4,090 Hits in 10.8 sec

Model-free functional MRI analysis using cluster-based methods

Thomas D. Otto, Anke Meyer-Baese, Monica Hurdal, DeWitt Sumners, Dorothee Auer, Axel Wismuller, Kevin L. Priddy, Peter J. Angeline
2003 Intelligent Computing: Theory and Applications  
A comparison of this new method with Kohonen's self-organizing map and with a minimal free energy vector quantizer is done in a systematic fMRI study showing comparative quantitative evaluations.  ...  Conventional model-based or statistical analysis methods for functional MItT (fMRI) are easy to implement, and are effective in analyzing data with simple paradigms.  ...  KOHONEN'S SELF-ORGANIZING MAP Kohonen's self-organizing map generates nodes on a two-dimensional lattice in which the distribution of these nodes corresponds to the proximity of their associated node patterns  ... 
doi:10.1117/12.487254 fatcat:wawh4i6hqjhzjbz46zsg4j2jum

Unsupervised Spatiotemporal Analysis of FMRI Data Using Graph-Based Visualizations of Self-Organizing Maps

Santosh B. Katwal, John C. Gore, Rene Marois, Baxter P. Rogers
2013 IEEE Transactions on Biomedical Engineering  
We conclude that the graph-based visualizations of self-organizing maps help in advanced visualization of cluster boundaries in fMRI data enabling the separation of regions with small differences in the  ...  In this paper, we used graph-based visualizations to capture fMRI data features based upon 1) the distribution of data across the receptive fields of the prototypes (density-based connectivity); and 2)  ...  Tombu for assistance with fMRI data preparation.  ... 
doi:10.1109/tbme.2013.2258344 pmid:23613020 pmcid:PMC3919688 fatcat:l5nkuvsbcrgz5dr3gnjtdp3spy

Model-free functional MRI analysis based on unsupervised clustering

Axel Wismüller, Anke Meyer-Bäse, Oliver Lange, Dorothee Auer, Maximilian F. Reiser, DeWitt Sumners
2004 Journal of Biomedical Informatics  
A comparison of this new method with KohonenÕs self-organizing map and with a fuzzy clustering scheme based on deterministic annealing is done in a systematic fMRI study showing comparative quantitative  ...  Conventional model-based or statistical analysis methods for functional MRI (fMRI) are easy to implement, and are effective in analyzing data with simple paradigms.  ...  Acknowledgment The authors greatly appreciate the programming efforts of Thomas Dan Otto.  ... 
doi:10.1016/j.jbi.2003.12.002 pmid:15016382 fatcat:ifzdabczuvgojc4oxjg3edcjka

Measuring relative timings of brain activities using fMRI

Santosh B. Katwal, John C. Gore, J. Christopher Gatenby, Baxter P. Rogers
2013 NeuroImage  
To maximize sensitivity, we used high spatial and temporal resolution fMRI at ultrahigh field (7 Tesla), in conjunction with a novel datadriven technique for voxel selection using graph-based visualizations  ...  of self-organizing maps and Granger causality to measure relative timing.  ...  Acknowledgments This research was supported by National Institutes of Health, NIH 5R01EB000461 (Principal Investigator JCG).  ... 
doi:10.1016/j.neuroimage.2012.10.052 pmid:23110880 pmcid:PMC3593774 fatcat:ujrjmzhx25didhn5awz4ofbipy

The Effects of Alcohol on the Nonhuman Primate Brain: A Network Science Approach to Neuroimaging

Qawi K. Telesford, Paul J. Laurienti, David P. Friedman, Robert A. Kraft, James B. Daunais
2013 Alcoholism: Clinical and Experimental Research  
In this study we used network science to build NHP brain networks from fMRI data to understand the basic functional organization of the NHP brain.  ...  Under an acute ethanol challenge, the functional organization of the brain was significantly impacted.  ...  The field was further driven by the introduction of functional connectivity in fMRI to analyze the coherence of signals in the brain (Biswal et al., 1995 , Biswal et al., 1997 , Lowe et al., 1998 .  ... 
doi:10.1111/acer.12181 pmid:23905720 pmcid:PMC3812370 fatcat:xndfz6hb2jb35l4ldn2lcojzyq

Self-organizing maps and entropy applied to data analysis of functional magnetic resonance images

Anderson D. S. Campelo, Valcir J. C. Farias, Heliton R. Tavares, Marcus P. da C. da Rocha
2014 Applied Mathematical Sciences  
Kohonen self-organizing maps (SOM) and Shannon entropy were applied together for the analysis of data from functional magnetic resonance imaging (fMRI).  ...  The procedure with these techniques was applied to simulated data and on real hearing experiment, the results showed that the application of entropy and SOM is a good tool to the identification of areas  ...  Self-organizing maps and entropy 4957 2.2 Self-Organizing Maps FMRI data was analyzed with Kohonen´s SOM [26] using an implementation available in the literature [6, 21, 22] .  ... 
doi:10.12988/ams.2014.310585 fatcat:wxdgy4zrwncidmbyulwuyb4e74

fMRI Brain Decoding and Its Applications in Brain–Computer Interface: A Survey

Bing Du, Xiaomu Cheng, Yiping Duan, Huansheng Ning
2022 Brain Sciences  
With the great success of deep learning on image recognition and generation, deep neural networks (DNN) have been engaged in reconstructing visual stimuli from human brain activity via functional magnetic  ...  Specifically, we focused on current brain activity decoding models with high attention: variational auto-encoder (VAE), generative confrontation network (GAN), and the graph convolutional network (GCN)  ...  Data Availability Statement: Not applicable. Conflicts of Interest: The authors declare no conflict of interest.  ... 
doi:10.3390/brainsci12020228 pmid:35203991 pmcid:PMC8869956 fatcat:t664eccq6nh5plnvhac2r2gcpa

Spatio-Temporal Graph Convolution for Resting-State fMRI Analysis [article]

Soham Gadgil, Qingyu Zhao, Adolf Pfefferbaum, Edith V. Sullivan, Ehsan Adeli, Kilian M. Pohl
2021 arXiv   pre-print
In analyzing the rs-fMRI of the Human Connectome Project (HCP, N=1,091) and the National Consortium on Alcohol and Neurodevelopment in Adolescence (NCANDA, N=773), ST-GCN is significantly more accurate  ...  The Blood-Oxygen-Level-Dependent (BOLD) signal of resting-state fMRI (rs-fMRI) records the temporal dynamics of intrinsic functional networks in the brain.  ...  Conclusion We introduced a framework for analyzing rs-fMRI data based on spatio-temporal graph convolution networks.  ... 
arXiv:2003.10613v3 fatcat:4qdp26d6sfdvfgd5ss7bh7nyg4

A Survey of Graph Based Complex Brain Network Analysis Using Functional and Diffusional MRI

Md Rafiqul Islam, Xiaoxia Yin, Anwaar Ulhaq, Yanchun Zhang, Hua Wang, Noreen Anjum, Tomas Kron
2017 American Journal of Applied Sciences  
The graph based techniques of brain complex networks have been successfully used in various types of image and medical data analysis.  ...  In this survey paper, we focus on a comprehensive study of the analytical methods for complex brain network based on graph theory.  ...  Acknowledgement We would like to thank the anonymous reviewers and editor for their constructive comments and suggestions on earlier version of this paper.  ... 
doi:10.3844/ajassp.2017.1186.1208 fatcat:qc2lydwqpjgkjhru34726c64wy

Towards a new approach to reveal dynamical organization of the brain using topological data analysis

Manish Saggar, Olaf Sporns, Javier Gonzalez-Castillo, Peter A. Bandettini, Gunnar Carlsson, Gary Glover, Allan L. Reiss
2018 Nature Communications  
Here we use Topological Data Analysis to reveal the overall organization of whole-brain activity maps at a single-participant level-as an interactive representation-without arbitrarily collapsing data  ...  Most previous work has focused on analyzing changes in co-fluctuations between a set of brain regions over several temporal segments of the data.  ...  The second dataset was originally collected as part of the Human Connectome Project (HCP 35 ) while participants performed working-memory tasks.  ... 
doi:10.1038/s41467-018-03664-4 pmid:29643350 pmcid:PMC5895632 fatcat:cxbund33zjbf3ilvlenezp5rye

Detection of functional activity in brain white matter using fiber architecture informed synchrony mapping [article]

Yu Zhao, Yurui Gao, Zhongliang Zu, Muwei Li, Kurt Schilling, Adam Anderson, John Gore
2022 bioRxiv   pre-print
The maps of brain activity produced reflect the magnitude of local BOLD responses.  ...  A general linear model is widely used for analyzing fMRI data, in which the blood oxygenation-level dependent (BOLD) signals in gray matter (GM) evoked in response to neural stimulation are modeled by  ...  Based on the GSP framework, we analyze fMRI time courses at a discrete set of positions, which form a set of vertices of a topological graph, in such a way that underlying constraints from fiber architectures  ... 
doi:10.1101/2022.02.23.481698 fatcat:rmwbj4fjqvhappfef4so66djli

A Novel Brain Decoding Method: a Correlation Network Framework for Revealing Brain Connections [article]

Siyu Yu, Nanning Zheng, Yongqiang Ma, Hao Wu, Badong Chen
2017 arXiv   pre-print
Analyzing the correlations of collected data from human brain activities and representing activity patterns are two problems in brain decoding based on functional magnetic resonance imaging (fMRI) signals  ...  Therefore, we proposed a correlation network (CorrNet) framework that could be flexibly combined with diverse pattern representation models.  ...  Complex brain activity states with limited data instances make it necessary to analyze the correlations between fMRI signals and visual stimuli.  ... 
arXiv:1712.01668v1 fatcat:pkmzwuuq7vgezdtlmpg4h6kohi

Multimodal Integration of fMRI and EEG Data for High Spatial and Temporal Resolution Analysis of Brain Networks

D. Mantini, L. Marzetti, M. Corbetta, G. L. Romani, C. Del Gratta
2010 Brain Topography  
We propose an approach based on the integration of EEG and fMRI, enabling the EEG temporal dynamics of information processing to be characterized within spatially well-defined fMRI large-scale networks  ...  The proposed approach has been evaluated on visual target detection data.  ...  Acknowledgments The authors wish to thank Simone Cugini and Mauro Gianni Perrucci for technical assistance and data acquisition.  ... 
doi:10.1007/s10548-009-0132-3 pmid:20052528 pmcid:PMC5682027 fatcat:fvrydzcojjdnjfikv7k27mokaq

A human brain atlas derived via n-cut parcellation of resting-state and task-based fMRI data

George Andrew James, Onder Hazaroglu, Keith A. Bush
2016 Magnetic Resonance Imaging  
Our findings indicate that atlases derived from parcellation of task-based and resting-state fMRI data are highly comparable, and existing resting-state atlases are suitable for task-based analyses.  ...  But given that functional connectivity between regions varies with task, we hypothesized that an atlas incorporating both resting-state and task-based fMRI data would produce an atlas with finer characterization  ...  Sonet Smitherman for assistance with data collection and maintaining institutional compliance. All authors contributed to the interpretation and writing of this manuscript.  ... 
doi:10.1016/j.mri.2015.10.036 pmid:26523655 pmcid:PMC4837649 fatcat:kjdcnl6o6fe2rjniktmh4rozlq

Precision Functional Mapping of Individual Human Brains

Evan M. Gordon, Timothy O. Laumann, Adrian W. Gilmore, Dillan J. Newbold, Deanna J. Greene, Jeffrey J. Berg, Mario Ortega, Catherine Hoyt-Drazen, Caterina Gratton, Haoxin Sun, Jacqueline M. Hampton, Rebecca S. Coalson (+8 others)
2017 Neuron  
Human functional MRI (fMRI) research primarily focuses on analyzing data averaged across groups, which limits the detail, specificity, and clinical utility of fMRI resting-state functional connectivity  ...  To push our understanding of functional brain organization to the level of individual humans, we assembled a novel MRI dataset containing five hours of RSFC data, six hours of task fMRI, multiple structural  ...  Acknowledgments This work was supported by National Institutes of Health Grants NS088590, TR000448 (NUFD),  ... 
doi:10.1016/j.neuron.2017.07.011 pmid:28757305 pmcid:PMC5576360 fatcat:avmog6q75ralfkje3qq57l7jvu
« Previous Showing results 1 — 15 out of 4,090 results