Model-free Region Of Interest Based Analysis of fMRI Data

2006 ◽  
Author(s):  
I.R. Keck ◽  
F.J. Theis ◽  
P. Gruber ◽  
E.W. Lang ◽  
J. Churan ◽  
...  
Keyword(s):  
Region Of Interest ◽  
Fmri Data ◽  
Model Free ◽  
Free Region

Optimal Model-Free Approach Based on MDL and CHL for Active Brain Identification in fMRI Data Analysis

2020 ◽  
Vol 16 ◽  
Author(s):  
Hussain A. Jaber ◽  
Ilyas Çankaya ◽  
Hadeel K. Aljobouri ◽  
Orhan M. Koçak ◽  
Oktay Algin
Keyword(s):  
Data Analysis ◽  
Time Course ◽  
Extreme Values ◽  
Statistical Parametric Mapping ◽  
Fmri Data ◽  
Cluster Center ◽  
Jaccard Coefficient ◽  
Neural Gas ◽  
Model Free ◽  
Clustering Approach

Background: Cluster analysis is a robust tool for exploring the underlining structures in data and grouping them with similar objects. In the researches of Functional Magnetic Resonance Imaging (fMRI), clustering approaches attempt to classify voxels depending on their time-course signals into a similar hemodynamic response over time. Objective: In this work, a novel unsupervised learning approach is proposed that relies on using Enhanced Neural Gas (ENG) algorithm in fMRI data for comparison with Neural Gas (NG) method, which has yet to be utilized for that aim. The ENG algorithm depends on the network structure of the NG and concentrates on an efficacious prototype-based clustering approach. Methods: The comparison outcomes on real auditory fMRI data show that ENG outperforms the NG and statistical parametric mapping (SPM) methods due to its insensitivity to the ordering of input data sequence, various initializations for selecting a set of neurons, and the existence of extreme values (outliers). The findings also prove its capability to discover the exact and real values of a cluster number effectively. Results: Four validation indices are applied to evaluate the performance of the proposed ENG method with fMRI and compare it with a clustering approach (NG algorithm) and model-based data analysis (SPM). These validation indices include the Jaccard Coefficient (JC), Receiver Operating Characteristic (ROC), Minimum Description Length (MDL) value, and Minimum Square Error (MSE). Conclusion: The ENG technique can tackle all shortcomings of NG application with fMRI data, identify the active area of the human brain effectively, and determine the locations of the cluster center based on the MDL value during the process of network learning.

scholarly journals Sensorimotor Integration in S2, PV, and Parietal Rostroventral Areas of the Human Sylvian Fissure

2007 ◽  
Vol 97 (2) ◽  
pp. 1288-1297 ◽  
Author(s):  
Leighton B. Hinkley ◽  
Leah A. Krubitzer ◽  
Srikantan S. Nagarajan ◽  
Elizabeth A. Disbrow
Keyword(s):  
Tactile Stimulus ◽  
Region Of Interest ◽  
Sylvian Fissure ◽  
Fmri Data ◽  
Movement Condition ◽  
Manual Exploration ◽  
Movement Component ◽  
The Right ◽  
Proprioceptive Inputs ◽  
Similar Location

We explored cortical fields on the upper bank of the Sylvian fissure using functional magnetic resonance imaging (fMRI) and magnetoencephalography (MEG) to measure responses to two stimulus conditions: a tactile stimulus applied to the right hand and a tactile stimulus with an additional movement component. fMRI data revealed bilateral activation in S2/PV in response to tactile stimulation alone and source localization of MEG data identified a peak latency of 122 ms in a similar location. During the tactile and movement condition, fMRI revealed bilateral activation of S2/PV and an anterior field, while MEG data contained one source at a location identical to the tactile-only condition with a latency of 96 ms and a second rostral source with a longer latency (136 ms). Furthermore, Region-of-interest analysis of fMRI data identified increased bilateral activation in S2/PV and the rostral area in the tactile and movement condition compared with the tactile only condition. An area of cortex immediately rostral to S2/PV in monkeys has been called the parietal rostroventral area (PR). Based on location, latency, and conditions under which this field was active, we have termed the rostral area of human cortex PR as well. These findings indicate that humans, like non-human primates, have a cortical field rostral to PV that processes proprioceptive inputs, both S2/PV and PR play a role in somatomotor integration necessary for manual exploration and object discrimination, and there is a temporal hierarchy of processing with S2/PV active prior to PR.

scholarly journals Phasor based single-molecule localization microscopy in 3D (pSMLM-3D): an algorithm for MHz localization rates using standard CPUs

2017 ◽  
Author(s):  
Koen J.A. Martens ◽  
Arjen N. Bader ◽  
Sander Baas ◽  
Bernd Rieger ◽  
Johannes Hohlbein
Keyword(s):  
Single Molecule ◽  
Iterative Algorithms ◽  
Region Of Interest ◽  
Depth Information ◽  
Localization Algorithm ◽  
Two Phase ◽  
Model Free ◽  
Spread Function ◽  
2D And 3D ◽  
Single Molecule Localization Microscopy

AbstractWe present a fast and model-free 2D and 3D single-molecule localization algorithm that allows more than 3 million localizations per second on a standard multi-core CPU with localization accuracies in line with the most accurate algorithms currently available. Our algorithm converts the region of interest around a point spread function (PSF) to two phase vectors (phasors) by calculating the first Fourier coefficients in both x- and y-direction. The angles of these phasors are used to localize the center of the single fluorescent emitter, and the ratio of the magnitudes of the two phasors is a measure for astigmatism, which can be used to obtain depth information (z-direction). Our approach can be used both as a stand-alone algorithm for maximizing localization speed and as a first estimator for more time consuming iterative algorithms.

Real-time fMRI data analysis using region of interest selection based on fast ICA

2011 ◽  
Author(s):  
Baoquan Xie ◽  
Xinyue Ma ◽  
Li Yao ◽  
Zhiying Long ◽  
Xiaojie Zhao
Keyword(s):  
Data Analysis ◽  
Real Time ◽  
Region Of Interest ◽  
Fmri Data ◽  
Fmri Data Analysis

scholarly journals Model testing for distinctive functional connectivity gradients with resting-state fMRI data

2018 ◽  
Author(s):  
Jonathan F. O’Rawe ◽  
Jaime S. Ide ◽  
Hoi-Chung Leung
Keyword(s):  
Functional Connectivity ◽  
Resting State ◽  
Functional Organization ◽  
Region Of Interest ◽  
Resting State Fmri ◽  
Model Testing ◽  
Fmri Data ◽  
Extensive Literature ◽  
Topographic Organization ◽  
Lateral Organization

AbstractIn accordance with the concept of topographic organization of neuroanatomical structures, there is an increased interest in estimating and delineating continuous changes in the functional connectivity patterns across neighboring voxels within a region of interest using resting-state fMRI data. Fundamental to this functional connectivity gradient analysis is the assumption that the functional organization is stable and uniform across the region of interest. To evaluate this assumption, we developed a model testing procedure to arbitrate between overlapping, shifted, or different topographic connectivity gradients across subdivisions of a structure. We tested the procedure using the striatum, a subcortical structure consisting of the caudate nucleus and putamen, in which an extensive literature, primarily from rodents and non-human primates, suggest to have a shared topographic organization of a single diagonal gradient. We found, across multiple resting state fMRI data samples of different spatial resolutions in humans, and one macaque resting state fMRI data sample, that the models with different functional connectivity gradients across the caudate and putamen was the preferred model. The model selection procedure was validated in control conditions of checkerboard subdivisions, demonstrating the expected overlapping gradient. More specifically, while we replicated the diagonal organization of the functional connectivity gradients in both the caudate and putamen, our analysis also revealed a medial-lateral organization within the caudate. Not surprisingly, performing the same analysis assuming a unitary gradient obfuscates the medial-lateral organization of the caudate, producing only a diagonal gradient. These findings demonstrate the importance of testing basic assumptions and evaluating interpretations across species. The significance of differential topographic gradients across the putamen and caudate and the medial-lateral gradient of the caudate in humans should be tested in future studies.

scholarly journals A generalized regression model for region of interest analysis of fMRI data

NeuroImage ◽  
2012 ◽  
Vol 59 (1) ◽  
pp. 502-510 ◽  
Author(s):  
Xiao-Feng Wang ◽  
Zhiguo Jiang ◽  
Janis J. Daly ◽  
Guang H. Yue
Keyword(s):  
Regression Model ◽  
Region Of Interest ◽  
Fmri Data ◽  
Generalized Regression ◽  
Generalized Regression Model

A hands-free region-of-interest selection interface for solo surgery with a wide-angle endoscope: preclinical proof of concept

2016 ◽  
Vol 31 (2) ◽  
pp. 974-980
Author(s):  
Kyunghwa Jung ◽  
Hyunseok Choi ◽  
Hanpyo Hong ◽  
Arnold Adikrishna ◽  
In-Ho Jeon ◽  
...  
Keyword(s):  
Region Of Interest ◽  
Wide Angle ◽  
Proof Of Concept ◽  
Solo Surgery ◽  
Free Region
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