Real-time fMRI brain-computer interface: Development of a "motivational feedback" subsystem for the regulation of visual cue reactivity

Frontiers in Behavioral Neuroscience

Volumn 8, Issue NOV, 2014, Pages

  Sokunbi, Moses O ^a,b   Linden, David E J ^a,b   Habes, Isabelle ^a,b   Johnston, Stephen ^c   Ihssen, Niklas ^a,b  

^a CARDIFF UNIVERSITY SCHOOL OF MEDICINE   (United Kingdom)

^b CARDIFF UNIVERSITY   (United Kingdom)

^c SWANSEA UNIVERSITY   (United Kingdom)

Author keywords

Brain computer interface (BCI); Food craving; Functional magnetic resonance imaging (fMRI); Hunger; Neurofeedback; Self regulation; Visual cue reactivity

Indexed keywords

ADULT; AMYGDALOID NUCLEUS; APPETITE; ARTICLE; ASSOCIATION; BOLD SIGNAL; BRAIN COMPUTER INTERFACE; BRAIN REGION; CAUDATE NUCLEUS; EVOKED BRAIN STEM RESPONSE; FEEDING BEHAVIOR; FEMALE; FOOD CRAVING; FUNCTIONAL MAGNETIC RESONANCE IMAGING; HABITUATION; HUMAN; HUNGER; INSULA; MALE; MOTIVATION; NEUROFEEDBACK; NUCLEAR MAGNETIC RESONANCE SCANNER; PARAHIPPOCAMPAL GYRUS; PUTAMEN; STIMULUS RESPONSE; TASK PERFORMANCE; THALAMUS; VISUAL FEEDBACK; VISUAL STIMULATION;

EID: 84913588308     PISSN: 16625153     EISSN: None     Source Type: Journal    
DOI: 10.3389/fnbeh.2014.00392     Document Type: Article

References (35)

1. Bandura, A. (1977). Self-efficacy: toward a unifying theory of behavioral change. Psychol. Rev. 84, 191-215. doi: 10.1037//0033-295x.84.2.191
2. Brühl, A. B., Scherpiet, S., Sulzer, J., Stämpfli, P., Seifritz, E., and Herwig, U. (2014). Real-time neurofeedback using functional MRI could improve down-regulation of amygdala activity during emotional stimulation: a proof-of-concept study. Brain Topogr. 27, 138-148. doi: 10.1007/s10548-013-0331-9
3. De Cesarei, A., and Codispoti, M. (2006). When does size not matter? Effects of stimulus size on affective modulation. Psychophysiology 43, 207-215. doi: 10.1111/j.1469-8986.2006.00392.x
4. deCharms, R. C., Christoff, K., Glover, G. H., Pauly, J. M., Whitfield, S., and Gabrieli, J. D. E. (2004). Learned regulation of spatially localized brain activation using real-time fMRI. Neuroimage 21, 436-443. doi: 10.1016/j.neuroimage.2003.08.041
5. Eberl, C., Wiers, R. W., Pawelczack, S., Rinck, M., Becker, E. S., and Lindenmeyer, J. (2013). Approach bias modification in alcohol dependence: do clinical effects replicate and for whom does it work best? Dev. Cogn. Neurosci. 4, 38-51. doi: 10.1016/j.dcn.2012.11.002
6. Ernst, L. H., Plichta, M. M., Dresler, T., Zesewitz, A. K., Tupak, S. V., Haeussinger, F. B., et al. (2014). Prefrontal correlates of approach preferences for alcohol stimuli in alcohol dependence. Addict. Biol. 19, 497-508. doi: 10.1111/adb.12005
7. Goebel, R. (2001). Cortex-based real-time fMRI. Neuroimage 13:S129. doi: 10.1016/s1053-8119(01)91472-7
8. Greenfield, S. F., Hufford, M. R., Vagge, L. M., Muenz, L. R., Costello, M. E., and Weiss, R. D. (2000). The relationship of self-efficacy expectancies to relapse among alcohol dependent men and women: a prospective study. J. Stud. Alcohol 61, 345-351.
9. Grill-Spector, K., Henson, R., and Martin, A. (2006). Repetition and the brain: neural models of stimulus-specific effects. Trends Cogn. Sci. 10, 14-23. doi: 10.1016/j.tics.2005.11.006
10. Hanlon, C. A., Hartwell, K. J., Canterberry, M., Li, X., Owens, M., Lematty, T., et al. (2013). Reduction of cue-induced craving through real time neuro feed back in nicotine users: the role of region of interest selection and multiple visits. Psychiatry Res. 213, 79-81. doi: 10.1016/j.pscychresns.2013.03.003
11. Ihssen, N., Cox, W. M., Wiggett, A., Fadardi, J. S., and Linden, D. E. (2011). Differentiating heavy from light drinkers by neural responses to visual alcohol cues and other motivational stimuli. Cereb. Cortex 21, 1408-1415. doi: 10.1093/cercor/bhq220
12. LaConte, S. M., Peltier, S. J., and Hu, X. P. (2007). Real-time fMRI using brain-state classification. Hum. Brain Mapp. 28, 1033-1044. doi: 10.1002/hbm.20326
13. Lang, P. J., Bradley, M. M., and Cuthbert, B. N. (2005). International Affective Picture System (IAPS): Affective Ratings of Pictures and Instruction Manual. Gainesville, FL: University of Florida.
14. Li, X., Hartwell, K. J., Borckardt, J., Prisciandaro, J. J., Saladin, M. E., Morgan, P. S., et al. (2013). Volitional reduction of anterior cingulate cortex activity produces decreased cue craving in smoking cessation: a preliminary real-time fMRI study. Addict. Biol. 18, 739-748. doi: 10.1111/j.1369-1600.2012.00449.x
15. Linden, D. E. J. (2014). Brain Control—Developments in Therapy and Implications for Society. Houndmills: Palgrave Macmillan.
16. Mathiak, K. A., Koush, Y., Dyck, M., Gaber, T. J., Alawi, E., Zepf, F. D., et al. (2010). Social reinforcement can regulate localized brain activity. Eur. Arch. Psychiatry Clin. Neurosci. 260(Supplement. 2), S132-S136. doi: 10.1007/s00406-010-0135-9
17. Mendelsohn, A., Pine, A., and Schiller, D. (2014). Between thoughts and actions: motivationally salient cues invigorate mental action in the human brain. Neuron 81, 207-217. doi: 10.1016/j.neuron.2013.10.019
18. Peeters, M., Wiers, R. W., Monshouwer, K., Van de Schoot, R., Janssen, T., and Vollebergh, W. A. (2012). Automatic processes in at-risk adolescents: the role of alcohol-approach tendencies and response inhibition in drinking behavior. Addiction 107, 1939-1946. doi: 10.1111/j.1360-0443.2012.03948.x
19. Peirce, J. W. (2007). PsychoPy—Psychophysics software in Python. J. Neurosci. Methods 162, 8-13. doi: 10.1016/j.jneumeth.2006.11.017
20. Posse, S., Fitzgerald, D., Gao, K. X., Habel, U., Rosenberg, D., Moore, G. J., et al. (2003). Real-time fMRI of temporolimbic regions detects amygdala activation during single-trial self-induced sadness. Neuroimage 18, 760-768. doi: 10.1016/s1053-8119(03)00004-1
21. Sitaram, R. (2007a). "fMRI brain-computer interfaces," in 15th Annual Conference of the International Society for Neurofeedback and Research, Current Perspectives in Neuroscience: Neuroplasticity and Neurofeedback (San Diego, CA).
22. Sitaram, R., Caria, A., Veit, R., Gaber, T., Kuebler, A., and Birbaumer, N. (2005). "Real-time fMRI based brain-computer interface enhanced by interactive virtual worlds," in 45th Annual Meeting Society for Psychophysiological Research (Lisbon, Portugal).
23. Sitaram, R., Caria, A., Veit, R., Gaber, T., Rota, G., Kuebler, A., et al. (2007b). FMRI brain-computer interface: a tool for neuroscientific research and treatment. Comput. Intell. Neurosci. 2007:25487. doi: 10.1155/2007/25487
24. Sitaram, R., Weiskopf, N., Caria, A., Veit, R., Erb, M., and Birbaumer, N. (2008). fMRI brain-computer interfaces. IEEE Signal Process. Mag. 25, 95-106. doi: 10.1109/msp.2008.4408446
25. Veit, R., Singh, V., Sitaram, R., Caria, A., Rauss, K., and Birbaumer, N. (2012). Using real-time fMRI to learn voluntary regulation of the anterior insula in the presence of threat-related stimuli. Soc. Cogn. Affect. Neurosci. 7, 623-634. doi: 10.1093/scan/nsr061
26. Weiskopf, N. (2012). Real-time fMRI and its application to neurofeedback. Neuroimage 62, 682-692. doi: 10.1016/j.neuroimage.2011.10.009
27. Weiskopf, N., Scharnowski, F., Veit, R., Goebel, R., Birbaumer, N., and Mathiak, K. (2004). Self-regulation of local brain activity using real-time functional magnetic resonance imaging (fMRI). J. Physiol. Paris 98, 357-373. doi: 10.1016/j.jphysparis.2005.09.019
28. Weiskopf, N., Veit, R., Erb, M., Mathiak, K., Grodd, W., Goebel, R., et al. (2003). Physiological self-regulation of regional brain activity using real-time functional magnetic resonance imaging (fMRI): methodology and exemplary data. Neuroimage 19, 577-586. doi: 10.1016/s1053-8119(03)00145-9
29. Weiss, F. (2005). Neurobiology of craving, conditioned reward and relapse. Curr. Opin. Pharmacol. 5, 9-19. doi: 10.1016/j.coph.2004.11.001
30. Wiers, R. W., Eberl, C., Rinck, M., Becker, E. S., and Lindenmeyer, J. (2011). Retraining automatic action tendencies changes alcoholic patients’ approach bias for alcohol and improves treatment outcome. Psychol. Sci. 22, 490-497. doi: 10.1177/0956797611400615
31. Wiers, C. E., Stelzel, C., Park, S. Q., Gawron, C. K., Ludwig, V. U., Gutwinski, S., et al. (2014). Neural correlates of alcohol-approach bias in alcohol addiction: the spirit is willing but the flesh is weak for spirits. Neuropsychopharmacology 39, 688-697. doi: 10.1038/npp.2013.252
32. Wright, C. I., Fischer, H., Whalen, P. J., McInerney, S. C., Shin, L. M., and Rauch, S. L. (2001). Differential prefrontal cortex and amygdala habituation to repeatedly presented emotional stimuli. Neuroreport 12, 379-383. doi: 10.1097/00001756-200102120-00039
33. Yoo, S. S., Fairneny, T., Chen, N. K., Choo, S. E., Panych, L. P., Park, H., et al. (2004). Brain-computer interface using fMRI: spatial navigation by thoughts. Neuroreport 15, 1591-1595. doi: 10.1097/01.wnr.0000133296.39160.fe
34. Yoo, S. S., and Jolesz, F. A. (2002). Functional MRI for neurofeedback: feasibility study on a hand motor task. Neuroreport 13, 1377-1381. doi: 10.1097/00001756-200208070-00005
35. Zilverstand, A., Sorger, B., Zimmermann, J., Kaas, A., and Goebel, R. (2014). Windowed correlation: a suitable tool for providing dynamic fMRI-based functional connectivity neurofeedback on task difficulty. PLoS One 9:e85929. doi: 10.1371/journal.pone.0085929