1.

Record Nr.

UNINA9910137204303321

Autore

Sharon M. Kolk

Titolo

Deciphering serotonin's role in neurodevelopment / / topic editors Judith R. Homberg, Sharon M. Kolkand Dirk Schubert

Pubbl/distr/stampa

Frontiers Media SA, 2014

France : , : Frontiers Media SA, , 2014

ISBN

9782889192762 (ebook)

Descrizione fisica

1 online resource (131 pages) : illustrations

Collana

Frontiers Research Topics

Disciplina

612.8/042

Soggetti

Serotonin

Serotonin - Physiological effect

Lingua di pubblicazione

Inglese

Formato

Materiale a stampa

Livello bibliografico

Monografia

Note generali

Bibliographic Level Mode of Issuance: Monograph

Nota di bibliografia

Includes bibliographical references.

Sommario/riassunto

This Research Topic is devoted to studies pinpointing the neurodevelopmental effects of serotonin in relation to prenatal SSRI exposure, serotonin transporter gene variation, and autism/neurodevelopmental disorders, using a wide-variety of cellular and molecular neurobiological techniques like, (epi)genetics, knockout, knockdown, neuroanatomy, physiology, MRI and behaviour in rodents and humans. We especially encouraged attempts to cross-link the neurodevelopmental processes across the fields of prenatal SSRI exposure, serotonin transporter gene variation, and autism/neurodevelopmental disorders, as well as new views on the positive or beneficial effects on serotonin-mediated neurodevelopmental changes.



2.

Record Nr.

UNINA9910437975503321

Autore

March Marisa Cristina

Titolo

Advanced statistical methods for astrophysical probes of cosmology : doctoral thesis accepted by the Astrophysics Group of Imperial College London / / Marisa Cristina March

Pubbl/distr/stampa

New York, : Springer, 2013

ISBN

1-299-19786-8

3-642-35060-7

Edizione

[1st ed. 2013.]

Descrizione fisica

1 online resource (191 p.)

Collana

Springer theses : recognizing outstanding Ph.D. research, , 2190-5053

Disciplina

523.101

Soggetti

Astrophysics

Cosmology

Lingua di pubblicazione

Inglese

Formato

Materiale a stampa

Livello bibliografico

Monografia

Note generali

Description based upon print version of record.

Nota di bibliografia

Includes bibliographical references and index.

Nota di contenuto

Introduction -- Cosmology background -- Dark energy and apparent late time acceleration -- Supernovae Ia -- Statistical techniques -- Bayesian Doubt: Should we doubt the Cosmological Constant? -- Bayesian parameter inference for SNeIa data -- Robustness to Systematic Error for Future Dark Energy Probes -- Summary and Conclusions -- Index.

Sommario/riassunto

This thesis explores advanced Bayesian statistical methods for extracting key information for cosmological model selection, parameter inference and forecasting from astrophysical observations. Bayesian model selection provides a measure of how good models in a set are relative to each other - but what if the best model is missing and not included in the set? Bayesian Doubt is an approach which addresses this problem and seeks to deliver an absolute rather than a relative measure of how good a model is.   Supernovae type Ia were the first astrophysical observations to indicate the late time acceleration of the Universe - this work presents a detailed Bayesian Hierarchical Model to infer the cosmological parameters (in particular dark energy) from observations of these supernovae type Ia.