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Deep driven fMRI decoding of visual categories
[article]
2017
arXiv
pre-print
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of Kernel Canonical Correlation Analysis. ...
However building an fMRI decoder with the typical structure of Convolutional Neural Network (CNN), i.e. learning multiple level of representations, seems impractical due to lack of brain data. ...
This approach, often referred to as Multi-Voxel Pattern Analysis (MVPA), uses classification and identifies a discriminating brain pattern that can be used to predict the category of new, unseen stimuli ...
arXiv:1701.02133v1
fatcat:h2bvkw3kojcyfbqhrqrewsgwcq
Development of the Complex General Linear Model in the Fourier Domain: Application to fMRI Multiple Input-Output Evoked Responses for Single Subjects
2013
Computational and Mathematical Methods in Medicine
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A linear time-invariant model based on statistical time series analysis in the Fourier domain for single subjects is further developed and applied to functional MRI (fMRI) blood-oxygen level-dependent ...
This is especially important for experimental designs involving multiple states (either stimulus or drug induced) that may alter the form of the response function. ...
This extension enables us to analyze evoked responses fMRI BOLD data for single subjects that have multiple stimulus inputs and multiple outputs (that is repeated runs fMRI data which we will refer to ...
doi:10.1155/2013/645043
pmid:23840281
pmcid:PMC3697143
fatcat:kgzorpdy3rfvtdi2wi7wuudx2q
Modeling Adaptation Effects in fMRI Analysis
[chapter]
2009
Lecture Notes in Computer Science
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for this effect to avoid bias in fMRI detection. ...
In the fMRI experiments using visual and auditory stimuli, we observed that the adaptation effect is significantly stronger in the visual area than in the auditory area, suggesting that we must account ...
The standard analysis for rapid ER fMRI models activation as a linear system [2, 5, 9] ; the hemodynamic response to multiple input stimuli is assumed to be a superposition of the responses to individual ...
doi:10.1007/978-3-642-04268-3_124
fatcat:n7nxn5urrncmjp3zqbdaemq4ru
Computational Modeling of Responses in Human Visual Cortex
[chapter]
2015
Brain Mapping
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Many of these models are based on a stimulus-referred approach, so that the computational principles can be tested using multiple types of measurements -spanning functional MRI, intracranial recordings ...
New models are being developed to predict responses in these maps and thus clarify their functional roles. ...
For example, it is reasonable to use linear pRF models to estimate receptive field center positions when using a single bar width, even though the model does not generalize to multiple bar widths. ...
doi:10.1016/b978-0-12-397025-1.00347-x
fatcat:kqej2gekunfcthihuspeuw5tcm
Unified Framework for Robust Estimation of Brain Networks From fMRI Using Temporal and Spatial Correlation Analyses
2009
IEEE Transactions on Medical Imaging
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Evaluation for accuracy and advantages, and comparisons of the new approaches in the presented general framework are performed using both realistic synthetic data and in vivo fMRI data. ...
This paper presents a general and novel statistical framework for robust and more complete estimation of brain functional connectivity from fMRI based on correlation analyses and hypothesis testing. ...
Marden for the valuable discussions and Dr. V. Calhoun, Dr. D. Rowe, and the reviewers for their helpful comments. ...
doi:10.1109/tmi.2009.2014863
pmid:19237342
pmcid:PMC3378991
fatcat:wwo4eq56zjehpd63clztby3jpi
Analysis of fMRI Single Subject Data in the Fourier Domain Acquired Using a Multiple Input Stimulus Experimental Design
2012
Journal of Signal and Information Processing
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Statistical analysis then proceeds via regression of the convolution of the HRF with the input stimuli. ...
However fMRI data can be analyzed in the Fourier domain where the assumptions made as to the structure of the noise can be less restrictive and hypothesis tests are straightforward for single subject analysis ...
It focused on obtaining unbiased estimates of the HRF using stochastic rather than deterministic input stimuli (the usual design for fMRI experiments). ...
doi:10.4236/jsip.2012.34060
fatcat:lk52h3k5o5h4xisksz5t4b7pti
Granger mediation analysis of multiple time series with an application to fMRI
2019
Biometrics
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This paper presents Granger mediation analysis, a new framework for causal mediation analysis of multiple time series. ...
We use "Granger" to refer to VAR correlations modeled in this paper. ...
Acknowledgements We thank the editor, associate editor, and three anonymous reviewers for their very helpful comments. ...
doi:10.1111/biom.13056
pmid:31009067
fatcat:2e6ia5zhzrherdhuets3mrsfmu
Joint, Partially-joint, and Individual Independent Component Analysis in Multi-Subject fMRI Data
[article]
2019
arXiv
pre-print
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In this paper, this source model is referred to as joint/partially-joint/individual multiple datasets multidimensional (JpJI-MDM), and accordingly, a source extraction method is developed. ...
This source model improves the accuracy of source extraction methods developed for multi-subject datasets. ...
fMRI data analysis: In [18] , statistical parametric methods in the AFNI software were used to analyze activation maps and multiple regression analysis with the general linear model (GLM) was applied ...
arXiv:1909.03676v2
fatcat:rgbgfgmdfje2xi6fafdqwvqxoq
Towards Semantic fMRI Neurofeedback: Navigating among Mental States using Real-time Representational Similarity Analysis
[article]
2020
bioRxiv
pre-print
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The developed method pipeline is verified in a proof-of-concept rt-fMRI-NF study at 7 Tesla using imagery of concrete objects. ...
similarity analysis of multi-voxel patterns of brain activity. ...
Acknowledgments Icons for the Figure 1 and Figure 2 : "brain activity" by Ben Davis, "Computer" by iconcheese, "dots" by Alexander Skowalsky, "BCG matrix" by Kirby Wu, "scatter chart" by KonKapp, "Sound ...
doi:10.1101/2020.11.09.374397
fatcat:n6ox44d5pffojbiddqgszstwmy
Conserved fMRI and LFP Signals during New Associative Learning in the Human and Macaque Monkey Medial Temporal Lobe
2012
Neuron
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Despite significantly faster learning in humans relative to monkeys, we found equivalent neural signals differentiating new versus highly familiar stimuli, first stimulus presentation, trial outcome, and ...
Parallel analyses were used to examine both data sets. ...
ACKNOWLEDGMENTS We wish to acknowledge Ellen Wang for superb assistance with animal care and Dr. Yuji Naya for expert assistance with the initial local field potential (LFP) analyses. ...
doi:10.1016/j.neuron.2012.03.029
pmid:22632731
pmcid:PMC3969034
fatcat:cxgbx4cfejbpbjj3w4yr5xbbge
Predicting Brain States from fMRI Data: Incremental Functional Principal Component Regression
2007
Neural Information Processing Systems
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Application of the method on an international test benchmark for prediction of naturalistic stimuli from new and unknown fMRI data shows that the method successfully uncovers spatially distributed parts ...
The method extends the traditional multivariate regression analysis of discretized fMRI data to the domain of stochastic functional measurements, facilitating evaluation of brain responses to complex stimuli ...
We are currently extending the method with new objective functions, dimension reduction techniques and multi-target search techniques to cope with multiple (interacting) stimuli. ...
dblp:conf/nips/GhebreabSA07
fatcat:25tizlpywfgq3hb2opwrxktloa
Multivariate time series analysis of neuroscience data: some challenges and opportunities
2016
Current Opinion in Neurobiology
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Neuroimaging data may be viewed as high-dimensional multivariate time series, and analyzed using techniques from regression analysis, time series analysis and spatiotemporal analysis. ...
We discuss issues related to data quality, model specification, estimation, interpretation, dimensionality and causality. ...
The common method to estimate the coherency function is the Welch method which by segmenting the signals as a function of frequencies uses the Pearson correlation formula to construct the estimate for ...
doi:10.1016/j.conb.2015.12.006
pmid:26752736
fatcat:o2pclutonfhz7ldllozz7va4wm
Efficient modeling and inference for event-related fMRI data
2008
Computational Statistics & Data Analysis
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Second, methodologies for estimation and hypothesis testing of the HRF are developed. Simulations support the effectiveness of our proposed methods. ...
Event-related functional magnetic resonance imaging (efMRI) has emerged as a powerful technique for detecting brains' responses to presented stimuli. ...
Acknowledgements We thank Andy Alexander, Kjell Doksum, Kam-Wah Tsui and Zhengjun Zhang for helpful comments. ...
doi:10.1016/j.csda.2008.03.033
fatcat:gajlkoutq5dwlcfzq3ettwlnka
Spatial patterns and functional profiles for discovering structure in fMRI data
2008
2008 42nd Asilomar Conference on Signals, Systems and Computers
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In both applications, our methods confirm previously known results in brain mapping and point to new research directions for exploratory analysis of fMRI data. ...
We explore unsupervised, hypothesis-free methods for fMRI analysis in two different types of experiments. First, we employ clustering to identify large-scale functionally homogeneous systems. ...
Here we present our work in developing methods for exploratory fMRI analysis. ...
doi:10.1109/acssc.2008.5074650
pmid:26082607
pmcid:PMC4465961
fatcat:2sstrrvadzgqphxz6pd7erw7fi
The folding fingerprint of visual cortex reveals the timing of human V1 and V2
2010
NeuroImage
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We developed an anatomically constrained dipole search method that solves the traditional problems by combining fMRI, EEG and many stimuli that activate small cortical regions. ...
Recent techniques such as functional magnetic resonance imaging (fMRI) have successfully identified many of these areas in the human brain, but have been of limited value for revealing the temporal dynamics ...
Analysis tools standard to many vision fMRI groups were used for mapping the visual cortex. ...
doi:10.1016/j.neuroimage.2009.09.022
pmid:19778621
pmcid:PMC2818454
fatcat:kjbaftyxyjejhpapx45illir4y
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