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Open AccessJournal ArticleDOI

Decoding Patterns of Human Brain Activity

Frank Tong, +1 more
- 01 Jan 2012 - 
- Vol. 63, Iss: 1, pp 483-509
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TLDR
It is described how multivoxel pattern analysis can provide a window into mind-brain relationships with unprecedented specificity, when carefully applied, as well as as issues of neuroethics and mental privacy will be important to consider.
Abstract
Considerable information about mental states can be decoded from noninvasive measures of human brain activity. Analyses of brain activity patterns can reveal what a person is seeing, perceiving, attending to, or remembering. Moreover, multidimensional models can be used to investigate how the brain encodes complex visual scenes or abstract semantic information. Such feats of "brain reading" or "mind reading," though impressive, raise important conceptual, methodological, and ethical issues. What does successful decoding reveal about the cognitive functions performed by a brain region? How should brain signals be spatially selected and mathematically combined to ensure that decoding reflects inherent computations of the brain rather than those performed by the decoder? We highlight recent advances and describe how multivoxel pattern analysis can provide a window into mind-brain relationships with unprecedented specificity, when carefully applied. However, as brain-reading technology advances, issues of neuroethics and mental privacy will be important to consider.

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Citations
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Representational geometry: integrating cognition, computation, and the brain

TL;DR: Representational geometry is a framework that enables us to relate brain, computation, and cognition and review recent insights into perception, cognition, memory, and action.
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Resolving human object recognition in space and time

TL;DR: This work acquired human magnetoencephalography and functional magnetic resonance imaging responses to 92 object images and identified transient and persistent neural activities during object processing with sources in V1 and IT.
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Decoding Neural Representational Spaces Using Multivariate Pattern Analysis

TL;DR: This article reviews the development of methods for decoding human neural activity, such as multivariate pattern classification, representational similarity analysis, hyperalignment, and stimulus-model-based encoding and decoding, into a common framework organized around the concept of high-dimensional representational spaces.
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A Primer on Pattern-Based Approaches to fMRI: Principles, Pitfalls, and Perspectives

John-Dylan Haynes
- 15 Jul 2015 - 
TL;DR: Human fMRI signals exhibit a spatial patterning that contains detailed information about a person's mental states that makes it possible to investigate human representational spaces in unprecedented ways, especially when combined with computational modeling.
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Revisiting the role of persistent neural activity during working memory

TL;DR: This work highlights multiple neural mechanisms supporting working memory, including temporally dynamic population coding in addition to persistent activity, and argues that sensory cortex, not the lPFC, maintains high-fidelity representations of WM content.
References
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Journal ArticleDOI

Beyond mind-reading: multi-voxel pattern analysis of fMRI data

TL;DR: How researchers are using multi-voxel pattern analysis methods to characterize neural coding and information processing in domains ranging from visual perception to memory search is reviewed.
Journal ArticleDOI

Information-based functional brain mapping

TL;DR: The development of high-resolution neuroimaging and multielectrode electrophysiological recording provides neuroscientists with huge amounts of multivariate data, but the local averaging standardly applied to this end may obscure the effects of greatest neuroscientific interest.
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