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A Searchlight Factor Model Approach for Locating Shared Information in Multi-Subject fMRI Analysis [article]

Hejia Zhang, Po-Hsuan Chen, Janice Chen, Xia Zhu, Javier S. Turek, Theodore L. Willke, Uri Hasson, Peter J. Ramadge
2016 arXiv   pre-print
There is a growing interest in joint multi-subject fMRI analysis. The challenge of such analysis comes from inherent anatomical and functional variability across subjects.  ...  One approach to resolving this is a shared response factor model. This assumes a shared and time synchronized stimulus across subjects.  ...  DISCUSSION AND CONCLUSION We have investigated how well various factor models can locate informative regions in a searchlight based analysis of multi-subject fMRI data.  ... 
arXiv:1609.09432v1 fatcat:ocqoep76gjgtbdmi2k7q6iy5zi

A Convolutional Autoencoder for Multi-Subject fMRI Data Aggregation [article]

Po-Hsuan Chen, Xia Zhu, Hejia Zhang, Javier S. Turek, Janice Chen, Theodore L. Willke, Uri Hasson, Peter J. Ramadge
2016 arXiv   pre-print
We first do this directly by combining a recent factor method known as a shared response model with searchlight analysis. Then we design a multi-view convolutional autoencoder for the same task.  ...  We examine two ways to combine the ideas of a factor model and a searchlight based analysis to aggregate multi-subject fMRI data while preserving spatial locality.  ...  A natural approach is that can satisfy this constraint to combine factor models and searchlight based analysis [16, 17] .  ... 
arXiv:1608.04846v1 fatcat:2227k6htenavtf7wlfhhfhu6g4

Decoding auditory spatial and emotional information encoding using multivariate versus univariate techniques

James H. Kryklywy, Ewan A. Macpherson, Derek G. V. Mitchell
2018 Experimental Brain Research  
A searchlight multi-voxel pattern analysis was conducted to identify activity patterns predictive of sound location and/or emotion.  ...  The current study aims to further investigate this dissociation using a more recently emerging multi-voxel pattern analysis searchlight approach.  ...  distributed under the terms of the Creative Commons Attribution 4.0 International License (http://creat iveco mmons .org/licen ses/by/4.0/), which permits unrestricted use, distribution, and reproduction in  ... 
doi:10.1007/s00221-018-5185-7 pmid:29374776 pmcid:PMC5887003 fatcat:chs3bc3n4vdsbat5r2v5vzgziu

Unveiling functions of the visual cortex using task-specific deep neural networks

Kshitij Dwivedi, Michael F. Bonner, Radoslaw Martin Cichy, Gemma Roig, Ulrik R. Beierholm
2021 PLoS Computational Biology  
The human visual cortex enables visual perception through a cascade of hierarchical computations in cortical regions with distinct functionalities.  ...  Together, our results provide a novel functional mapping of the human visual cortex and demonstrate the power of the computational approach.  ...  Using the same fMRI dataset as used in this study, a previous study [18] showed that representation in scene-selective ROIs consists of both location and category information using scene-parsing DNNs  ... 
doi:10.1371/journal.pcbi.1009267 pmid:34388161 pmcid:PMC8407579 fatcat:hwfb2xww7ng4xcjvhj7gembnjm

A comparison of volume-based and surface-based multi-voxel pattern analysis

Nikolaas N. Oosterhof, Tobias Wiestler, Paul E. Downing, Jörn Diedrichsen
2011 NeuroImage  
This makes surface-based information mapping a useful technique for a data-driven analysis of information representation in the cerebral cortex.  ...  For functional magnetic resonance imaging (fMRI), multi-voxel pattern analysis (MVPA) has been shown to be a sensitive method to detect areas that encode certain stimulus dimensions.  ...  NNO was supported by a fellowship awarded by the Boehringer Ingelheim Fonds.  ... 
doi:10.1016/j.neuroimage.2010.04.270 pmid:20621701 fatcat:x5nf6yfkdbhkhmrxfay6zcfye4

Evidence against the detectability of a hippocampal place code using functional magnetic resonance imaging [article]

Christopher R Nolan, Joyce M.G. Vromen, Allen Cheung, Oliver Baumann
2017 bioRxiv   pre-print
task, there was no statistical evidence for a place code.  ...  Individual hippocampal neurons selectively increase their firing rates in specific spatial locations.  ...  Additionally, we found robust and consistent evidence to di-583 rectly support the null hypothesis for location classification data, using Bayes factor analysis and a model of All rights reserved.  ... 
doi:10.1101/229781 fatcat:732daq3nfzhnznut6d7etb2efm

Decoding individual differences in STEM learning from functional MRI data

Joshua S. Cetron, Andrew C. Connolly, Solomon G. Diamond, Vicki V. May, James V. Haxby, David J. M. Kraemer
2019 Nature Communications  
Using a novel data-driven multivariate neuroimaging approach-informational network analysis-we successfully derived a neural score from patterns of activity across the brain that predicted individual differences  ...  The informational network score outperformed alternative neural scores computed using data-driven neuroimaging methods, including multivariate representational similarity analysis.  ...  This multi-stage, data-driven approach allowed for a successful mapping between neural data and a behavioral test of concept knowledge at the individual subject level.  ... 
doi:10.1038/s41467-019-10053-y pmid:31048694 pmcid:PMC6497647 fatcat:a6xgen5enbeybgxeyw7c33askm

Hyperalignment: Modeling shared information encoded in idiosyncratic cortical topographies

James V Haxby, J Swaroop Guntupalli, Samuel A Nastase, Ma Feilong
2020 eLife  
In this Perspective, we present the conceptual framework that motivates hyperalignment, its computational underpinnings for joint modeling of a common information space and idiosyncratic cortical topographies  ...  Hyperalignment captures shared information by projecting pattern vectors for neural responses and connectivities into a common, high-dimensional information space, rather than by aligning topographies  ...  Other approaches decompose tuning profiles using analyses such as ICA, PCA, or factor analysis.  ... 
doi:10.7554/elife.56601 pmid:32484439 fatcat:dbikkgynz5fx3hpxyjdmal5bn4

Informational connectivity: identifying synchronized discriminability of multi-voxel patterns across the brain

Marc N. Coutanche, Sharon L. Thompson-Schill
2013 Frontiers in Human Neuroscience  
The fluctuations in a brain region's activation levels over a functional magnetic resonance imaging (fMRI) time-course are used in functional connectivity (FC) to identify networks with synchronous responses  ...  Here we present a novel analysis method that quantifies regions' synchrony in multi-voxel activity pattern discriminability, rather than univariate activation, across a timeseries.  ...  We are grateful to Jim Haxby and colleagues for making their dataset available for further analyses. Marc Coutanche is funded by a fellowship from the Howard Hughes Medical Institute.  ... 
doi:10.3389/fnhum.2013.00015 pmid:23403700 pmcid:PMC3566529 fatcat:mvwi46segzgc3bz5c4yglccnle

Action kinematics as an organising principle in the cortical control of human hand movement [article]

James Kolasinski, Diana C Dima, David M A Mehler, Alice Stevenson, Sara Valadan, Slawomir Kusmia, Holly E Rossiter
2019 bioRxiv   pre-print
Comparable M1 activity was not observed for an ethological action model based functional mappings proposed in M1.  ...  Using a powerful combination of high-field fMRI and MEG, a spatial and temporal multivariate representational similarity analysis revealed that patterns of M1 activity mirrored kinematic, but not muscle-based  ...  For each participant and each fMRI run, fMRI data were analysed using a first-level general linear modelling (GLM) approach implemented in FSL FEAT 58 using FMRIBs Improved Linear Model (FILM) to estimate  ... 
doi:10.1101/613323 fatcat:nlm6xu55wndvjdld3m7mxuoh2i

Unveiling functions of the visual cortex using task-specific deep neural networks [article]

Kshitij Dwivedi, Michael F Bonner, Radoslaw Martin Cichy, Gemma Roig
2020 bioRxiv   pre-print
The human visual cortex enables visual perception through a cascade of hierarchical computations in cortical regions with distinct functionalities.  ...  Together, our results provide a novel functional mapping of the human visual cortex and demonstrate the power of the computational approach.  ...  We then averaged the RDMs across the subjects resulting in a single RDM for each searchlight block.Using RSA to compare multiple DNNs we do not obtain a complete picture of how each model is contributing  ... 
doi:10.1101/2020.11.27.401380 fatcat:gwdjp7iljnarpbiswd6g3nuhfu

Analyzing Neuroimaging Data Through Recurrent Deep Learning Models

Armin W. Thomas, Hauke R. Heekeren, Klaus-Robert Müller, Wojciech Samek
2019 Frontiers in Neuroscience  
We show that DeepLight outperforms conventional approaches of uni- and multivariate fMRI analysis in decoding the cognitive states and in identifying the physiologically appropriate brain regions associated  ...  To approach these challenges, we introduce the DeepLight framework, which utilizes long short-term memory (LSTM) based DL models to analyze whole-brain functional Magnetic Resonance Imaging (fMRI) data  ...  AT implemented all visualizations of DeepLight and the experimental procedures, performed all formal data analyses, wrote all software that was used in the data analyses and that is underlying DeepLight  ... 
doi:10.3389/fnins.2019.01321 pmid:31920491 pmcid:PMC6914836 fatcat:5fksyguwprdprjirl3zmukejxm

Spatially and temporally distinct encoding of muscle and kinematic information in rostral and caudal primary motor cortex

James Kolasinski, Diana C Dima, David M A Mehler, Alice Stephenson, Sara Valadan, Slawomir Kusmia, Holly E Rossiter
2020 Cerebral Cortex Communications  
Using a powerful combination of high-field fMRI and MEG, a spatial and temporal multivariate representational similarity analysis revealed encoding of kinematic information in more caudal regions of M1  ...  Here we provide evidence for spatially and temporally distinct encoding of kinematic and muscle information in human M1 during the production of a wide variety of naturalistic hand movements.  ...  Funding James Kolasinski holds a Wellcome Trust Sir Henry Wellcome Postdoctoral Fellowship, (204696/Z/16/Z). CUBRIC is supported by a Strategic Award from the Wellcome Trust (104943/Z/14/Z).  ... 
doi:10.1093/texcom/tgaa009 pmid:32864612 pmcid:PMC7446240 fatcat:wkfcso3cezfghhxb4zole7pl24

Visual representations are dominated by intrinsic fluctuations correlated between areas

Linda Henriksson, Seyed-Mahdi Khaligh-Razavi, Kendrick Kay, Nikolaus Kriegeskorte
2015 NeuroImage  
We characterized the representations in several human visual areas by representational dissimilarity matrices (RDMs) constructed from fMRI response-patterns for natural image stimuli.  ...  visual areas V1-3 and a categorical animate-inanimate model in the object-responsive lateral occipital cortex.  ...  mean of a spherical searchlight at each location.  ... 
doi:10.1016/j.neuroimage.2015.04.026 pmid:25896934 pmcid:PMC4503804 fatcat:aj2z7j52ovbith77y6ac3raxdq

Analyzing Neuroimaging Data Through Recurrent Deep Learning Models [article]

Armin W. Thomas, Hauke R. Heekeren, Klaus-Robert Müller, Wojciech Samek
2019 arXiv   pre-print
We show that DeepLight outperforms conventional approaches of uni- and multivariate fMRI analysis in decoding the cognitive states and in identifying the physiologically appropriate brain regions associated  ...  To approach these challenges, we introduce the DeepLight framework, which utilizes long short-term memory (LSTM) based DL models to analyze whole-brain functional Magnetic Resonance Imaging (fMRI) data  ...  Acknowledgements This work was supported by the German Federal Ministry for Education and Research through the Berlin Big Data Centre (01IS14013A), the Berlin Center for Machine Learning (01IS18037I) and  ... 
arXiv:1810.09945v2 fatcat:2rsispay4vd5resugdios3dkma
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