clarified and extended to any supersymmetric flux background that admits a time-like Killing vector and for which all fields are time-independent with respect to the associated time. As explicit examples, we discuss supersymmetric D-branes on IIA nearly Kähler AdS4 flux compactifications.

  14. Dyonic AdS black holes from magnetohydrodynamics

    NASA Astrophysics Data System (ADS)

    Caldarelli, Marco M.; Dias, Óscar J. C.; Klemm, Dietmar

    2009-03-01

    We use the AdS/CFT correspondence to argue that large dyonic black holes in anti-de Sitter spacetime are dual to stationary solutions of the equations of relativistic magnetohydrodynamics on the conformal boundary of AdS. The dyonic Kerr-Newman-AdS4 solution corresponds to a charged diamagnetic fluid not subject to any net Lorentz force, due to orthogonal magnetic and electric fields compensating each other. The conserved charges, stress tensor and R-current of the fluid are shown to be in exact agreement with the corresponding quantities of the black hole. Furthermore, we obtain stationary solutions of the Navier-Stokes equations in four dimensions, which yield predictions for (yet to be constructed) charged rotating black strings in AdS5 carrying nonvanishing momentum along the string. Finally, we consider Scherk-Schwarz reduced AdS gravity on a circle. In this theory, large black holes and black strings are dual to lumps of deconfined plasma of the associated CFT. We analyze the effects that a magnetic field introduces in the Rayleigh-Plateau instability of a plasma tube, which is holographically dual to the Gregory-Laflamme instability of a magnetically charged black string.

  15. AdS Branes from Partial Breaking of Superconformal Symmetries

    SciTech Connect

    Ivanov, E.A.

    2005-10-01

    It is shown how the static-gauge world-volume superfield actions of diverse superbranes on the AdS{sub d+1} superbackgrounds can be systematically derived from nonlinear realizations of the appropriate AdS supersymmetries. The latter are treated as superconformal symmetries of flat Minkowski superspaces of the bosonic dimension d. Examples include the N = 1 AdS{sub 4} supermembrane, which is associated with the 1/2 partial breaking of the OSp(1|4) supersymmetry down to the N = 1, d = 3 Poincare supersymmetry, and the T-duality related L3-brane on AdS{sub 5} and scalar 3-brane on AdS{sub 5} x S{sup 1}, which are associated with two different patterns of 1/2 breaking of the SU(2, 2|1) supersymmetry. Another (closely related) topic is the AdS/CFT equivalence transformation. It maps the world-volume actions of the codimension-one AdS{sub d+1} (super)branes onto the actions of the appropriate Minkowski (super)conformal field theories in the dimension d.

  16. Worldsheet dilatation operator for the AdS superstring

    NASA Astrophysics Data System (ADS)

    Ramírez, Israel; Vallilo, Brenno Carlini

    2016-05-01

    In this work we propose a systematic way to compute the logarithmic divergences of composite operators in the pure spinor description of the AdS 5 × S 5 superstring. The computations of these divergences can be summarized in terms of a dilatation operator acting on the local operators. We check our results with some important composite operators of the formalism.

  17. [Late-onset Neurodegenerative Diseases Following Traumatic Brain Injury: Chronic Traumatic Encephalopathy (CTE) and Alzheimer's Disease Secondary to TBI (AD-TBI)].

    PubMed

    Takahata, Keisuke; Tabuchi, Hajime; Mimura, Masaru

    2016-07-01

    Chronic traumatic encephalopathy (CTE) is a neurodegenerative disease, which is associated with mild repetitive traumatic brain injury (TBI). This long-term and progressive symptom due to TBI was initially called punch-drunk syndrome or dementia pugilistica, since it was believed to be associated with boxing. However, serial neuropathological studies of mild repetitive TBI in the last decade have revealed that CTE occurs not only in boxers but also in a wider population including American football players, wrestlers, and military personnel. CTE has gained large public interest owing to dramatic cases involving retired professional athletes wherein serious behavioral problems and tragic incidents were reported. Unlike mild repetitive TBI, a single episode of severe TBI can cause another type of late-onset neuropsychiatric disease including Alzheimer's disease (AD). Several epidemiological studies have shown that a single episode of severe TBI is one of the major risk factors of AD. Pathologically, both AD and CTE are characterized by abnormal accumulations of hyperphosphorylated tau proteins. However, recent neuropathological studies revealed that CTE demonstrates a unique pattern of tau pathology in neurons and astrocytes, and accumulation of other misfolded proteins such as TDP-43. Currently, no reliable biomarkers of late-onset neurodegenerative diseases following TBI are available, and a definitive diagnosis can be made only via postmortem neuropathological examination. Development in neuroimaging techniques such as tau and amyloid positron emission tomography imaging might not only enable early diagnosis of CTE, but also contribute to the interventions for prevention of late-onset neurodegenerative diseases following TBI. Further studies are necessary to elucidate the mechanisms of neurodegeneration in the living brain of patients with TBI. PMID:27395469

  18. Entanglement temperature and perturbed AdS3 geometry

    NASA Astrophysics Data System (ADS)

    Levine, G. C.; Caravan, B.

    2016-06-01

    Generalizing the first law of thermodynamics, the increase in entropy density δ S (x ) of a conformal field theory (CFT) is proportional to the increase in energy density, δ E (x ) , of a subsystem divided by a spatially dependent entanglement temperature, TE(x ) , a fixed parameter determined by the geometry of the subsystem, crossing over to thermodynamic temperature at high temperatures. In this paper we derive a generalization of the thermodynamic Clausius relation, showing that deformations of the CFT by marginal operators are associated with spatial temperature variations, δ TE(x ) , and spatial energy correlations play the role of specific heat. Using AdS/CFT duality we develop a relationship between a perturbation in the local entanglement temperature of the CFT and the perturbation of the bulk AdS metric. In two dimensions, we demonstrate a method through which direct diagonalizations of the boundary quantum theory may be used to construct geometric perturbations of AdS3 .

  19. The effects of acute alcohol administration on the human brain: insights from neuroimaging.

    PubMed

    Bjork, James M; Gilman, Jodi M

    2014-09-01

    Over the last quarter century, researchers have peered into the living human brain to develop and refine mechanistic accounts of alcohol-induced behavior, as well as neurobiological mechanisms for development and maintenance of addiction. These in vivo neuroimaging studies generally show that acute alcohol administration affects brain structures implicated in motivation and behavior control, and that chronic intoxication is correlated with structural and functional abnormalities in these same structures, where some elements of these decrements normalize with extended sobriety. In this review, we will summarize recent findings about acute human brain responses to alcohol using neuroimaging techniques, and how they might explain behavioral effects of alcohol intoxication. We then briefly address how chronic alcohol intoxication (as inferred from cross-sectional differences between various drinking populations and controls) may yield individual brain differences between drinking subjects that may confound interpretation of acute alcohol administration effects. This article is part of the Special Issue Section entitled 'Neuroimaging in Neuropharmacology'.

  20. The BrainMap strategy for standardization, sharing, and meta-analysis of neuroimaging data

    PubMed Central

    2011-01-01

    Background Neuroimaging researchers have developed rigorous community data and metadata standards that encourage meta-analysis as a method for establishing robust and meaningful convergence of knowledge of human brain structure and function. Capitalizing on these standards, the BrainMap project offers databases, software applications, and other associated tools for supporting and promoting quantitative coordinate-based meta-analysis of the structural and functional neuroimaging literature. Findings In this report, we describe recent technical updates to the project and provide an educational description for performing meta-analyses in the BrainMap environment. Conclusions The BrainMap project will continue to evolve in response to the meta-analytic needs of biomedical researchers in the structural and functional neuroimaging communities. Future work on the BrainMap project regarding software and hardware advances are also discussed. PMID:21906305

  1. What do neurologists think about their role in neuroimaging training and practice?

    PubMed

    Masdeu, J C

    1999-01-01

    In 1996, a survey of the members of the American Academy of Neurology revealed the following facts and opinions: (1) On an average month, each respondent ordered 15 computed tomography, 22 magnetic resonance imaging, 13 ultrasound and 1 single-photon emission computerized tomography studies. (2) Most respondents did not read their own studies for reimbursement, but relied on their own reading for patient management. (3) Respondents felt that neurologists are appropriate specialists to read imaging studies; however, they favored certification for neurologists credentialed in neuroimaging. (4) Organized neurology should provide certification in neuroimaging for neurologists with appropriate training and defend their right and their need to practice neuroimaging, including endovascular procedures. PMID:16173163

  2. Functional and clinical insights from neuroimaging studies in childhood-onset schizophrenia.

    PubMed

    Ordóñez, Anna E; Sastry, Nevin V; Gogtay, Nitin

    2015-08-01

    Childhood-onset schizophrenia is a rare pediatric onset psychiatric disorder continuous with and typically more severe than its adult counterpart. Neuroimaging research conducted on this population has revealed similarly severe neural abnormalities. When taken as a whole, neuroimaging research in this population shows generally decreased cortical gray matter coupled with white matter connectivity abnormalities, suggesting an anatomical basis for deficits in executive function. Subcortical abnormalities are pronounced in limbic structures, where volumetric deficits are likely related to social skill deficits, and cerebellar deficits that have been correlated to cognitive abnormalities. Structures relevant to motor processing also show a significant alteration, with volumetric increase in basal ganglia structures likely due to antipsychotic administration. Neuroimaging of this disorder shows an important clinical image of exaggerated cortical loss, altered white matter connectivity, and differences in structural development of subcortical areas during the course of development and provides important background to the disease state. PMID:26234702

  3. Functional and clinical insights from neuroimaging studies in childhood-onset schizophrenia.

    PubMed

    Ordóñez, Anna E; Sastry, Nevin V; Gogtay, Nitin

    2015-08-01

    Childhood-onset schizophrenia is a rare pediatric onset psychiatric disorder continuous with and typically more severe than its adult counterpart. Neuroimaging research conducted on this population has revealed similarly severe neural abnormalities. When taken as a whole, neuroimaging research in this population shows generally decreased cortical gray matter coupled with white matter connectivity abnormalities, suggesting an anatomical basis for deficits in executive function. Subcortical abnormalities are pronounced in limbic structures, where volumetric deficits are likely related to social skill deficits, and cerebellar deficits that have been correlated to cognitive abnormalities. Structures relevant to motor processing also show a significant alteration, with volumetric increase in basal ganglia structures likely due to antipsychotic administration. Neuroimaging of this disorder shows an important clinical image of exaggerated cortical loss, altered white matter connectivity, and differences in structural development of subcortical areas during the course of development and provides important background to the disease state.

  4. Neuroimaging of diving-related decompression illness: current knowledge and perspectives.

    PubMed

    Kamtchum Tatuene, J; Pignel, R; Pollak, P; Lovblad, K O; Kleinschmidt, A; Vargas, M I

    2014-01-01

    Diving-related decompression illness is classified into 2 main categories: arterial gas embolism and decompression sickness. The latter is further divided into types 1 and 2, depending on the clinical presentation. MR imaging is currently the most accurate neuroimaging technique available for the detection of brain and spinal cord lesions in neurologic type 2 decompression sickness. Rapid bubble formation in tissues and the bloodstream during ascent is the basic pathophysiologic mechanism in decompression illness. These bubbles can damage the central nervous system through different mechanisms, namely arterial occlusion, venous obstruction, or in situ toxicity. Neuroimaging studies of decompression sickness have reported findings associated with each of these mechanisms: some typical results are summarized and illustrated in this article. We also review the limitations of previous work and make practical methodologic suggestions for future neuroimaging studies.

  5. Suspected non-AD pathology in mild cognitive impairment.

    PubMed

    Wisse, Laura E M; Butala, Nirali; Das, Sandhitsu R; Davatzikos, Christos; Dickerson, Bradford C; Vaishnavi, Sanjeev N; Yushkevich, Paul A; Wolk, David A

    2015-12-01

    We aim to better characterize mild cognitive impairment (MCI) patients with suspected non-Alzheimer's disease (AD) pathology (SNAP) based on their longitudinal outcome, cognition, biofluid, and neuroimaging profile. MCI participants (n = 361) from ADNI-GO/2 were designated "amyloid positive" with abnormal amyloid-beta 42 levels (AMY+) and "neurodegeneration positive" (NEU+) with abnormal hippocampal volume or hypometabolism using fluorodeoxyglucose-positron emission tomography. SNAP was compared with the other MCI groups and with AMY- controls. AMY-NEU+/SNAP, 16.6%, were older than the NEU- groups but not AMY- controls. They had a lower conversion rate to AD after 24 months than AMY+NEU+ MCI participants. SNAP-MCI participants had similar amyloid-beta 42 levels, florbetapir and tau levels, but larger white matter hyperintensity volumes than AMY- controls and AMY-NEU- MCI participants. SNAP participants performed worse on all memory domains and on other cognitive domains, than AMY-NEU- participants but less so than AMY+NEU+ participants. Subthreshold levels of cerebral amyloidosis are unlikely to play a role in SNAP-MCI, but pathologies involving the hippocampus and cerebrovascular disease may underlie the neurodegeneration and cognitive impairment in this group.

  6. Suspected non-AD pathology in mild cognitive impairment.

    PubMed

    Wisse, Laura E M; Butala, Nirali; Das, Sandhitsu R; Davatzikos, Christos; Dickerson, Bradford C; Vaishnavi, Sanjeev N; Yushkevich, Paul A; Wolk, David A

    2015-12-01

    We aim to better characterize mild cognitive impairment (MCI) patients with suspected non-Alzheimer's disease (AD) pathology (SNAP) based on their longitudinal outcome, cognition, biofluid, and neuroimaging profile. MCI participants (n = 361) from ADNI-GO/2 were designated "amyloid positive" with abnormal amyloid-beta 42 levels (AMY+) and "neurodegeneration positive" (NEU+) with abnormal hippocampal volume or hypometabolism using fluorodeoxyglucose-positron emission tomography. SNAP was compared with the other MCI groups and with AMY- controls. AMY-NEU+/SNAP, 16.6%, were older than the NEU- groups but not AMY- controls. They had a lower conversion rate to AD after 24 months than AMY+NEU+ MCI participants. SNAP-MCI participants had similar amyloid-beta 42 levels, florbetapir and tau levels, but larger white matter hyperintensity volumes than AMY- controls and AMY-NEU- MCI participants. SNAP participants performed worse on all memory domains and on other cognitive domains, than AMY-NEU- participants but less so than AMY+NEU+ participants. Subthreshold levels of cerebral amyloidosis are unlikely to play a role in SNAP-MCI, but pathologies involving the hippocampus and cerebrovascular disease may underlie the neurodegeneration and cognitive impairment in this group. PMID:26422359

  7. Gene X Environment Interactions in Schizophrenia and Bipolar Disorder: Evidence from Neuroimaging

    PubMed Central

    Geoffroy, Pierre Alexis; Etain, Bruno; Houenou, Josselin

    2013-01-01

    Introduction: Schizophrenia (SZ) and Bipolar disorder (BD) are considered as severe multifactorial diseases, stemming from genetic and environmental influences. Growing evidence supports gene x environment (GxE) interactions in these disorders and neuroimaging studies can help us to understand how those factors mechanistically interact. No reviews synthesized the existing data of neuroimaging studies in these issues. Methods: We conduct a systematic review on the neuroimaging studies exploring GxE interactions relative to SZ or BD in PubMed. Results: First results of the influence of genetic and environmental risks on brain structures came from monozygotic twin pairs concordant and discordant for SZ or BD. Few structural magnetic resonance imaging (sMRI) studies have explored the GxE interactions. No other imaging methods were found. Two main GxE interactions on brain volumes have arisen. First, an interaction between genetic liability to SZ and obstetric complications on gray matter, cerebrospinal fluid, and hippocampal volumes. Second, cannabis use and genetic liability interaction effects on cortical thickness and white matter volumes. Conclusion: Combining GxE interactions and neuroimaging domains is a promising approach. Genetic risk and environmental exposures such as cannabis or obstetrical complications seem to interact leading to specific neuroimaging cerebral alterations in SZ. They are suggestive of GxE interactions that confer phenotypic abnormalities in SZ and possibly BD. We need further, larger neuroimaging studies of GxE interactions for which we may propose a framework focusing on GxE interactions data already known to have a clinical effect such as infections, early stress, urbanicity, and substance abuse. PMID:24133464

  8. Effective Ad-Hoc Committees.

    ERIC Educational Resources Information Center

    Young, David G.

    1983-01-01

    Ad-hoc committees may be symbolic, informational, or action committees. A literature survey indicates such committees' structural components include a suprasystem and three subsystems involving linkages, production, and implementation. Other variables include size, personal factors, and timing. All the factors carry implications about ad-hoc…

  9. One-loop diagrams in AdS space

    SciTech Connect

    Hung Lingyan; Shang Yanwen

    2011-01-15

    We study the complex scalar loop corrections to the boundary-boundary gauge two-point function in pure AdS space in Poincare coordinates, in the presence of boundary quadratic perturbations to the scalar. These perturbations correspond to double-trace perturbations in the dual CFT and modify the boundary conditions of the bulk scalars in AdS. We find that, in addition to the usual UV divergences, the one-loop calculation suffers from a divergence originating in the limit as the loop vertices approach the AdS horizon. We show that this type of divergence is independent of the boundary coupling; making use of this we extract the finite relative variation of the imaginary part of the loop via Cutkosky rules as the boundary perturbation varies. Applying our methods to compute the effects of a time-dependent impurity to the conductivities using the replica trick in AdS/CFT, we find that generally an IR-relevant disorder reduces the conductivity and that in the extreme low frequency limit the correction due to the impurities overwhelms the planar CFT result even though it is supposedly 1/N{sup 2} suppressed. We also comment on the more physical scenario of a time-independent impurity.

  10. Neuroimaging auditory hallucinations in schizophrenia: from neuroanatomy to neurochemistry and beyond.

    PubMed

    Allen, Paul; Modinos, Gemma; Hubl, Daniela; Shields, Gregory; Cachia, Arnaud; Jardri, Renaud; Thomas, Pierre; Woodward, Todd; Shotbolt, Paul; Plaze, Marion; Hoffman, Ralph

    2012-06-01

    Despite more than 2 decades of neuroimaging investigations, there is currently insufficient evidence to fully understand the neurobiological substrate of auditory hallucinations (AH). However, some progress has been made with imaging studies in patients with AH consistently reporting altered structure and function in speech and language, sensory, and nonsensory regions. This report provides an update of neuroimaging studies of AH with a particular emphasis on more recent anatomical, physiological, and neurochemical imaging studies. Specifically, we provide (1) a review of findings in schizophrenia and nonschizophrenia voice hearers, (2) a discussion regarding key issues that have interfered with progress, and (3) practical recommendations for future studies. PMID:22535906

  11. Neuroimaging Auditory Hallucinations in Schizophrenia: From Neuroanatomy to Neurochemistry and Beyond

    PubMed Central

    Allen, Paul; Modinos, Gemma; Hubl, Daniela; Shields, Gregory; Cachia, Arnaud; Jardri, Renaud; Thomas, Pierre; Woodward, Todd; Shotbolt, Paul; Plaze, Marion; Hoffman, Ralph

    2012-01-01

    Despite more than 2 decades of neuroimaging investigations, there is currently insufficient evidence to fully understand the neurobiological substrate of auditory hallucinations (AH). However, some progress has been made with imaging studies in patients with AH consistently reporting altered structure and function in speech and language, sensory, and nonsensory regions. This report provides an update of neuroimaging studies of AH with a particular emphasis on more recent anatomical, physiological, and neurochemical imaging studies. Specifically, we provide (1) a review of findings in schizophrenia and nonschizophrenia voice hearers, (2) a discussion regarding key issues that have interfered with progress, and (3) practical recommendations for future studies. PMID:22535906

  12. Neuroimaging studies of aggressive and violent behavior: current findings and implications for criminology and criminal justice.

    PubMed

    Bufkin, Jana L; Luttrell, Vickie R

    2005-04-01

    With the availability of new functional and structural neuroimaging techniques, researchers have begun to localize brain areas that may be dysfunctional in offenders who are aggressive and violent. Our review of 17 neuroimaging studies reveals that the areas associated with aggressive and/or violent behavioral histories, particularly impulsive acts, are located in the prefrontal cortex and the medial temporal regions. These findings are explained in the context of negative emotion regulation, and suggestions are provided concerning how such findings may affect future theoretical frameworks in criminology, crime prevention efforts, and the functioning of the criminal justice system.

  13. Inferring mental states from neuroimaging data: From reverse inference to large-scale decoding

    PubMed Central

    Poldrack, Russell A.

    2011-01-01

    A common goal of neuroimaging research is to use imaging data to identify the mental processes that are engaged when a subject performs a mental task. The use of reasoning from activation to mental functions, known as “reverse inference”, has been previously criticized on the basis that it does not take into account how selectively the area is activated by the mental process in question. In this Perspective, I outline the critique of informal reverse inference, and describe a number of new developments that provide the ability to more formally test the predictive power of neuroimaging data. PMID:22153367

  14. Subthalamic nucleus involvement in children: a neuroimaging pattern-recognition approach.

    PubMed

    Bosemani, Thangamadhan; Anghelescu, Cristina; Boltshauser, Eugen; Hoon, Alexander H; Pearl, Phillip L; Craiu, Dana; Johnston, Michael V; Huisman, Thierry A G M; Poretti, Andrea

    2014-05-01

    A neuroimaging-based pattern-recognition approach has been shown to be very helpful in the diagnosis of a wide range of pediatric central nervous system diseases. Few disorders may selectively affect the subthalamic nucleus in children including Leigh syndrome, succinic semialdehyde dehydrogenase deficiency, kernicterus, chronic end-stage liver failure and near total hypoxic-ischemic injury in the full-term neonates. The consideration of the constellation of clinical history and findings as well as additional neuroimaging findings should allow planning the appropriate diagnostic tests to make the correct diagnosis in children with involvement of the subthalamic nucleus.

  15. Prenatal Cerebellar Disruptions: Neuroimaging Spectrum of Findings in Correlation with Likely Mechanisms and Etiologies of Injury.

    PubMed

    Poretti, Andrea; Boltshauser, Eugen; Huisman, Thierry A G M

    2016-08-01

    There is increasing evidence that the cerebellum is susceptible to prenatal infections and hemorrhages and that congenital morphologic anomalies of the cerebellum may be caused by disruptive (acquired) causes. Starting from the neuroimaging pattern, this report describes a spectrum of prenatal cerebellar disruptions including cerebellar agenesis, unilateral cerebellar hypoplasia, cerebellar cleft, global cerebellar hypoplasia, and vanishing cereb