Thought experiment: Decoding cognitive processes from the fMRI data of one individual

Wegrzyn M, Aust J, Barnstorf L, Gippert M, Harms M, Hautum A, Heidel S, Herold F, Hommel SM, Knigge A-K, Neu D, et al. (2018)
PLOS ONE 13(9): e0204338.

Zeitschriftenaufsatz | Veröffentlicht | Englisch
 
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Wegrzyn, MartinUniBi; Aust, Joana; Barnstorf, Larissa; Gippert, MagdalenaUniBi; Harms, Mareike; Hautum, Antonia; Heidel, Shanna; Herold, Friederike; Hommel, Sarah M.; Knigge, Anna-Katharina; Neu, Dominik; Peters, Diana
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Abstract / Bemerkung
Cognitive processes, such as the generation of language, can be mapped onto the brain using fMRI. These maps can in turn be used for decoding the respective processes from the brain activation patterns. Given individual variations in brain anatomy and organization, analyzes on the level of the single person are important to improve our understanding of how cognitive processes correspond to patterns of brain activity. They also allow to advance clinical applications of fMRI, because in the clinical setting making diagnoses for single cases is imperative. In the present study, we used mental imagery tasks to investigate language production, motor functions, visuo-spatial memory, face processing, and resting-state activity in a single person. Analysis methods were based on similarity metrics, including correlations between training and test data, as well as correlations with maps from the NeuroSynth meta-analysis. The goal was to make accurate predictions regarding the cognitive domain (e.g. language) and the specific content (e.g. animal names) of single 30-second blocks. Four teams used the dataset, each blinded regarding the true labels of the test data. Results showed that the similarity metrics allowed to reach the highest degrees of accuracy when predicting the cognitive domain of a block. Overall, 23 of the 25 test blocks could be correctly predicted by three of the four teams. Excluding the unspecific rest condition, up to 10 out of 20 blocks could be successfully decoded regarding their specific content. The study shows how the information contained in a single fMRI session and in each of its single blocks can allow to draw inferences about the cognitive processes an individual engaged in. Simple methods like correlations between blocks of fMRI data can serve as highly reliable approaches for cognitive decoding. We discuss the implications of our results in the context of clinical fMRI applications, with a focus on how decoding can support functional localization.
Erscheinungsjahr
2018
Zeitschriftentitel
PLOS ONE
Band
13
Ausgabe
9
Art.-Nr.
e0204338
ISSN
1932-6203
eISSN
1932-6203
Finanzierungs-Informationen
Open-Access-Publikationskosten wurden durch die Deutsche Forschungsgemeinschaft und die Universität Bielefeld gefördert.
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https://pub.uni-bielefeld.de/record/2931499

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Wegrzyn M, Aust J, Barnstorf L, et al. Thought experiment: Decoding cognitive processes from the fMRI data of one individual. PLOS ONE. 2018;13(9): e0204338.
Wegrzyn, M., Aust, J., Barnstorf, L., Gippert, M., Harms, M., Hautum, A., Heidel, S., et al. (2018). Thought experiment: Decoding cognitive processes from the fMRI data of one individual. PLOS ONE, 13(9), e0204338. doi:10.1371/journal.pone.0204338
Wegrzyn, Martin, Aust, Joana, Barnstorf, Larissa, Gippert, Magdalena, Harms, Mareike, Hautum, Antonia, Heidel, Shanna, et al. 2018. “Thought experiment: Decoding cognitive processes from the fMRI data of one individual”. PLOS ONE 13 (9): e0204338.
Wegrzyn, M., Aust, J., Barnstorf, L., Gippert, M., Harms, M., Hautum, A., Heidel, S., Herold, F., Hommel, S. M., Knigge, A. - K., et al. (2018). Thought experiment: Decoding cognitive processes from the fMRI data of one individual. PLOS ONE 13:e0204338.
Wegrzyn, M., et al., 2018. Thought experiment: Decoding cognitive processes from the fMRI data of one individual. PLOS ONE, 13(9): e0204338.
M. Wegrzyn, et al., “Thought experiment: Decoding cognitive processes from the fMRI data of one individual”, PLOS ONE, vol. 13, 2018, : e0204338.
Wegrzyn, M., Aust, J., Barnstorf, L., Gippert, M., Harms, M., Hautum, A., Heidel, S., Herold, F., Hommel, S.M., Knigge, A.-K., Neu, D., Peters, D., Schaefer, M., Schneider, J., Vormbrock, R., Zimmer, S.M., Woermann, F.G., Labudda, K.: Thought experiment: Decoding cognitive processes from the fMRI data of one individual. PLOS ONE. 13, : e0204338 (2018).
Wegrzyn, Martin, Aust, Joana, Barnstorf, Larissa, Gippert, Magdalena, Harms, Mareike, Hautum, Antonia, Heidel, Shanna, Herold, Friederike, Hommel, Sarah M., Knigge, Anna-Katharina, Neu, Dominik, Peters, Diana, Schaefer, Marius, Schneider, Julia, Vormbrock, Ria, Zimmer, Sabrina M., Woermann, Friedrich G., and Labudda, Kirsten. “Thought experiment: Decoding cognitive processes from the fMRI data of one individual”. PLOS ONE 13.9 (2018): e0204338.
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49 References

Daten bereitgestellt von Europe PubMed Central.

Remarks on the seat of the faculty of articulated language, following an observation of aphemia (loss of speech) [Translation by Christopher D. Green]
AUTHOR UNKNOWN, 1861
Towards an Individualized Delineation of Functional Neuroanatomy.
Satterthwaite TD, Davatzikos C., Neuron 87(3), 2015
PMID: 26247857

AUTHOR UNKNOWN, 2007

AUTHOR UNKNOWN, 2010
Practice guideline summary: Use of fMRI in the presurgical evaluation of patients with epilepsy: Report of the Guideline Development, Dissemination, and Implementation Subcommittee of the American Academy of Neurology.
Szaflarski JP, Gloss D, Binder JR, Gaillard WD, Golby AJ, Holland SK, Ojemann J, Spencer DC, Swanson SJ, French JA, Theodore WH., Neurology 88(4), 2017
PMID: 28077494
The Quest for the FFA and Where It Led.
Kanwisher N., J. Neurosci. 37(5), 2017
PMID: 28148806

AUTHOR UNKNOWN, 2015
Building a Science of Individual Differences from fMRI.
Dubois J, Adolphs R., Trends Cogn. Sci. (Regul. Ed.) 20(6), 2016
PMID: 27138646
Functional System and Areal Organization of a Highly Sampled Individual Human Brain.
Laumann TO, Gordon EM, Adeyemo B, Snyder AZ, Joo SJ, Chen MY, Gilmore AW, McDermott KB, Nelson SM, Dosenbach NU, Schlaggar BL, Mumford JA, Poldrack RA, Petersen SE., Neuron 87(3), 2015
PMID: 26212711
Natural speech reveals the semantic maps that tile human cerebral cortex.
Huth AG, de Heer WA, Griffiths TL, Theunissen FE, Gallant JL., Nature 532(7600), 2016
PMID: 27121839
Precision Functional Mapping of Individual Human Brains.
Gordon EM, Laumann TO, Gilmore AW, Newbold DJ, Greene DJ, Berg JJ, Ortega M, Hoyt-Drazen C, Gratton C, Sun H, Hampton JM, Coalson RS, Nguyen AL, McDermott KB, Shimony JS, Snyder AZ, Schlaggar BL, Petersen SE, Nelson SM, Dosenbach NUF., Neuron 95(4), 2017
PMID: 28757305
Single subject fMRI test-retest reliability metrics and confounding factors.
Gorgolewski KJ, Storkey AJ, Bastin ME, Whittle I, Pernet C., Neuroimage 69(), 2012
PMID: 23153967
Language lateralization by Wada test and fMRI in 100 patients with epilepsy.
Woermann FG, Jokeit H, Luerding R, Freitag H, Schulz R, Guertler S, Okujava M, Wolf P, Tuxhorn I, Ebner A., Neurology 61(5), 2003
PMID: 12963768
Can cognitive processes be inferred from neuroimaging data?
Poldrack RA., Trends Cogn. Sci. (Regul. Ed.) 10(2), 2006
PMID: 16406760
Decoding mental states from brain activity in humans.
Haynes JD, Rees G., Nat. Rev. Neurosci. 7(7), 2006
PMID: 16791142
Detecting awareness in the vegetative state.
Owen AM, Coleman MR, Boly M, Davis MH, Laureys S, Pickard JD., Science 313(5792), 2006
PMID: 16959998
When thoughts become action: an fMRI paradigm to study volitional brain activity in non-communicative brain injured patients.
Boly M, Coleman MR, Davis MH, Hampshire A, Bor D, Moonen G, Maquet PA, Pickard JD, Laureys S, Owen AM., Neuroimage 36(3), 2007
PMID: 17509898
A real-time fMRI-based spelling device immediately enabling robust motor-independent communication.
Sorger B, Reithler J, Dahmen B, Goebel R., Curr. Biol. 22(14), 2012
PMID: 22748322
Encoding and decoding in fMRI.
Naselaris T, Kay KN, Nishimoto S, Gallant JL., Neuroimage 56(2), 2010
PMID: 20691790
Memory fMRI lateralizes temporal lobe epilepsy.
Jokeit H, Okujava M, Woermann FG., Neurology 57(10), 2001
PMID: 11723264
Electrical stimulation of human fusiform face-selective regions distorts face perception.
Parvizi J, Jacques C, Foster BL, Witthoft N, Withoft N, Rangarajan V, Weiner KS, Grill-Spector K., J. Neurosci. 32(43), 2012
PMID: 23100414
The distributed human neural system for face perception.
Haxby JV, Hoffman EA, Gobbini MI., Trends Cogn. Sci. (Regul. Ed.) 4(6), 2000
PMID: 10827445
The human brain is intrinsically organized into dynamic, anticorrelated functional networks
AUTHOR UNKNOWN, 2005
Sequences Balanced for Pairs of Residual Effects
AUTHOR UNKNOWN, 1967
Unified segmentation.
Ashburner J, Friston KJ., Neuroimage 26(3), 2005
PMID: 15955494
Machine learning for neuroimaging with scikit-learn
AUTHOR UNKNOWN, 2014

AUTHOR UNKNOWN, 0
50 years of data science
AUTHOR UNKNOWN, 2017
Large-scale automated synthesis of human functional neuroimaging data.
Yarkoni T, Poldrack RA, Nichols TE, Van Essen DC, Wager TD., Nat. Methods 8(8), 2011
PMID: 21706013
Scikit-learn: Machine learning in Python
AUTHOR UNKNOWN, 2011
Matching categorical object representations in inferior temporal cortex of man and monkey.
Kriegeskorte N, Mur M, Ruff DA, Kiani R, Bodurka J, Esteky H, Tanaka K, Bandettini PA., Neuron 60(6), 2008
PMID: 19109916
Functional neuroanatomy of the semantic system: divisible by what?
Mummery CJ, Patterson K, Hodges JR, Price CJ., J Cogn Neurosci 10(6), 1998
PMID: 9831743
Neurophysiology. Decoding motor imagery from the posterior parietal cortex of a tetraplegic human.
Aflalo T, Kellis S, Klaes C, Lee B, Shi Y, Pejsa K, Shanfield K, Hayes-Jackson S, Aisen M, Heck C, Liu C, Andersen RA., Science 348(6237), 2015
PMID: 25999506
Is the human primary motor cortex involved in motor imagery?
Dechent P, Merboldt KD, Frahm J., Brain Res Cogn Brain Res 19(2), 2004
PMID: 15019710
Neural systems for recognition of familiar faces.
Gobbini MI, Haxby JV., Neuropsychologia 45(1), 2006
PMID: 16797608
A Generative Model of Speech Production in Broca's and Wernicke's Areas.
Price CJ, Crinion JT, Macsweeney M., Front Psychol 2(), 2011
PMID: 21954392
A common, high-dimensional model of the representational space in human ventral temporal cortex.
Haxby JV, Guntupalli JS, Connolly AC, Halchenko YO, Conroy BR, Gobbini MI, Hanke M, Ramadge PJ., Neuron 72(2), 2011
PMID: 22017997
Decoding brain activity using a large-scale probabilistic functional-anatomical atlas of human cognition.
Rubin TN, Koyejo O, Gorgolewski KJ, Jones MN, Poldrack RA, Yarkoni T., PLoS Comput. Biol. 13(10), 2017
PMID: 29059185
The influence of head motion on intrinsic functional connectivity MRI.
Van Dijk KR, Sabuncu MR, Buckner RL., Neuroimage 59(1), 2011
PMID: 21810475

AUTHOR UNKNOWN, 1997
Distributed and overlapping representations of faces and objects in ventral temporal cortex.
Haxby JV, Gobbini MI, Furey ML, Ishai A, Schouten JL, Pietrini P., Science 293(5539), 2001
PMID: 11577229
Dermatologist-level classification of skin cancer with deep neural networks.
Esteva A, Kuprel B, Novoa RA, Ko J, Swetter SM, Blau HM, Thrun S., Nature 542(7639), 2017
PMID: 28117445
Can we open the black box of AI?
Castelvecchi D., Nature 538(7623), 2016
PMID: 27708329
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