From brain maps to cognitive ontologies: Informatics and the search for mental structure

Annual Review of Psychology

Volumn 67, Issue , 2016, Pages 587-612

  Poldrack, Russell A ^a   Yarkoni, Tal ^b  

^a STANFORD UNIVERSITY   (United States)

^b UNIVERSITY OF TEXAS AT AUSTIN   (United States)

Author keywords

Classification; Cognition; Meta analysis; Neuroimaging; Neuroinformatics; Ontologies

Indexed keywords

BRAIN; BRAIN MAPPING; COGNITION; COGNITIVE NEUROSCIENCE; HUMAN; META ANALYSIS (TOPIC); NEUROIMAGING; PHYSIOLOGY;

BRAIN; BRAIN MAPPING; COGNITION; COGNITIVE NEUROSCIENCE; HUMANS; META-ANALYSIS AS TOPIC; NEUROIMAGING;

EID: 84953776017     PISSN: 00664308     EISSN: 15452085     Source Type: Book Series    
DOI: 10.1146/annurev-psych-122414-033729     Document Type: Article

References (91)

1. Aron AR, Robbins TW, Poldrack RA. (2004). Inhibition and the right inferior frontal cortex. Trends Cogn. Sci. 8: 170-77
2. Ashburner M, Ball CA, Blake JA, Botstein D, Butler H, et al (2000). Gene ontology: tool for the unification of biology. The Gene Ontology Consortium. Nat. Genet. 25: 25-29
3. Ashton MC, Lee K, Paunonen SV. (2002). What is the central feature of extraversion? Social attention versus reward sensitivity. J. Personal. Soc. Psychol. 83: 245-52
4. Baddeley A. (1992). Working memory. Science 255: 556-59
5. Bard JBL, Rhee SY. (2004). Ontologies in biology: design, applications and future challenges. Nat. Rev. Genet. 5: 213-22
6. Beckmann CF, Smith SM. (2004). Probabilistic independent component analysis for functional magnetic resonance imaging. IEEE Trans. Med. Imaging 23: 137-52
7. Biswal B, Yetkin FZ, Haughton VM, Hyde JS. (1995). Functional connectivity in the motor cortex of resting human brain using echo-planar MRI. Magn. Reson. Med. 34: 537-41
8. Blei D, Ng A, Jordan M. (2003). Latent Dirichlet allocation. J. Mach. Learn. Res. 3: 993-1022
9. Bodenreider O, Stevens R. (2006). Bio-ontologies: current trends and future directions. Brief Bioinform. 7: 256-74
10. Chang LJ, Yarkoni T, Khaw MW, Sanfey AG. (2013). Decoding the role of the insula in human cognition: functional parcellation and large-scale reverse inference. Cereb. Cortex 23: 739-49
11. Chronbach LJ, Meehl PE. (1955). Construct validity in psychological tests. Psychol. Bull. 52: 281-302
12. Churchland PM. (1981). Eliminative materialism and the propositional attitudes. J. Philos. 78: 67-90
13. Cox DD, Savoy RL. (2003). Functional magnetic resonance imaging (fMRI) "brain reading": detecting and classifying distributed patterns of fMRI activity in human visual cortex. NeuroImage 19: 261-70
14. Craddock RC, James GA, Holtzheimer PE 3rd, Hu XP, Mayberg HS. (2012). A whole brain fMRI atlas generated via spatially constrained spectral clustering. Hum. Brain Mapp. 33: 1914-28
15. Critchley HD, Wiens S, Rotshtein P, Ohman A, Dolan RJ. (2004). Neural systems supporting interoceptive awareness. Nat. Neurosci. 7: 189-95
16. Dale AM, Buckner RL. (1997). Selective averaging of rapidly presented individual trials using fMRI. Hum. Brain Mapp. 5: 329-40
17. Derrfuss J, Mar RA. (2009). Lost in localization: the need for a universal coordinate database. NeuroImage 48: 1-7
18. Dickson J, Drury H, Van Essen DC. (2001). "The Surface Management System" (SuMS) database: a surfacebased database to aid cortical surface reconstruction, visualization and analysis. Philos. Trans. R. Soc. B 356: 1277-92
19. Dosenbach NUF, Visscher KM, Palmer ED, Miezin FM, Wenger KK, et al (2006). A core system for the implementation of task sets. Neuron 50: 799-812
20. Egeth H, Marcus N, Bevan W. (1972). Target-set and response-set interaction: implications for models of human information processing. Science 176: 1447-48
21. Fan Y, Duncan NW, De Greck M, Northoff G. (2011). Is there a core neural network in empathy? An fMRI based quantitative meta-analysis. Neurosci. Biobehav. Rev. 35: 903-11
22. Fodor JA. (1974). Special sciences (or: the disunity of science as a working hypothesis). Synthese 28: 97-115
23. Friston KJ, Price CJ, Fletcher P, Moore C, Frackowiak RS, Dolan RJ. (1996). The trouble with cognitive subtraction. NeuroImage 4: 97-104
24. Garner WR, Hake HW, Eriksen CW. (1956). Operationism and the concept of perception. Psychol. Rev. 63: 149-59
25. Gordon EM, Laumann TO, Adeyemo B, Huckins JF, Kelley WM, Petersen SE. (2014). Generation and evaluation of a cortical area parcellation from resting-state correlations. Cereb. Cortex. doi: 10.1093/cercor/bhu239
26. Gorgolewski K, Burns CD, Madison C, Clark D, Halchenko YO, et al (2011). Nipype: a flexible, lightweight and extensible neuroimaging data processing framework in Python. Front. Neuroinform. 5: 13
27. Gorgolewski KJ, Varoquaux G, Rivera G, Schwartz Y, Ghosh SS, et al (2015). NeuroVault.org: a web-based repository for collecting and sharing unthresholded statistical maps of the human brain. Front. Neuroinform. 9: 8
28. Greenwald AG. (2012). There is nothing so theoretical as a good method. Perspect. Psychol. Sci. 7: 99-108
29. Gruber T. (1993). A translation approach to portable ontology specifications. Knowl. Acquis. 5: 199-220
30. Haynes JD, Rees G. (2006). Decoding mental states from brain activity in humans. Nat. Rev. Neurosci. 7: 523-34
31. Huth AG, Nishimoto S, Vu AT, Gallant JL. (2012). A continuous semantic space describes the representation of thousands of object and action categories across the human brain. Neuron 76: 1210-24
32. Hutzler F. (2014). Reverse inference is not a fallacy per se: Cognitive processes can be inferred from functional imaging data. NeuroImage 84: 1061-69
33. Jeneson A, Squire LR. (2012). Workingmemory, long-termmemory, andmedial temporal lobe function. Learn. Mem. 19: 15-25
34. Jennings JM, McIntosh AR, Kapur S, Tulving E, Houle S. (1997). Cognitive subtractions may not add up: the interaction between semantic processing and response mode. NeuroImage 5: 229-39
35. Kane MJ, Conway ARA, Miura TK, Colflesh GJH. (2007). Workingmemory, attention control, and theN-back task: a question of construct validity. J. Exp. Psychol.: Learn. Mem. Cogn. 33: 615-22
36. Kay KN, Naselaris T, Prenger RJ, Gallant JL. (2008). Identifying natural images from human brain activity. Nature 452: 352-55
37. Khatib F, Cooper S, Tyka MD, Xu K, Makedon I, et al (2011). Algorithm discovery by protein folding game players. PNAS 108: 18949-53
38. Kim H. (2011). Neural activity that predicts subsequent memory and forgetting: a meta-analysis of 74 fMRI studies. NeuroImage 54: 2446-61
39. Klein C. (2012). Cognitive ontology and region-versus network-oriented analyses. Philos. Sci. 79: 952-60
40. Klein TA, Endrass T, Kathmann N, Neumann J, von Cramon DY, Ullsperger M. (2007). Neural correlates of error awareness. NeuroImage 34: 1774-81
41. Koyejo O, Poldrack RA. (2013). Decoding cognitive processes from functional MRI. Presented at NIPS Workshop Mach. Learn. Interpret. Neuroimaging, Dec. 5-10, Lake Tahoe, CA
42. Laird AR, Lancaster JL, Fox PT. (2005). BrainMap: the social evolution of a human brain mapping database. Neuroinformatics 3: 65-78
43. Larocque JJ, Lewis-Peacock JA, Postle BR. (2014). Multiple neural states of representation in short-term memory? It s a matter of attention. Front. Hum. Neurosci. 8: 5
44. Lucas RE, Diener E. (2001). Understanding extraverts enjoyment of social situations: the importance of pleasantness. J. Personal. Soc. Psychol. 81: 343-56
45. Lucas RE, Diener E, Grob A, Suh EM, Shao L. (2000). Cross-cultural evidence for the fundamental features of extraversion. J. Personal. Soc. Psychol. 79: 452-68
46. Lucas RE, Le K, Dyrenforth PS. (2008). Explaining the extraversion/positive affect relation: Sociability cannot account for extraverts greater happiness. J. Personal. 76: 385-414
47. Machery E. (2014). In defense of reverse inference. Br. J. Philos. Sci. 65: 251-267
48. Mischel W. (2008). The toothbrush problem. APS Obs. 21: 11
49. Mitchell TM, Hutchinson R, Just MA, Niculescu RS, Pereira F, Wang X. (2003). Classifying instantaneous cognitive states from fMRI data. AMIA Annu. Symp. Proc. 2003: 465-69
50. Mitchell TM, Shinkareva SV, Carlson A, Chang KM, Malave VL, et al (2008). Predicting human brain activity associated with the meanings of nouns. Science 320: 1191-95
51. Mourão-Miranda J, Bokde ALW, Born C, Hampel H, Stetter M. (2005). Classifying brain states and determining the discriminating activation patterns: Support Vector Machine on functional MRI data. NeuroImage 28: 980-95
52. Munakata Y, Herd SA, Chatham CH, Depue BE, Banich MT, O Reilly RC. (2011). A unified framework for inhibitory control. Trends Cogn. Sci. 15: 453-59
53. Nielsen FA, Hansen LK, Balslev D. (2004). Mining for associations between text and brain activation in a functional neuroimaging database. Neuroinformatics 2: 369-80
54. Nishimoto S, Vu AT, Naselaris T, Benjamini Y, Yu B, Gallant JL. (2011). Reconstructing visual experiences from brain activity evoked by natural movies. Curr. Biol. 21: 1641-46
55. Norman KA, Polyn SM, Detre GJ, Haxby JV. (2006). Beyond mind-reading: multi-voxel pattern analysis of fMRI data. Trends Cogn. Sci. 10: 424-30
56. Owen AM, McMillan KM, Laird AR, Bullmore E. (2005). N-back working memory paradigm: a meta-analysis of normative functional neuroimaging studies. Hum. Brain. Mapp. 25: 46-59
57. Poldrack RA. (2006). Can cognitive processes be inferred from neuroimaging data? Trends Cogn. Sci. 10: 59-63
58. Poldrack RA. (2010). An exchange about localism. In Foundational Issues in Human Brain Mapping, ed. SJ Hanson, M Bunzl, pp. 147-60. Cambridge, MA: MIT press
59. Poldrack RA. (2011). Inferring mental states from neuroimaging data: from reverse inference to large-scale decoding. Neuron 72: 692-97
60. Poldrack RA, Barch DM, Mitchell JP, Wager TD, Wagner AD, et al (2013). Toward open sharing of task-based fMRI data: the OpenfMRI project. Front. Neuroinform. 7: 12
61. Poldrack RA, Halchenko YO, Hanson SJ. (2009). Decoding the large-scale structure of brain function by classifying mental states across individuals. Psychol. Sci. 20: 1364-72
62. Poldrack RA, Kittur A, Kalar D, Miller E, Seppa C, et al (2011). The Cognitive Atlas: toward a knowledge foundation for cognitive neuroscience. Front. Neuroinform. 5: 17
63. Poldrack RA, Mumford JA, Schonberg T, Kalar D, Barman B, Yarkoni T. (2012). Discovering relations between mind, brain, and mental disorders using topic mapping. PLOS Comput. Biol. 8: e1002707
64. Price C, Friston K. (2005). Functional ontologies for cognition: the systematic definition of structure and function. Cogn. Neuropsychol. 22: 262-75
65. Quine WV. (1948). On what there is. Rev. Metaphys. 2: 21-38
66. Raichle ME, MacLeod AM, Snyder AZ, Powers WJ, Gusnard DA, Shulman GL. (2001). A default mode of brain function. PNAS 98: 676-82
67. Rhee SY, Wood V, Dolinski K, Draghici S. (2008). Use and misuse of the gene ontology annotations. Nat. Rev. Genet. 9: 509-15
68. Rogers RD, Monsell S. (1995). Costs of a predictable switch between simple cognitive tasks. J. Exp. Psychol.: Gen. 124: 207-31
69. Rottschy C, Langner R, Dogan I, Reetz K, Laird AR, et al (2012). Modelling neural correlates of working memory: a coordinate-based meta-analysis. NeuroImage 60: 830-46
70. Rubin DL, Shah NH, Noy NF. (2008). Biomedical ontologies: a functional perspective. Brief Bioinform. 9: 75-90
71. Salimi-Khorshidi G, Smith SM, Keltner JR, Wager TD, Nichols TE. (2009). Meta-analysis of neuroimaging data: a comparison of image-based and coordinate-based pooling of studies. NeuroImage 45: 810-23
72. Schwartz Y, Thirion B, Varoquaux G. (2013). Mapping paradigm ontologies to and from the brain. Presented at NIPS Workshop Mach. Learn. Interpret. Neuroimaging, Dec. 5-10, Lake Tahoe, CA
73. Shinkareva SV, Mason RA, Malave VL, Wang W, Mitchell TM, Just MA. (2008). Using fMRI brain activation to identify cognitive states associated with perception of tools and dwellings. PLOS ONE 3: e1394
74. Smillie LD, Cooper AJ, Wilt J, Revelle W. (2012). Do extraverts get more bang for the buck? Refining the affective-reactivity hypothesis of extraversion. J. Personal. Soc. Psychol. 103: 306-26
75. Smith SM, Fox PT, Miller KL, Glahn DC, Fox PM, et al (2009). Correspondence of the brain s functional architecture during activation and rest. PNAS 106: 13040-45
76. Sternberg S. (1969). Memory-scanning: mental processes revealed by reaction-time experiments. Am. Sci. 57: 421-57
77. Tillisch K, Mayer EA, Labus JS. (2011). Quantitative meta-analysis identifies brain regions activated during rectal distension in irritable bowel syndrome. Gastroenterology 140: 91-100
78. Turkeltaub PE, Eden GF, Jones KM, Zeffiro TA. (2002). Meta-analysis of the functional neuroanatomy of single-word reading: method and validation. NeuroImage 16: 765-80
79. Turner JA, Laird AR. (2012). The cognitive paradigm ontology: design and application. Neuroinformatics 10: 57-66
80. Uttal W. (2001). The New Phrenology: The Limits of Localizing Cognitive Processes in the Brain. Cambridge, MA: MIT press
81. Varoquaux G, Craddock RC. (2013). Learning and comparing functional connectomes across subjects. NeuroImage 80: 405-15
82. Wager TD, Atlas LY, Lindquist MA, Roy M, Woo CW, Kross E. (2013). An fMRI-based neurologic signature of physical pain. N. Engl. J. Med. 368: 1388-97
83. Wager TD, Lindquist M, Kaplan L. (2007). Meta-analysis of functional neuroimaging data: current and future directions. Soc. Cogn. Affect. Neurosci. 2: 150-58
84. Wager TD, Rilling JK, Smith EE, Sokolik A, Casey KL, et al (2004). Placebo-induced changes in fMRI in the anticipation and experience of pain. Science 303: 1162-67
85. Wiech K, Lin CS, Brodersen KH, Bingel U, Ploner M, Tracey I. (2010). Anterior insula integrates information about salience into perceptual decisions about pain. J. Neurosci. 30: 16324-31
86. Wilhelm O, Hildebrandt A, Oberauer K. (2013). What is working memory capacity, and how can we measure it? Front. Psychol. 4: 433
87. Wise RJ, Greene J, Büchel C, Scott SK. (1999). Brain regions involved in articulation. Lancet 353: 1057-61
88. Yarkoni T, Barch DM, Gray JR, Conturo TE, Braver TS. (2009). Bold correlates of trial-by-trial reaction time variability in gray and white matter: a multi-study fMRI analysis. PLOS ONE 4: e4257
89. Yarkoni T, Poldrack RA, Nichols TE, Van Essen DC, Wager TD. (2011). Large-scale automated synthesis of human functional neuroimaging data. Nat. Methods 8: 665-70
90. Yarkoni T, Poldrack RA, Van Essen DC, Wager TD. (2010). Cognitive neuroscience 2.0: building a cumulative science of human brain function. Trends Cogn. Sci. 14: 489-96
91. Yeo BTT, Krienen FM, Eickhoff SB, Yaakub SN, Fox PT, et al (2014). Functional specialization and flexibility in human association cortex. Cereb. Cortex. doi: 10.1093/cercor/bhu217