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Literature DB >> 22833038

Recent developments in multivariate pattern analysis for functional MRI.

Abstract

Multivariate pattern analysis (MVPA) is a recently-developed approach for functional magnetic resonance imaging (fMRI) data analyses. Compared with the traditional univariate methods, MVPA is more sensitive to subtle changes in multivariate patterns in fMRI data. In this review, we introduce several significant advances in MVPA applications and summarize various combinations of algorithms and parameters in different problem settings. The limitations of MVPA and some critical questions that need to be addressed in future research are also discussed.

Mesh：

Year: 2012 PMID： 22833038 PMCID： PMC5561894 DOI： 10.1007/s12264-012-1253-3

Source DB: PubMed Journal: Neurosci Bull ISSN： 1995-8218 Impact factor: 5.203

77 in total

1. Detection of neural activity in fMRI using maximum correlation modeling.

Authors: Ola Friman; Magnus Borga; Peter Lundberg; Hans Knutsson
Journal: Neuroimage Date: 2002-02 Impact factor: 6.556

2. Functional magnetic resonance imaging (fMRI) "brain reading": detecting and classifying distributed patterns of fMRI activity in human visual cortex.

Authors: David D Cox; Robert L Savoy
Journal: Neuroimage Date: 2003-06 Impact factor: 6.556

Recent developments in multivariate pattern analysis for functional MRI.

1. Detection of neural activity in fMRI using maximum correlation modeling.

2. Functional magnetic resonance imaging (fMRI) "brain reading": detecting and classifying distributed patterns of fMRI activity in human visual cortex.

3. Machine learning and data mining: strategies for hypothesis generation.

Review 4. Decoding mental states from brain activity in humans.

5. Decoding and predicting intentions.

6. Decoding the content of delayed intentions.

7. Inferring mental states from neuroimaging data: from reverse inference to large-scale decoding.

8. Distributed and overlapping representations of faces and objects in ventral temporal cortex.

9. Human anterior prefrontal cortex encodes the 'what' and 'when' of future intentions.

10. Identifying natural images from human brain activity.

Review 1. Predictive analytics in mental health: applications, guidelines, challenges and perspectives.

2. Using fMRI to decode true thoughts independent of intention to conceal.

3. Decomposing spatiotemporal brain patterns into topographic latent sources.

4. Distinct Neural Profiles of Frontoparietal Networks in Boys with ADHD and Boys with Persistent Depressive Disorder.

5. Searchlight analysis: promise, pitfalls, and potential.

6. The challenges of neural mind-reading paradigms.

7. A pilot study investigating changes in neural processing after mindfulness training in elite athletes.

8. Principal feature analysis: a multivariate feature selection method for fMRI data.

9. Cocaine dependence and thalamic functional connectivity: a multivariate pattern analysis.

10. PAIR Comparison between Two Within-Group Conditions of Resting-State fMRI Improves Classification Accuracy.