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Brain decoding: Opportunities and challenges for pattern recognition
2012
Pattern Recognition
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The specific problems at hand constitute opportunities for future research in pattern recognition and neurosciences. & 2011 Elsevier Ltd. All rights reserved. ...
This is where advanced pattern recognition methods can play a central role to enable more accurate and efficient brain decoding. ...
doi:10.1016/j.patcog.2011.06.001
fatcat:ykrkdjom4ranjpsiufb6v2elwq
Bayesian decoding of brain images
2008
NeuroImage
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We frame this approach in terms of decoding measured brain states to predict or classify outcomes using the rhetoric established in pattern classification of neuroimaging data. ...
This paper introduces a multivariate Bayesian (MVB) scheme to decode or recognise brain states from neuroimages. ...
This work was undertaken under the auspices of the Brain Network Recovery Group (http://www.brainnrg.org), sponsored by the James S. McDonnell Foundation. ...
doi:10.1016/j.neuroimage.2007.08.013
pmid:17919928
fatcat:2ljuwyzv55ashcur67skv3h4be
Decoding Patterns of Human Brain Activity
2012
Annual Review of Psychology
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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. ...
• Decoding Patterns of Human Brain Activity ...
doi:10.1146/annurev-psych-120710-100412
pmid:21943172
pmcid:PMC7869795
fatcat:lern4jlb2neivhadjjjzea5jcq
Decoding fMRI brain states in real-time
2011
NeuroImage
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and opportunities. ...
The decoded brain states can be used as a control signal for a brain computer interface (BCI) or to provide neurofeedback to the subject. ...
Thanks to Robert Cox, Ziad Saad, and Richard Reynolds for input and help with 3dsvm and discussions of rtfMRI configurations. ...
doi:10.1016/j.neuroimage.2010.06.052
pmid:20600972
fatcat:lfendwnttze5xd5z2wp5cgoiui
Multi-Region Neural Representation: A novel model for decoding visual stimuli in human brains
[article]
2017
bioRxiv
pre-print
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Multivariate Pattern (MVP) classification holds enormous potential for decoding visual stimuli in the human brain by employing task-based fMRI data sets. ...
There is a wide range of challenges in the MVP techniques, i.e. decreasing noise and sparsity, defining effective regions of interest (ROIs), visualizing results, and the cost of brain studies. ...
Acknowledgment We thank the anonymous reviewers for comments. ...
doi:10.1101/097675
fatcat:zhl37d6kerauhnw7zdiapw5oga
Multi-Region Neural Representation: A novel model for decoding visual stimuli in human brains
[article]
2016
arXiv
pre-print
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Multivariate Pattern (MVP) classification holds enormous potential for decoding visual stimuli in the human brain by employing task-based fMRI data sets. ...
There is a wide range of challenges in the MVP techniques, i.e. decreasing noise and sparsity, defining effective regions of interest (ROIs), visualizing results, and the cost of brain studies. ...
Acknowledgment We thank the anonymous reviewers for comments. ...
arXiv:1612.08392v1
fatcat:ad4to5j6ojfm3dfyqcs23nzjii
Modality-Independent Decoding of Semantic Information from the Human Brain
2012
Cerebral Cortex
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An ability to decode semantic information from fMRI spatial patterns has been demonstrated in previous studies mostly for 1 specific input modality. ...
The results show that semantic information can be decoded from the fMRI signal independently of the input modality and have clear implications for understanding the functional mechanisms of semantic memory ...
Debener, and A.K. Engel at the Department of Neurophysiology and Pathophysiology, Univesity Medical Center Hamburg-Eppendorf, Germany. Conflict of Interest: None declared. ...
doi:10.1093/cercor/bhs324
pmid:23064107
fatcat:bn3lgsg2cncjplabfgyug453vi
Multi-Region Neural Representation: A novel model for decoding visual stimuli in human brains
[chapter]
2017
Proceedings of the 2017 SIAM International Conference on Data Mining
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Multivariate Pattern (MVP) classification holds enormous potential for decoding visual stimuli in the human brain by employing task-based fMRI data sets. ...
There is a wide range of challenges in the MVP techniques, i.e. decreasing noise and sparsity, defining effective regions of interest (ROIs), visualizing results, and the cost of brain studies. ...
Acknowledgment We thank the anonymous reviewers for comments. ...
doi:10.1137/1.9781611974973.7
dblp:conf/sdm/YousefnezhadZ17
fatcat:ad6e3cdy2bhmrd4zaxi5rh66ue
Decode Brain System: A Dynamic Adaptive Convolutional Quorum Voting Approach for Variable-Length EEG Data
2020
Complexity
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Electroencephalogram (EEG) recordings of brain activity play a vital role to decode the cognitive process of human beings in learning research and application areas. ...
The brain is a complex and dynamic system, consisting of interacting sets and the temporal evolution of these sets. ...
Introduction e human brain system is a complex and dynamic system, which is difficult to unravel and understand [1] . How to decode brain activity is always a challenge for researchers. ...
doi:10.1155/2020/6929546
fatcat:kftlai4qhngwdgckcahe5jakfy
Decoding and mapping task states of the human brain via deep learning
[article]
2019
arXiv
pre-print
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In this study, we propose a deep neural network (DNN) for directly decoding multiple brain task states from fMRI signals of the brain without any burden for feature handcrafts. ...
Without incurring the burden of handcrafting the features, the proposed deep decoding method can classify brain task states highly accurately, and is a powerful tool for fMRI researchers. ...
There is a criticism where good decoding performance is not a guarantee that patterns of brain activity are learned (Ritchie, et al., 2019) , for a decoder may learn from nuisance or latent variables ...
arXiv:1801.09858v2
fatcat:jxxtowifvjbpnggszvz2c2kvnu
Interpretable brain decoding from sensations to cognition to action: graph neural networks reveal the representational hierarchy of human cognition
[article]
2022
bioRxiv
pre-print
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AbstractInter-subject modeling of cognitive processes has been a challenging task due to large individual variability in brain structure and function. ...
Moreover, the multilevel representations of VWM exhibit better inter-subject alignment in brain responses, higher decoding of cognitive states, and strong phenotypic and genetic correlations with individual ...
remains challenging. ...
doi:10.1101/2022.09.30.510241
fatcat:dlo6yrecpjauzlkgdzekosdfpm
Beyond smiles: The impact of culture and race in embodying and decoding facial expressions
2010
Behavioral and Brain Sciences
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These are then linked to behavioral and brain research on facial mimicry and eye gaze. ...
A smile is the chosen vehicle for all ambiguities. ...
ACKNOWLEDGMENTS The authors thank Ralph Adolphs, Anthony Atkinson, Markus Brauer, Julie Grè zes, and Piotr Winkielman for comments on an earlier draft of the paper. ...
doi:10.1017/s0140525x10001470
fatcat:kyzfo7v6sfeflg34yg6g7ea7ga
Brain2GAN: Feature-disentangled neural encoding and decoding of visual perception in the primate brain
[article]
2023
bioRxiv
pre-print
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A challenging goal of neural coding is to characterize the neural representations underlying visual perception. ...
Subsequently, a multivariate neural decoding analysis of the feature-disentangled representations resulted in state-of-the-art spatiotemporal reconstructions of visual perception. ...
of VGG16 for face recognition (faces images) / object recognition (natural images) and latent cosine similarity between w-latents of stimuli and their reconstructions (mean ± std.error). ...
doi:10.1101/2023.04.26.537962
fatcat:nomhno5545fcvfj54tjlonz4le
Effects of prior information on decoding degraded speech: An fMRI study
2012
Human Brain Mapping
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The current fMRI study investigated the effect of prior information on brain activity during the decoding of degraded speech stimuli. ...
In contrast, the activation of the left inferior frontal gyrus (area 44/45) appeared to reflect the search for meaningful information in degraded speech material that could not be decoded because of mismatches ...
Of note, this contrast and the inverse contrast revealed an activity pattern very similar to that reported by Meyer et al. [2004] for comparing nondegraded and degraded speech. ...
doi:10.1002/hbm.22151
pmid:22936472
fatcat:whz526rierem5csseoulkzbota
Could grammatical encoding and grammatical decoding be subserved by the same processing module?
2000
Behavioral and Brain Sciences
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He has been investigating brain/language relations for many years and has published numerous articles in the leading journals in linguistics, psycholinguistics, and cognitive neuroscience. ...
Here are located the integrative centers for cross-modal visual and auditory functions. ...
I would like to thank Michal Ben-Shachar for her invaluable comments and help and Danny Fox for saving me from several pitfalls. ...
doi:10.1017/s0140525x00402396
fatcat:elcwtgd6offmxa7vyfegpbjpyq
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