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Inferring consistent functional interaction patterns from natural stimulus FMRI data

Jiehuan Sun, Xintao Hu, Xiu Huang, Yang Liu, Kaiming Li, Xiang Li, Junwei Han, Lei Guo, Tianming Liu, Jing Zhang
2012 NeuroImage  
Along this direction, this paper presents our effort in inferring consistent and reproducible functional interaction patterns under natural stimulus of video watching among known functional brain regions  ...  In particular, these consistent functional interaction patterns are supported by structural connections derived from diffusion tensor imaging (DTI) data, suggesting the structural underpinnings of consistent  ...  X Hu was supported by the National Natural Science Foundation of China (61103061) and the Postdoctoral Foundation of China (20110490174).  ... 
doi:10.1016/j.neuroimage.2012.01.142 pmid:22440644 pmcid:PMC3929522 fatcat:upshw56plren5ieily2m4uilku

Detecting Brain State Changes via Fiber-Centered Functional Connectivity Analysis

Xiang Li, Chulwoo Lim, Kaiming Li, Lei Guo, Tianming Liu
2012 Neuroinformatics  
Our extensive experimental results have shown that meaningful brain state change points can be detected in task-based fMRI/DTI, resting state fMRI/DTI, and natural stimulus fMRI/DTI data sets.  ...  interactions and dynamics.  ...  Parts of the OSPAN working memory fMRI data sets were provided by Carlos Faraco and L. Stephen Miller.  ... 
doi:10.1007/s12021-012-9157-y pmid:22941508 pmcid:PMC3908655 fatcat:bhgwrg4ysjhn3m7v3qp6pg3n44

Dependencies between stimuli and spatially independent fMRI sources: Towards brain correlates of natural stimuli

Jarkko Ylipaavalniemi, Eerika Savia, Sanna Malinen, Riitta Hari, Ricardo Vigário, Samuel Kaski
2009 NeuroImage  
The detected complex activation patterns were explained as resulting from interactions of multiple brain processes. Our approach seems promising for analysis of data from studies with natural stimuli.  ...  Natural stimuli are increasingly used in functional magnetic resonance imaging (fMRI) studies to imitate real-life situations.  ...  Acknowledgments We thank Yevhen Hlushchuk (Brain Research Unit, Low Temperature Laboratory, Helsinki University of Technology) for collaboration in the original fMRI study.  ... 
doi:10.1016/j.neuroimage.2009.03.056 pmid:19344775 fatcat:kdike4btrbahvpjxkqlplpozim

Linear Systems Analysis of Functional Magnetic Resonance Imaging in Human V1

Geoffrey M. Boynton, Stephen A. Engel, Gary H. Glover, David J. Heeger
1996 Journal of Neuroscience  
A typical fMRI experiment measures the correlation between the fMRI response and a stimulus. From this, scientists hope to infer something about neural activity.  ...  Because the linear transform model is consistent with our data, we proceeded to estimate the temporal fMRI impulse-response function and the underlying (presumably neural) contrast-response function of  ...  Contrast-response function The linear transform model of fMRI responses allows us to infer neural contrast-response functions from fMRI data (Fig. 13) .  ... 
doi:10.1523/jneurosci.16-13-04207.1996 pmid:8753882 fatcat:styoe27u2zg5vjldwsvhcvfgaq

Categories and Functional Units: An Infinite Hierarchical Model for Brain Activations

Danial Lashkari, Ramesh Sridharan, Polina Golland
2010 Advances in Neural Information Processing Systems  
When applied to data from an fMRI study of object recognition, the method finds meaningful and consistent clusterings of stimuli into categories and voxels into units.  ...  A variational inference algorithm derived based on the model learns categories, units, and a set of unit-category activation probabilities from data.  ...  Acknowledgments We thank Ed Vul, Po-Jang Hsieh, and Nancy Kanwisher for the insight they have offered us throughout our collaboration, and also for providing the fMRI data.  ... 
pmid:24839377 pmcid:PMC4022600 fatcat:6dybjwn3gjeprpocrjbaew6a7u

Spikes versus BOLD: what does neuroimaging tell us about neuronal activity?

David J. Heeger, Alex C. Huk, Wilson S. Geisler, Duane G. Albrecht
2000 Nature Neuroscience  
If that were true, then it would allow us to make direct inferences about firing rates from fMRI data.  ...  If that were true, the interpretation of fMRI data would be confounded.  ...  If that were true, then it would allow us to make direct inferences about firing rates from fMRI data.  ... 
doi:10.1038/76572 pmid:10862687 fatcat:ef74eeyyojg5njdr5whcvhyq5y

Pattern-information fMRI: New questions which it opens up and challenges which face it

Rajeev D. S. Raizada, Nikolaus Kriegeskorte
2010 International journal of imaging systems and technology (Print)  
The open challenges that we discuss are as follows: inferring the causal role of pattern information, seeking diagnostic power for fMRI at the level of individuals, determining whether observed patterns  ...  have real functional significance, finding the structure underlying high-dimensional activation spaces, and relating one person's neural patterns to another's.  ...  e.g. turning them on and off) and observing consistent changes in fMRI responses, we can infer that the stimuli were causally involved in triggering the responses.  ... 
doi:10.1002/ima.20225 fatcat:yydbg4dswngzbpee7ejq5jaxi4

Computational approaches to fMRI analysis

Jonathan D Cohen, Nathaniel Daw, Barbara Engelhardt, Uri Hasson, Kai Li, Yael Niv, Kenneth A Norman, Jonathan Pillow, Peter J Ramadge, Nicholas B Turk-Browne, Theodore L Willke
2017 Nature Neuroscience  
As opposed to univariate methods, which examine individual voxels or regions, multivoxel pattern analysis (MVPA) considers spatial patterns of activity over ensembles of voxels to recover what information  ...  Adapted with permission from ref. 96 , Nature Partner Journals. Schematic of model-based fMRI.  ...  Adapted with permission from ref. 65, Curran Associates, Inc. Figure 6 6 Functional interactions within and between participants.  ... 
doi:10.1038/nn.4499 pmid:28230848 pmcid:PMC5457304 fatcat:y2ufetiszzaufgwa3h2xhkjw3m

Searching for "the Top" in Top-Down Control

Brian T. Miller, Mark D'Esposito
2005 Neuron  
In this review, we highlight direct evidence for this view of PFC function and discuss several lines of other supportive findings.  ...  These fMRI patterns corroborate the relative timing measures discussed in the single-unit data above and provide further evidence that memoryguided decisions involve a top-down interaction between the  ...  Consequently, causal inferences are assumed a priori rather than in a data-driven manner.  ... 
doi:10.1016/j.neuron.2005.11.002 pmid:16301170 fatcat:cpzmjx4u3vgeppgwkuiapnxyk4

Pattern-information analysis: From stimulus decoding to computational-model testing

Nikolaus Kriegeskorte
2011 NeuroImage  
Abstract Pattern-information analysis has become an important new paradigm in functional imaging.  ...  Citation: Kriegeskorte N (in press) Pattern-information analysis: from stimulus decoding to computational-model testing. NeuroImage.  ...  The cited studies have shown that reconstructions that deserve to be called such are possible from fMRI data.  ... 
doi:10.1016/j.neuroimage.2011.01.061 pmid:21281719 fatcat:pbloc55h3nfgva3c7ag6lr65ay

Hippocampal-neocortical interactions sharpen over time for predictive actions

Nicholas C. Hindy, Emily W. Avery, Nicholas B. Turk-Browne
2019 Nature Communications  
We use high-resolution fMRI and a dual-training behavioral paradigm to examine how the hippocampus interacts with visual cortex during predictive and nonpredictive actions learned either three days earlier  ...  These expectations can result from retrieval of action-outcome associations in the hippocampus and the reinstatement of anticipated outcomes in visual cortex.  ...  Fig. 1 Design and RT. a The first training session was proctored 3 days before the fMRI scan, while the second training session was proctored immediately Acknowledgements This work was supported by NIH  ... 
doi:10.1038/s41467-019-12016-9 pmid:31488845 pmcid:PMC6728336 fatcat:s7bjieue6zdqbdtubyoul6lwbm

Bayesian Inference for Functional Dynamics Exploring in fMRI Data

Xuan Guo, Bing Liu, Le Chen, Guantao Chen, Yi Pan, Jing Zhang
2016 Computational and Mathematical Methods in Medicine  
functional interaction patterns based on corresponding temporal boundaries.  ...  Particularly, we focus on one specific long-standing challenge in the computational modeling of fMRI datasets: how to effectively explore typical functional interactions from fMRI time series and the corresponding  ...  Acknowledgments The authors are grateful for support from Georgia State University Brains-Behavior Seed grant.  ... 
doi:10.1155/2016/3279050 pmid:27034708 pmcid:PMC4791514 fatcat:goiphn32andxto2ohh6kw26voq

Recognition Alters the Spatial Pattern of fMRI Activation in Early Retinotopic Cortex

P.-J. Hsieh, E. Vul, N. Kanwisher
2010 Journal of Neurophysiology  
Recognition alters the spatial pattern of fMRI activation in early retinotopic cortex.  ...  Here we used functional magnetic resonance imaging pattern analyses to ask whether the representation of an object in early retinotopic cortex changes when the object is recognized compared with when the  ...  Spatial patterns were extracted from each set of data (Mooney1, Photo, and Mooney2) separately for each combination of ROI and stimulus type (e.g., fish vs. camel).  ... 
doi:10.1152/jn.00812.2009 pmid:20071627 pmcid:PMC3257064 fatcat:gx6tukyj4zf7pmfffwezgw3j6q

Multimodal Functional Network Connectivity: An EEG-fMRI Fusion in Network Space

Xu Lei, Dirk Ostwald, Jiehui Hu, Chuan Qiu, Camillo Porcaro, Andrew P. Bagshaw, Dezhong Yao, Pedro Antonio Valdes-Sosa
2011 PLoS ONE  
Identifying network interaction from the complementary neuroelectric and hemodynamic signals may help to explain the complex relationships between different brain regions.  ...  EEG and fMRI recordings measure the functional activity of multiple coherent networks distributed in the cerebral cortex.  ...  Theory Multimodal functional network connectivity (mFNC) is a natural extension of fMRI FNC to cover the interaction among EEG FNs and to further explore the spatial matching between different modalities  ... 
doi:10.1371/journal.pone.0024642 pmid:21961040 pmcid:PMC3178514 fatcat:4t3i6k6mvvdnlojyxdr5dukhka

Bayesian models for functional magnetic resonance imaging data analysis

Linlin Zhang, Michele Guindani, Marina Vannucci
2014 Wiley Interdisciplinary Reviews: Computational Statistics  
We start from spatiotemporal models for fMRI data that detect task-related activation patterns. We then address the very important problem of estimating brain connectivity.  ...  Functional magnetic resonance imaging (fMRI), a noninvasive neuroimaging method that provides an indirect measure of neuronal activity by detecting blood flow changes, has experienced an explosive growth  ...  Zhang et al. 70 proposed a dynamic Bayesian variable partition model that simultaneously infers global functional interaction patterns within brain networks and their temporal transition boundaries.  ... 
doi:10.1002/wics.1339 pmid:25750690 pmcid:PMC4346370 fatcat:jqt3gog5f5h7hcceqnbve2mtye
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