Filters








10 Hits in 3.9 sec

CoSMoMVPA: multi-modal multivariate pattern analysis of neuroimaging data in Matlab / GNU Octave [article]

Nikolaas N Oosterhof, Andrew C Connolly, James V Haxby
2016 bioRxiv   pre-print
Recent years have seen an increase in the popularity of multivariate pattern (MVP) analysis of functional magnetic resonance (fMRI) data, and, to a much lesser extent, magneto- and electro-encephalography  ...  We present CoSMoMVPA, a lightweight MVPA (MVP analysis) toolbox implemented in the intersection of the Matlab and GNU Octave languages, that treats both fMRI and M/EEG data as first-class citizens.  ...  which formed the basis of CoSMoMVPA; Gunnar Blohm for providing us with the CoSMo logo; Michael Hanke and Yaroslav Halchenko for their work on PyMVPA, which inspired the semantics and data structure of  ... 
doi:10.1101/047118 fatcat:6siq6wldxfe2rhdpyw4yj4slwy

CoSMoMVPA: Multi-Modal Multivariate Pattern Analysis of Neuroimaging Data in Matlab/GNU Octave

Nikolaas N. Oosterhof, Andrew C. Connolly, James V. Haxby
2016 Frontiers in Neuroinformatics  
Recent years have seen an increase in the popularity of multivariate pattern (MVP) analysis of functional magnetic resonance (fMRI) data, and, to a much lesser extent, magneto-and electro-encephalography  ...  We present CoSMoMVPA, a lightweight MVPA (MVP analysis) toolbox implemented in the intersection of the Matlab and GNU Octave languages, that treats both fMRI and M/EEG data as first-class citizens.  ...  ACKNOWLEDGMENTS We thank Gunnar Blohm and Sara Fabri for inviting two of the authors (NO and AC) This work has been supported by the Autonomous Province of Trento, Italy, Call "Grandi Progetti 2012,  ... 
doi:10.3389/fninf.2016.00027 pmid:27499741 pmcid:PMC4956688 fatcat:4hriih27ufagthqnex442updei

MVPA-Light: A Classification and Regression Toolbox for Multi-Dimensional Data

Matthias S. Treder
2020 Frontiers in Neuroscience  
High-level functions allow for the multivariate analysis of multi-dimensional data, including generalization (e.g., time x time) and searchlight analysis.  ...  MVPA-Light is a MATLAB toolbox for multivariate pattern analysis (MVPA). It provides native implementations of a range of classifiers and regression models, using modern optimization algorithms.  ...  CoSMoMVPA: multi-modal multivariate pattern analysis of neuroimaging data in Matlab/GNU Octave. Front.  ... 
doi:10.3389/fnins.2020.00289 pmid:32581662 pmcid:PMC7287158 fatcat:7mxsgmesynayjk5q34jehmm5j4

Cross-Situational Learning Is Supported by Propose-but-Verify Hypothesis Testing

Sam C. Berens, Jessica S. Horst, Chris M. Bird
2018 Current Biology  
Neuroimage 24, 244-252. 38. Oosterhof, N.N., Connolly, A.C., and Haxby, J.V. (2016). CoSMoMVPA: Multi-Modal Multivariate Pattern Analysis of Neuroimaging Data in Matlab/GNU Octave. Front.  ...  For the representational similarity analysis, multivariate BOLD patterns of interest were estimates as the t-statistics resulting from a GLM of the unsmoothed EPI data in native space (see below).  ... 
doi:10.1016/j.cub.2018.02.042 pmid:29551416 fatcat:ad3uhor5vzhx3f6rto2bvh76ua

MVPANI: A Toolkit With Friendly Graphical User Interface for Multivariate Pattern Analysis of Neuroimaging Data

Yanmin Peng, Xi Zhang, Yifan Li, Qian Su, Sijia Wang, Feng Liu, Chunshui Yu, Meng Liang
2020 Frontiers in Neuroscience  
With the rapid development of machine learning techniques, multivariate pattern analysis (MVPA) is becoming increasingly popular in the field of neuroimaging data analysis.  ...  Third, MVPANI also offers the function of data fusion at two levels (feature level or decision level) to utilize complementary information contained in different measures obtained from multimodal neuroimaging  ...  INTRODUCTION Multivariate pattern analysis (MVPA), a machine learning technique used in neuroimaging data analysis, has rapidly grown in popularity in recent years (Liang et al., 1993; Dosenbach et al  ... 
doi:10.3389/fnins.2020.00545 pmid:32742251 pmcid:PMC7364177 fatcat:axekelobvnhrbgadmmws5pmeem

Enhanced reinstatement of naturalistic event memories due to hippocampal-network-targeted stimulation [article]

Melissa Hebscher, James E Kragel, Thorsten Kahnt, Joel L. Voss
2020 bioRxiv   pre-print
We measured reinstatement of multi-voxel patterns of fMRI activity during encoding and retrieval of naturalistic video clips depicting everyday activities.  ...  Reinstatement of video-specific activity patterns was robust in posterior-parietal and occipital areas previously implicated in event reinstatement.  ...  Acknowledgments We thank Stephanie Wert, Brennan Durr, and Erica Karp for their assistance with data collection.  ... 
doi:10.1101/2020.08.18.256008 fatcat:ttk3xuqhdvc5neqz6n6mppur5a

The neural representational space of social memory [article]

Sarah L. Dziura, James C. Thompson
2017 bioRxiv   pre-print
Here we utilized a novel incidental learning paradigm and representational similarity analysis (RSA), a functional MRI multivariate pattern analysis technique, to examine the relationship between learning  ...  We found that accuracy of learning face pair relationships through observation is correlated with neural similarity patterns to those pairs in the left temporoparietal junction (TPJ), the left fusiform  ...  CoSMoMVPA: Multi-modal 610 multivariate pattern analysis of neuroimaging data in Matlab / GNU Octave. 611 Frontiers in Neuroinformatics, 10, 1-27. doi: 10.3389/fninf.2016.00027. 612 Figure 1 . 1 A.  ... 
doi:10.1101/130351 fatcat:d75ulwh4fvfincxvm4oqgmhm4m

MEG Multivariate Analysis Reveals Early Abstract Action Representations in the Lateral Occipitotemporal Cortex

R. Tucciarelli, L. Turella, N. N. Oosterhof, N. Weisz, A. Lingnau
2015 Journal of Neuroscience  
analysis of magnetoencephalography data.  ...  We examined which human brain regions are able to distinguish between pointing and grasping, regardless of reach direction (left or right) and effector (left or right hand), using multivariate pattern  ...  Haxby, in preparation ("CoSMoMVPA: Multi-Modal Multivariate Pattern Analysis of Neuroimaging Data in Matlab/GNU Octave"; toolbox available from http:// cosmomvpa.org)].  ... 
doi:10.1523/jneurosci.1422-15.2015 pmid:26658857 pmcid:PMC6605497 fatcat:vw6n2kvwibbbpe6y7ws4yqr3zm

Decoding digits and dice with Magnetoencephalography: Evidence for a shared representation of magnitude [article]

Lina Teichmann, Tijl Grootswagers, Thomas Carlson, Anina Rich
2018 bioRxiv   pre-print
Multivariate Pattern Analysis (MVPA) applied to MEG data allows us to draw conclusions about brain activation patterns underlying information processing over time.  ...  Additionally, results from a time-generalisation analysis show that digits were accessed slightly earlier than dice, demonstrating temporal asynchronies in their shared representation of magnitude.  ...  CoSMoMVPA: multi-modal 583 multivariate pattern analysis of neuroimaging data in Matlab/GNU Octave. Frontiers 584 in Neuroinformatics, 10. Retrieved from 585  ... 
doi:10.1101/249342 fatcat:v2kwg5brz5cuxpctks6q45mjy4

Decoding Digits and Dice with Magnetoencephalography: Evidence for a Shared Representation of Magnitude

Lina Teichmann, Tijl Grootswagers, Thomas Carlson, Anina N. Rich
2018 Journal of Cognitive Neuroscience  
Multivariate Pattern 8 Analysis (MVPA) applied to MEG data allows us to draw conclusions about brain activation 9 patterns underlying information processing over time.  ...  Additionally, results from a time-generalisation 13 analysis show that digits were accessed slightly earlier than dice, demonstrating temporal 14 asynchronies in their shared representation of magnitude  ...  CoSMoMVPA: multi-modal 583 multivariate pattern analysis of neuroimaging data in Matlab/GNU Octave. Frontiers 584 in Neuroinformatics, 10. Retrieved from 585  ... 
doi:10.1162/jocn_a_01257 pmid:29561240 fatcat:knd5dwwh7vg6fdxv7ngevss4oi