Document Type : Full Research Paper

Authors

1 Assistant Professor, Computer Engineering Department, North Tehran Branch, Islamic Azad University, Tehran, Iran

2 Associate Professor, CSE & IT Department, Faculty of Electrical and Computer Engineering, Shiraz University, Shiraz, Iran

3 Assistant Professor, Department of Neurosurgery, Mofid Children’s Hospital, Shahid Beheshti University of Medical Sciences, Tehran, Iran

Abstract

The P300 event-related potentials (ERPs) has implicated in outcome evaluation and reward processing. It is controversial how reward processing affects the neural sources of P300. We try to investigate the effect of feedback on the neural sources of P300 component. Thirty healthy subjects were participated and their EEG signals were recorded by thirty channels through the start (30 minutes), feedback (60-90 minutes) and last (30 minutes) segments. We analyzed feedback segment where an equal number of audio and visual stimulus were applied to the participants to perform audio and visual recognition tasks. We punished participants for wrong answers where each wrong answer adds four more tests to this segment. The P300 component was extracted from the background EEG at all channels using the conventional time-locked synchronous grand averaging over all time frames and subjects. Next, two well-known source localization algorithms including standardize low resolution electromagnetic tomography (sLORETA) and shrinking sLORETA were applied to the P300 waveforms for estimating the activity of the P300 sources. Our finding show a significant increase in the activation of P300 sources in the feedback-locked compared to the stimulus-locked over right tempo-parieto-occipital areas (secondary association area) in visual recognition task, but difference of P300 sources is not significant in audio recognition task. The discrepancy between the audio and visual task confirms the hypothesis that our participants considered more probability of wrong answers in the audio task, but they respond to visual test with more confidence.

Keywords

[1]   S.J. Luck, An introduction to the event-related potential technique, second ed., The MIT Press, 2005.
References and further reading may be available for this article. To view references and further reading you must
[2]   J. Polich, “Updating P300: an integrative theory of P3a and P3b,” Clin. Neurophysiol., vol. 118, pp. 2128-2148, Jun. 2007.
[3]   M.F. Bear, B.W. Connors, M.A. Paradiso, Neuroscience exploring the brain, 4th ed. Philadelphia, Wolters Kluwer, 2016.
[4]   G. McCarthy, C.C. Wood, P.D. Williamson, D. Spencer, “Task-dependent field potentials in human hippocampal formation,” J. Neurosci., vol. 9, pp. 4235–4268, Dec. 1989.
[5]   M. Molnar, “On the origin of the P300 event-related potential component,” Int. J. Psychophysiol., vol. 17, pp. 129–144, 1994.
[6]   E. Kirino, A. Belger, P. Goldman-Rakic, G. McCarthy, “Prefrontal activation evoked by infrequent target and novel stimuli in a visual target detection task: an event-related functional magnetic resonance study,” J. Neurosci., vol. 20, pp. 6612–6618, Sep. 2000.
[7]   R.T. Knight, “Distributed cortical network for visual attention,” J. Cogn. Neurosci., vol. 9, pp. 75–91, 1997.
[8]   A.A. Stevens, P. Skudlarski, J.C. Gatenby, J.C. Gore, “Event related fMRI of auditory and visual oddball tasks,” Magn. Reson. Imaging, vol. 18, pp. 495–502, Jun. 2000.
[9]   V.P. Clark, S. Fannon, S. Lai, R. Benson, L. Bauer, “Responses to rare visual target and distractor stimuli using event-related fMRI,” J. Neurophysiol., vol. 83, pp. 3133–3139, May 2000.
[10]Y. Long, X. Jiang, X. Zhou, “To believe or not to believe: trust choice modulates brain responses in outcome evaluation,” Neuroscience, vol. 200, pp. 50- 58, Jan. 2012.
[11]C. Bellebaum, I. Daum, “Learning-related changes in reward expectancy are reflected in the feedback-related negativity,” Eur. J. Neurosci., vol. 27, pp. 1823-1835, Apr 2008.
[12]م. عبدالصالحی، ع. مطیع نصرآبادی، س.م. فیروزآبادی، «بررسی میزان تعیین سیگنالهای مغزی در احساسات مثبت، منفی و خنثی در منابع حاصل از الگوریتم ICA،» فصلنامه علمی پژوهشی مهندسی پزشکی زیستی، شماره 2، دوره 7، صفحه 143-153، تابستان 1392.
[13]Y. Wu, X. Zhou, “The P300 and reward valence, magnitude, and expectancy in outcome evaluation,” Brain Res., vol. 1286, pp. 114-122, Aug. 2009.
[14]B. Ernst, M. Steinhauser, “Feedback-related brain activity predicts learning from feedback in multiple-choice testing,” Cogn. Affect. Behav. Neurosci., vol. 12, pp. 323-336, Jun. 2012.
[15]G. Hajcak, C.B. Holroyd, J.S. Moser, R.F. Simons, “Brain potentials associated with expected and unexpected good and bad outcomes,” Psychophysiology, vol. 42, pp. 161–170, Mar. 2005.
[16]M. Zeiler, “The impact of different positive and negative feedback stimuli on the FRN and P300: A synopsis of three event-related potential studies,” M.S. thesis, University of Wien, 2012.
[17]Y. Zhang, X. Li, X. Qian, X. Zhou, “Brain responses in evaluating feedback stimuli with a social dimension,” Front. Hum. Neurosci., vol. 6, pp. 29, Feb. 2012.purchase this article.
[18]X. Mai, T. Tardif, S.N. Doan, C. Liu, W.J. Gehring, Y.J. Luo, “Brain activity elicited by positive and negative feedback in preschool-aged children,” PLoS ONE, vol. 6, pp. 1-6, 2011.
[19]R.S. Martin, “Event-related potential studies of outcome processing and feedback-guided leaning,” Front. Hum. Neurosci., vol. 6, pp. 304, Nov. 2012.
[20]R.D. Pascual-Marqui, C.M. Michel, D. Lehmann, “Low resolution electromagnetic tomography: a new method for localizing electrical activity in the brain,” Int. J. Psychophysiol., vol. 18, pp. 49-65, Oct. 1994.
[21]R.D. Pascual-Marqui, “Standardized low-resolution brain electromagnetic tomography: technical details,” Methods. Find. Exp. Clin. Pharmacol., vol. 24, pp. 5-12, 2002.
[22]I.F. Gorodnitsky, J.S. George, B.D. Rao, “Neuromagnetic source imaging with FOCUSS: a recursive weighted minimum norm algorithm,” Electroencephalogr. Clin. Neurophysiol., vol. 95, pp. 231–251, Oct. 1995.
[23]H. Liu, P.H. Schimpf, G. Dong, X. Gao, F. Yang, S. Gao, “Standardized shrinking LORETA-FOCUSS (SSLOFO): a new algorithm for spatio-temporal EEG source reconstruction,” IEEE Trans. Biomed. Eng., vol. 52, pp. 1681-1691, Oct. 2005.
[24]S. Sanei, J.A. Chambers, EEG signal processing, John Wiley & Sons, 2007.
[25]ف. سلیمیان ریزی، و. ابوطالبی، م.ت. صادقی، « آشکار سازی مولفه P300 سیگنال مغزی با استفاده از الگوی زمانی مشترک،» فصلنامه علمی پژوهشی مهندسی پزشکی زیستی، دوره 9، شماره 4، صفحه 387-397، زمستان 1394.
[26]M. Sabeti, S.D. Katebi, K. Rastgar, “Source localization algorithms to find attention and memory circuits in the brain,” J. King Saud Univ. Comput. Inform. Sci., vol. 27, pp. 334–343, Jul. 2015.
[27]M. Sabeti, R. Boostani, K. Rastgar, “How mental fatigue affects the neural sources of P300 component?” J. Integr. Neurosci., vol. 17, pp. 71-81, 2018.
[28]P.H. Schimpf, H. Liu, “Localizing sources of the P300 using ICA, SSLOFO and latency mapping,” J. Biomechan. Biomed. Biophysic. Eng, vol.  2, pp. 1-11, 2008.
[29]A.J. Bell, T.J. Sejnowski, “An information-maximization approach to blind separation and blind deconvolution,” Neural Comput., vol. 7, pp. 1129-1159, Nov. 1995.
[30]و. ابوطالبی، م.ح. مرادی، م.ع. خلیل زاده، «آشکار سازی مولفه های شناختی سیگنال مغز با استفاده از ضرایب ویولت،» فصلنامه علمی پژوهشی مهندسی پزشکی زیستی، دوره 1، شماره 1، صفحه 25-45، پاییز 1383.
[31]M. Fuchs, R. Drenckhahn, H.A. Wischmann, M. Wagner, “An improved boundary element method for realistic volume-conductor modeling,” IEEE Trans Biomed Eng, vol. 45, pp. 980-97, Aug. 1998.
[32]Site of Spm12 software, Available: http://www.fil.ion.ucl.ac.uk/spm/software/spm12.
[33]M.M. Walsh, J.R. Anderson, “Learning from experience: Event-related potential correlates of reward processing, neural adaptation, and behavioral choice,” Neurosci. Biobehav. Rev., vol. 36, pp. 1870-1884, Sep. 2012.