Statistical Parametric Mapping: The Analysis of Functional Brain Images

Statistical Parametric Mapping: The Analysis of Functional Brain Images
Author: William D. Penny
Publisher: Elsevier
Total Pages: 689
Release: 2011-04-28
Genre: Psychology
ISBN: 0080466508

In an age where the amount of data collected from brain imaging is increasing constantly, it is of critical importance to analyse those data within an accepted framework to ensure proper integration and comparison of the information collected. This book describes the ideas and procedures that underlie the analysis of signals produced by the brain. The aim is to understand how the brain works, in terms of its functional architecture and dynamics. This book provides the background and methodology for the analysis of all types of brain imaging data, from functional magnetic resonance imaging to magnetoencephalography. Critically, Statistical Parametric Mapping provides a widely accepted conceptual framework which allows treatment of all these different modalities. This rests on an understanding of the brain's functional anatomy and the way that measured signals are caused experimentally. The book takes the reader from the basic concepts underlying the analysis of neuroimaging data to cutting edge approaches that would be difficult to find in any other source. Critically, the material is presented in an incremental way so that the reader can understand the precedents for each new development. This book will be particularly useful to neuroscientists engaged in any form of brain mapping; who have to contend with the real-world problems of data analysis and understanding the techniques they are using. It is primarily a scientific treatment and a didactic introduction to the analysis of brain imaging data. It can be used as both a textbook for students and scientists starting to use the techniques, as well as a reference for practicing neuroscientists. The book also serves as a companion to the software packages that have been developed for brain imaging data analysis. - An essential reference and companion for users of the SPM software - Provides a complete description of the concepts and procedures entailed by the analysis of brain images - Offers full didactic treatment of the basic mathematics behind the analysis of brain imaging data - Stands as a compendium of all the advances in neuroimaging data analysis over the past decade - Adopts an easy to understand and incremental approach that takes the reader from basic statistics to state of the art approaches such as Variational Bayes - Structured treatment of data analysis issues that links different modalities and models - Includes a series of appendices and tutorial-style chapters that makes even the most sophisticated approaches accessible

Statistical Analysis of fMRI Data, second edition

Statistical Analysis of fMRI Data, second edition
Author: F. Gregory Ashby
Publisher: MIT Press
Total Pages: 569
Release: 2019-09-17
Genre: Medical
ISBN: 0262042681

A guide to all aspects of experimental design and data analysis for fMRI experiments, completely revised and updated for the second edition. Functional magnetic resonance imaging (fMRI), which allows researchers to observe neural activity in the human brain noninvasively, has revolutionized the scientific study of the mind. An fMRI experiment produces massive amounts of highly complex data for researchers to analyze. This book describes all aspects of experimental design and data analysis for fMRI experiments, covering every step—from preprocessing to advanced methods for assessing functional connectivity—as well as the most popular multivariate approaches. The goal is not to describe which buttons to push in the popular software packages but to help researchers understand the basic underlying logic, the assumptions, the strengths and weaknesses, and the appropriateness of each method. The field of fMRI research has advanced dramatically in recent years, in both methodology and technology, and this second edition has been completely revised and updated. Six new chapters cover experimental design, functional connectivity analysis through the methods of psychophysiological interactions and beta-series regression, decoding using multi-voxel pattern analysis, dynamic causal modeling, and representational similarity analysis. Other chapters offer new material on recently discovered problems related to head movements, the multivariate GLM, meta-analysis, and other topics. All complex derivations now appear at the end of the relevant chapter to improve readability. A new appendix describes how to build a design matrix with effect coding for group analysis. As in the first edition, MATLAB code is provided with which readers can implement many of the methods described.

Functional Neuroimaging

Functional Neuroimaging
Author: Andrei I. Holodny
Publisher: CRC Press
Total Pages: 360
Release: 2019-04-23
Genre: Medical
ISBN: 0429524773

The first text designed specifically with clinical practitioners in mind, Functional Neuroimaging demonstrates the clinical application and utilization of functional neuroradiology for early diagnosis, neurological decision-making, and assessing response to cancer therapy. Edited by the Founding President of American Society of Functional Neuroradi

Psychoanalytical neuroscience: Exploring psychoanalytic concepts with neuroscientific methods

Psychoanalytical neuroscience: Exploring psychoanalytic concepts with neuroscientific methods
Author: Nikolai Axmacher
Publisher: Frontiers E-books
Total Pages: 179
Release: 2015-01-09
Genre: Cognitive neuroscience
ISBN: 2889193772

Sigmund Freud was a trained neuroanatomist and wrote his first psychoanalytical theory in neuroscientific terms. Throughout his life, he maintained the belief that at some distant day in the future, all psychoanalytic processes could be tied to a neural basis: "We must recollect that all of our provisional ideas in psychology will presumably one day be based on an organic substructure" (Freud 1914, On Narcissism: An Introduction). Fundamental Freudian concepts reveal their foundation in the physiological science of his time, most importantly among them the concept of libidinous energy and the homeostatic "principle of constancy". However, the subsequent history of psychoanalysis and neuroscience was mainly characterized by mutual ignorance or even opposition; many scientists accused psychoanalytic viewpoints not to be scientifically testable, and many psychoanalysts claimed that their theories did not need empirical support outside of the therapeutic situation. On this historical background, it may appear surprising that the recent years have seen an increasing interest in re-connecting psychoanalysis and neuroscience in various ways: By studying psychodynamic consequences of brain lesions in neurological patients, by investigating how psychoanalytic therapy affects brain structure and function, or even by operationalizing psychoanalytic concepts in well-controlled experiments and exploring their neural correlates. These empirical studies are accompanied by theoretical work on the philosophical status of the "neuropsychoanalytic" endeavour. In this volume, we attempt to provide a state-of-the-art overview of this new exciting field. All types of submissions are welcome, including research in patient populations, healthy human participants and animals, review articles on some empirical or theoretical aspect, and of course also critical accounts of the new field. Despite this welcome variability, we would like to suggest that all contributions attempt to address one (or both) of two main questions, which should motivate the connection between psychoanalysis and neuroscience and that in our opinion still remain exigent: First, from the neuroscientific side, why should researchers in the neurosciences address psychoanalytic ideas, and what is (or will be) the impact of this connection on current neuroscientific theories? Second, from the psychoanalytic side, why should psychoanalysts care about neuroscientific studies, and (how) can current psychoanalytical theory and practice benefit from their results? Of course, contributors are free to provide a critical viewpoint on these two questions as well.

New Insights into Brain Imaging Methods for Rehabilitation of Brain Diseases

New Insights into Brain Imaging Methods for Rehabilitation of Brain Diseases
Author: Guang-qing Xu
Publisher: Frontiers Media SA
Total Pages: 199
Release: 2024-03-28
Genre: Science
ISBN: 2832546978

Brain diseases such as stroke, Alzheimer's disease, and Parkinson's disease cause dysfunction in multiple body systems. Motor dysfunction, cognitive impairment, dysphagia, and emotion disorders are frequently observed in patients with brain diseases. As the dysfunctions are associated with alterations in the brain, brain imaging methods such as functional MRI (fMRI), electroencephalography (EEG), functional near-infrared spectroscopy (fNIRS), and transcranial magnetic stimulation (TMS) are essential for investigating the neural mechanisms underlying the dysfunction caused by brain diseases. Brain imaging methods are also critical for understanding the neural mechanisms for the effectiveness of therapeutic or rehabilitative interventions that promote recovery from brain diseases. The usage of these brain imaging methods would deepen our understanding of brain diseases and potentially translate this knowledge to improve effectiveness of rehabilitative interventions for brain diseases.

Recent Advances and the Future Generation of Neuroinformatics Infrastructure

Recent Advances and the Future Generation of Neuroinformatics Infrastructure
Author: Xi Cheng
Publisher: Frontiers Media SA
Total Pages: 390
Release: 2015-12-11
Genre: Neurosciences. Biological psychiatry. Neuropsychiatry
ISBN: 2889196771

The huge volume of multi-modal neuroimaging data across different neuroscience communities has posed a daunting challenge to traditional methods of data sharing, data archiving, data processing and data analysis. Neuroinformatics plays a crucial role in creating advanced methodologies and tools for the handling of varied and heterogeneous datasets in order to better understand the structure and function of the brain. These tools and methodologies not only enhance data collection, analysis, integration, interpretation, modeling, and dissemination of data, but also promote data sharing and collaboration. This Neuroinformatics Research Topic aims to summarize the state-of-art of the current achievements and explores the directions for the future generation of neuroinformatics infrastructure. The publications present solutions for data archiving, data processing and workflow, data mining, and system integration methodologies. Some of the systems presented are large in scale, geographically distributed, and already have a well-established user community. Some discuss opportunities and methodologies that facilitate large-scale parallel data processing tasks under a heterogeneous computational environment. We wish to stimulate on-going discussions at the level of the neuroinformatics infrastructure including the common challenges, new technologies of maximum benefit, key features of next generation infrastructure, etc. We have asked leading research groups from different research areas of neuroscience/neuroimaging to provide their thoughts on the development of a state of the art and highly-efficient neuroinformatics infrastructure. Such discussions will inspire and help guide the development of a state of the art, highly-efficient neuroinformatics infrastructure.