The precision of value-based choices depends causally on fronto-parietal phase coupling

Nature Communications

Volumn 6, Issue , 2015, Pages

  Polanía, Rafael ^a   Moisa, Marius ^a   Opitz, Alexander ^b,c   Grueschow, Marcus ^a   Ruff, Christian C ^a  

^a UNIVERSITY OF ZURICH   (Switzerland)

^b NATHAN S KLINE INSTITUTE FOR PSYCHIATRIC RESEARCH   (United States)

^c CHILD MIND INSTITUTE   (United States)

Author keywords

[No Author keywords available]

Indexed keywords

BIOTRANSFORMATION; BRAIN; DECISION ANALYSIS; EXPERIMENTAL STUDY; NUMERICAL MODEL; SENSORY SYSTEM; SPATIAL DISTRIBUTION;

ACCURACY; ADULT; ARTICLE; DECISION MAKING; FEMALE; FRONTAL CORTEX; FRONTOPARIETAL CORTEX; FRONTOPOLAR CORTEX; HUMAN; HUMAN EXPERIMENT; MALE; NORMAL HUMAN; OSCILLATION; BIOLOGICAL MODEL; COMPUTER SIMULATION; ELECTROENCEPHALOGRAPHY; FRONTAL LOBE; MAGNETOENCEPHALOGRAPHY; PARIETAL LOBE; PHYSIOLOGY; YOUNG ADULT;

ADULT; CHOICE BEHAVIOR; COMPUTER SIMULATION; ELECTROENCEPHALOGRAPHY; FEMALE; FRONTAL LOBE; HUMANS; MAGNETOENCEPHALOGRAPHY; MALE; MODELS, BIOLOGICAL; PARIETAL LOBE; YOUNG ADULT;

EID: 84939824670     PISSN: None     EISSN: 20411723     Source Type: Journal    
DOI: 10.1038/ncomms9090     Document Type: Article

References (52)

1. Rangel, A., Camerer, C. & Montague, P. R. A framework for studying the neurobiology of value-based decision making. Nat. Rev. Neurosci. 9, 545-556 (2008).
2. Siegel, M., Donner, T. H. & Engel, A. K. Spectral fingerprints of large-scale neuronal interactions. Nat. Rev. Neurosci. 13, 121-134 (2012).
3. Philiastides, M. G., Biele, G. & Heekeren, H. R. A mechanistic account of value computation in the human brain. Proc. Natl Acad. Sci. USA 107, 9430-9435 (2010).
4. Wimmer, G. E. & Shohamy, D. Preference by association: how memory mechanisms in the hippocampus bias decisions. Science 338, 270-273 (2012).
5. Gluth, S., Sommer, T., Rieskamp, J. & Büchel, C. Effective connectivity between hippocampus and ventromedial prefrontal cortex controls preferential choices from memory. Neuron 86, 1078-1090 (2015).
6. Hare, T. A., Schultz, W., Camerer, C. F., O'Doherty, J. P. & Rangel, A. Transformation of stimulus value signals into motor commands during simple choice. Proc. Natl Acad. Sci. USA 108, 18120-18125 (2011).
7. Strait, C. E., Blanchard, T. C. & Hayden, B. Y. Reward value comparison via mutual inhibition in ventromedial prefrontal cortex. Neuron 82, 1357-1366 (2014).
8. Padoa-Schioppa, C. Neuronal origins of choice variability in economic decisions. Neuron 80, 1322-1336 (2013).
9. Dorris, M. C. & Glimcher, P. W. Activity in posterior parietal cortex is correlated with the relative subjective desirability of action. Neuron 44, 365-378 (2004).
10. Louie, K. & Glimcher, P. W. Separating value from choice: delay discounting activity in the lateral intraparietal area. J. Neurosci. 30, 5498-5507 (2010).
11. Hunt, L. T., Dolan, R. J. & Behrens, T. E. J. Hierarchical competitions subserving multi-attribute choice. Nat. Neurosci. 17, 1613-1622 (2014).
12. Boorman, E. D., Behrens, T. E. J., Woolrich, M. W. & Rushworth, M. F. S. How green is the grass on the other side? Frontopolar cortex and the evidence in favor of alternative courses of action. Neuron 62, 733-743 (2009).
13. Polanía, R., Krajbich, I., Grueschow, M. & Ruff, C. C. C. Neural oscillations and synchronization differentially support evidence accumulation in perceptual and value-based decision-making. Neuron 82, 709-720 (2014).
14. Basten, U., Biele, G., Heekeren, H. R. & Fiebach, C. J. How the brain integrates costs and benefits during decision making. Proc. Natl Acad. Sci. USA 107, 21767-21772 (2010).
15. Thut, G., Miniussi, C. & Gross, J. The functional importance of rhythmic activity in the brain. Curr. Biol. 22, R658-R663 (2012).
16. Polanía, R., Nitsche, M. A., Korman, C., Batsikadze, G. & Paulus, W. The importance of timing in segregated theta phase-coupling for cognitive performance. Curr. Biol. 22, 1314-1318 (2012).
17. Helfrich, R. F. et al. Entrainment of brain oscillations by transcranial alternating current stimulation. Curr. Biol. 24, 333-339 (2014).
18. Ratcliff, R. & Rouder, J. N. Modeling response times for two-choice decisions. Psychol. Sci. 9, 347-356 (1998).
19. Voss, U. et al. Induction of self awareness in dreams through frontal low current stimulation of gamma activity. Nat. Neurosci. 17, 810-812 (2014).
20. Brittain, J.-S., Probert-Smith, P., Aziz, T. Z. & Brown, P. Tremor suppression by rhythmic transcranial current stimulation. Curr. Biol. 23, 436-440 (2013).
21. Ali, M. M., Sellers, K. K. & Fröhlich, F. Transcranial alternating current stimulation modulates large-scale cortical network activity by network resonance. J. Neurosci. 33, 11262-11275 (2013).
22. Ozen, S. et al. Transcranial electric stimulation entrains cortical neuronal populations in rats. J. Neurosci. 30, 11476-11485 (2010).
23. Joundi, R. A., Jenkinson, N., Brittain, J.-S., Aziz, T. Z. & Brown, P. Driving oscillatory activity in the human cortex enhances motor performance. Curr. Biol. 22, 403-407 (2012).
24. Cecere, R., Rees, G. & Romei, V. Individual Differences in Alpha Frequency Drive Crossmodal Illusory Perception. Curr. Biol. 25, 1-5 (2014).
25. Opitz, A. et al. Physiological observations validate finite element models for estimating subject-specific electric field distributions induced by transcranial magnetic stimulation of the human motor cortex. Neuroimage 81, 253-264 (2013).
26. Hunt, L. T. et al. Mechanisms underlying cortical activity during value-guided choice. Nat. Neurosci. 15, 470-476 S1-3 (2012).
27. Canolty, R. T. et al. High gamma power is phase-locked to theta oscillations in human neocortex. Science 313, 1626-1628 (2006).
28. Polanía, R., Paulus, W. & Nitsche, M. A. Noninvasively decoding the contents of visual working memory in the human prefrontal cortex within high-gamma oscillatory patterns. J. Cogn. Neurosci 24, 304-314 (2012).
29. Akam, T. & Kullmann, D. M. Oscillatory multiplexing of population codes for selective communication in the mammalian brain. Nat. Rev. Neurosci. 15, 111-122 (2014).
30. Brunton, B. W., Botvinick, M. M. & Brody, C. D. Rats and humans can optimally accumulate evidence for decision-making. Science 340, 95-98 (2013).
31. Bogacz, R., Wagenmakers, E.-J., Forstmann, B. U. & Nieuwenhuis, S. The neural basis of the speed-accuracy tradeoff. Trends Neurosci. 33, 10-16 (2010).
32. Forstmann, B. U. et al. Striatum and pre-SMA facilitate decision-making under time pressure. Proc. Natl Acad. Sci. USA 105, 17538-17542 (2008).
33. Baldauf, D. & Desimone, R. Neural mechanisms of object-based attention. Science 344, 424-427 (2014).
34. Mazaheri, A. et al. Functional disconnection of frontal cortex and visual cortex in attention-deficit/hyperactivity disorder. Biol. Psychiatry 67, 617-623 (2010).
35. Clithero, J. A. & Rangel, A. Informatic parcellation of the network involved in the computation of subjective value. Soc. Cogn. Affect. Neurosci. 9, 1289-1302 (2013).
36. Grueschow, M., Polania, R., Hare, T. A. A. & Ruff, C. C. C. Automatic versus choice-dependent value representations in the human brain. Neuron 85, 874-885 (2015).
37. Chau, B. K. H., Kolling, N., Hunt, L. T., Walton, M. E. & Rushworth, M. F. S. A neural mechanism underlying failure of optimal choice with multiple alternatives. Nat. Neurosci. 17, 463-470 (2014).
38. Hanks, T. D. et al. Distinct relationships of parietal and prefrontal cortices to evidence accumulation. Nature 520, 220-223 (2015).
39. Kahnt, T., Park, S. Q., Haynes, J.-D. & Tobler, P. N. Disentangling neural representations of value and salience in the human brain. Proc. Natl Acad. Sci. USA 111, 5000-5005 (2014).
40. Summerfield, C. & Koechlin, E. A neural representation of prior information during perceptual inference. Neuron 59, 336-347 (2008).
41. Gregoriou, G. G., Gotts, S. J., Zhou, H. & Desimone, R. High-frequency, long-range coupling between prefrontal and visual cortex during attention. Science 324, 1207-1210 (2009).
42. Siegel, M., Donner, T. H., Oostenveld, R., Fries, P. & Engel, A. K. Neuronal synchronization along the dorsal visual pathway reflects the focus of spatial attention. Neuron 60, 709-719 (2008).
43. Ruff, C. C. et al. Concurrent TMS-fMRI and psychophysics reveal frontal influences on human retinotopic visual cortex. Curr. Biol. 16, 1479-1488 (2006).
44. Jbabdi, S., Lehman, J. F., Haber, S. N. & Behrens, T. E. Human and monkey ventral prefrontal fibers use the same organizational principles to reach their targets: tracing versus tractography. J. Neurosci. 33, 3190-3201 (2013).
45. Hare, T. A., Camerer, C. F. & Rangel, A. Self-control in decision-making involves modulation of the vmPFC valuation system. Science 324, 646-648 (2009).
46. Helfrich, R. F. et al. Selective Modulation of Interhemispheric Functional Connectivity by HD-tACS Shapes Perception. PLoS Biol. 12, e1002031 (2014).
47. Mulder, M. J., van Maanen, L. & Forstmann, B. U. Perceptual decision neurosciences - a model-based review. Neuroscience 277, 872-884 (2014).
48. Navarro, D. J. & Fuss, I. G. Fast and accurate calculations for first-passage times in Wiener diffusion models. J. Math. Psychol. 53, 222-230 (2009).
49. Vandekerckhove, J., Tuerlinckx, F. & Lee, M. D. Hierarchical diffusion models for two-choice response times. Psychol. Methods 16, 44-62 (2011).
50. Roitman, J. D. & Shadlen, M. N. Response of neurons in the lateral intraparietal area during a combined visual discrimination reaction time task. J. Neurosci. 22, 9475-9489 (2002).
51. Plummer, M. in Proceedings of the 3rd International Workshop on Distributed Statistical Computing (DSC 2003) 20-22 (Technische Universitat Wein, Vienna, Austria, 2003).
52. Gelman, A. et al. Bayesian Data Analysis. 3rd edn (CRC Press, 2013).