Spatial Alignment of Functional Regions in fMRI

نویسندگان

  • Gabriel Andres Tobón
  • Polina Golland
  • Christopher J. Terman
چکیده

An essential step for discovering a common structure in brain activation regions from multi-subject fMRI data is the ability to find spatial correspondences across subjects. This has proven to be a challenging problem due to the lack of a ground truth and variability in anatomical brain structure, functional activation, and spatial locations of functional regions. Standard methods rely on the correspondences given by anatomical registration to a common space, but fail to account for spatial variability of the functional regions relative to anatomy. We develop a clustering method that relies on the alignment of both the anatomical structure and the functional landmarks. The method is shown to improve over standard group analysis techniques that rely on anatomical alignment only. The validation of our method confirms that peaks of activation exhibit consistent spatial structure. Furthermore, our work creates a framework for future testing of different metrics for similarity of brain activation regions across subjects. Thesis Supervisor: Polina Golland Title: Associate Professor

برای دانلود متن کامل این مقاله و بیش از 32 میلیون مقاله دیگر ابتدا ثبت نام کنید

ثبت نام

اگر عضو سایت هستید لطفا وارد حساب کاربری خود شوید

منابع مشابه

Brain Activity Map Extraction of Neuromyelitis Optica Patients Using Resting-State fMRI Data Based on Amplitude of Low Frequency Fluctuations and Regional Homogeneity Analysis

Introduction: Neuromyelitis Optica (NMO) is a rare inflammatory disease of the central nervous system which generally affecting the spinal cord and optic nerve. Damage to the optic nerve can result in the patient's dim vision or even blindness, while the spinal cord damage may lead to sensory and motor paralysis and the weakness of the lower limbs in the patient. Magnetic Reson...

متن کامل

Investigating the Effect of Music on Spatial Learning in a Virtual Reality Task

Background: Spatial learning and navigation is a fundamental cognitive ability consisting of multiple cognitive components. Despite intensive efforts conducted with the assistance of virtual reality technology and functional Magnetic Resonance Imaging (fMRI) modality, the music effect on this cognition and the involved neuronal mechanisms remain elusive. Objectives: We aimed to investigate the...

متن کامل

Integrating fMRI data into 3D conventional radiotherapy treatmentplanning of brain tumors

Introduction: This study was aimed to investigate the beneficial effects of functional magnetic resonance imaging (fMRI) data in treatment planning for patients with CNS tumors in order to decrease the injury of functional regions of the brain followed by increase in life quality and survival of patients. This study pursues a novel approach in planning for the treatment of brai...

متن کامل

Using functional magnetic resonance imaging (fMRI) to explore brain function: cortical representations of language critical areas

Pre-operative determination of the dominant hemisphere for speech and speech associated sensory and motor regions has been of great interest for the neurological surgeons. This dilemma has been of at most importance, but difficult to achieve, requiring either invasive (Wada test) or non-invasive methods (Brain Mapping). In the present study we have employed functional Magnetic Resonance Imaging...

متن کامل

Optimized co-registration method of Spinal cord MR Neuroimaging data analysis and application for generating multi-parameter maps

Introduction: The purpose of multimodal and co-registration In MR Neuroimaging is to fuse two or more sets images (T1, T2, fMRI, DTI, pMRI, …) for combining the different information into a composite correlated data set in order to visualization, re-alignment and generating transform to functional Matrix. Multimodal registration and motion correction in spinal cord MR Neuroimag...

متن کامل

Improving the Performance of ICA Algorithm for fMRI Simulated Data Analysis Using Temporal and Spatial Filters in the Preprocessing Phase

Introduction: The accuracy of analyzing Functional MRI (fMRI) data is usually decreases in the presence of noise and artifact sources. A common solution in for analyzing fMRI data having high noise is to use suitable preprocessing methods with the aim of data denoising. Some effects of preprocessing methods on the parametric methods such as general linear model (GLM) have previously been evalua...

متن کامل

ذخیره در منابع من


  با ذخیره ی این منبع در منابع من، دسترسی به آن را برای استفاده های بعدی آسان تر کنید

برای دانلود متن کامل این مقاله و بیش از 32 میلیون مقاله دیگر ابتدا ثبت نام کنید

ثبت نام

اگر عضو سایت هستید لطفا وارد حساب کاربری خود شوید

عنوان ژورنال:

دوره   شماره 

صفحات  -

تاریخ انتشار 2011