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INTRODUCTION. RESULTS. SUMMARY. cI. cI. cI. iI. iI. iI. iC. iC. iC. cC. cC. cC. -. +. iiiI. iiiiiI. iI. cccccI. cI. cccI. iiiC. iC. iiiiiC. cC. cccccC. cccC. 2 µV. 2 µV. 2 µV. -100. -100. -100. -100. 0. 0. 0. 0. 100. 100. 100. 100. 200. 200. 200.

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  1. INTRODUCTION RESULTS SUMMARY cI cI cI iI iI iI iC iC iC cC cC cC - + iiiI iiiiiI iI cccccI cI cccI iiiC iC iiiiiC cC cccccC cccC 2 µV 2 µV 2 µV -100 -100 -100 -100 0 0 0 0 100 100 100 100 200 200 200 200 300 300 300 300 400 400 400 400 500 500 500 500 Time (ms) Time (ms) Time (ms) Time (ms) REFERENCES 0 0 100 100 Theta Alpha CRN Stim ERN Error Resp Correct - Preceding + Pe c i 6Hz Ending Ending Incongruent Incongruent Incongruent Incongruent Incongruent Incongruent Incongruent C I C I Congruent Congruent Congruent Congruent Congruent Congruent Congruent 1 cC cI iC iI 3 cccC cccI iiiC iiiI EEG Behavioral Number preceding (CM) 5 cccccC cccccI iiiiiC iiiiiI 7 cccccccC cccccccI iiiiiiiC iiiiiiiI 1st 2nd 1500 ms 3rd Preceding Trial(s) 1-7 4th Wait for response 5th 1500 ms * Ending trial * * Wait for response * * * Time * * * 1500 ms GREEN Preceding trial number Preceding trial number RED ACKNOWLEDGEMENTS Limited Modulation of the Stroop Interference Effect by up to 3 Preceding Trials 634.22/CCC15 M.T. Sutherland1 and A.C. Tang1,2,3 Department of Psychology1, Department of Neurosciences2, Department of Computer Science3, University of New Mexico, Albuquerque, NM 3. Ending-trial assessment: RT and CRN were modulated by the preceding context EEG data processing • EEG data were processed with a blind source separation algorithm, second-order blind identification (SOBI, [12,13]) to isolate frontal-midline EEG activity from other neuronal sources and artifact signals. Correct-related Negativity (CRN) • The CRN was quantified as the average voltage value (with respect to baseline) between the 0-100 ms interval following a button press response. Frontal-midline EEG activity in the form of negative deflections in event-related brain potentials (e.g., the error-related negativity, ERN), has been considered to reflect aspects of anterior cingulate cortex (ACC) activity related to performance monitoring [1-6]. Bartholow et al. [5] have shown that the correct-related negativity (CRN, [7]) is sensitive to strategic expectations about an upcoming trial. Using a design where the probability of incongruent (I) or congruent (C) trials was manipulated over large blocks (e.g., C-80%: I-20%), CRN amplitude increased when the less probable trial type was encountered for both I and C trials. CRN modulation for C trials is unexpected according to conflict monitoring [3] because C trials are unlikely to induce response-conflict regardless of context. Bartholow et al. suggested a broadening of the conflict monitoring hypothesis to include other forms of conflict in addition to that at the response level. In the present study a different contextual manipulation was employed to further assess CRN modulation. Previously, the compatibility level (I vs. C) of the preceding trial has been shown to affect reaction times (RTs) and ACC activity on a current trial []. However, the number of preceding trials has not been considered as an important source of variance for current-trial RT. CM-1 CM-3 CM-5 CM-7 • 1. The SOBI recovered frontal-midline components likely capture aspects of ACC function. • 2. The CRN and ERN may share a similar neural generator since both of these ERP deflections were captured in a single component. • 3. The reduction of the Stroop interference effect (I-C) following a preceding i trial, in comparison to following a c trial, was diminished in the current study when only one preceding trial was delivered before the ending-trial of interest (CM-1). • 4. The CRN was modulated by the contextual manipulations in the present study. (we need to say what this means to existing theory) Preceding trial(s) CM-1 vs 3,5,7: F(1,23) = 45.92, p < 0.001 • CRN and ERN were present in the same frontal-midline component that captured ACC activity. Number of preceding trials CM-1 vs 3,5: F(1,23) = 36.19, p < 0.001 Preceding trial(s) - METHODS + 1. Ridderinkhof K.R., Ullsperger M., Crone E.A., Nieuwenhuiss S. (2004). The role of the medial frontal cortex in cognitive control. Science, 306:443-447. 2. Ullsperger M., von Cramon D.Y. (2004). Neuroimaging of performance monitoring: Error detection and beyond. Cortex, 40:593-604. 3. Botvinick M.M., Braver T.S., Barch D.M., Carter C.S., Cohen J.D. (2001). Conflict monitoring and cognitive control. Psychological Review, 108:624-652. 4. Luu P., Flaisch T., Tucker D.M. (2000). Medial frontal cortex in action monitoring. J. Neurosci., 20:464-469. 5. Bartholow B.D., Pearson M.A., Dickter C.L., Sher K.J., Fabiani M., Gratton G. (2005). Strategic control and medial frontal negativity: beyond errors and response conflict. Psychophysiology. 42:33-42. 6. Taylor S.F., Stern E.R., Gehring W.J. (2007). Neural systems for error monitoring: recent findings and theoretical perspectives. Neuroscientist, 13:160-172. 7. Vidal F., Hasbroucq T., Grapperon J., Bonnet M. (2000). Is the 'error negativity' specific to errors? Biol Psychol, 51:109-128. 8. Botvinick M., Nystrom L.E., Fissell K., Carter C.S., Cohen J.D. (1999). Conflict monitoring versus selection-for-action in anterior cingulate cortex. Nature, 402:179-181. 9. Egner T., Hirsch J. (2005). The neural correlates and functional integration of cognitive control in a Stroop task. NeuroImage, 24:539-547. 10. Gratton G., Coles M.G., Donchin E. (1992) .Optimizing the use of information: strategic control of activation of responses. J Exp Psychol Gen, 121:480-506. 11. Kerns J.G., Cohen J.D., MacDonald A.W., 3rd, Cho R.Y., Stenger V.A., Carter C.S. (2004). Anterior cingulate conflict monitoring and adjustments in control. Science, 303:1023-1026. 12. Belouchrani A., Abed-Meraim K., Cardoso J-F, Moulines E. (1997). A blind source separation technique using second-order statistics. IEEE Trans on Signal Proc, 45:434-444. 13. Tang A.C., Sutherland M.T., McKinney C.J. (2005). Validation of SOBI components from high density EEG. NeuoImage, 25:539-553. Number of preceding trials Participants •Right-handed, healthy volunteers •Behavioral task: n=24 (12 males), mean age=24.6, range= 18-35 •EEG + behavioral task: n=24 (12 males), mean age=23.7, range=18-31 Task •Stroop color-identification task requiring button press responses. •2 x 2 x 4(3) repeated measures design with factors of preceding-trial type (congruent vs. incongruent), ending-trial type (Congruent vs. Incongruent), and number of preceding trials (contextual manipulation, cm: 1, 3, 5, [7]). Each cell in the design is referred to as a “mini-block”. • Example of a single “mini-block”: EEG Data Collection •Continuous 128 channel data, sampling rate: 1000Hz, bandpass:1-100 Hz, nose reference, electrode locations recorded in 3D space. Number of preceding trials CM-1 vs 3,5: F(1,23) = 3.25, p = 0.085 Preceding trial(s) 2. Preceding-trial assessment: RT and CRN amplitude differed across preceding trial numbers 4. Modulation of RT was unlikely to be explained as a speed-accuracy tradeoff: Error rates CM-1 CM-3 CM-5 CM-7 Preceding trial(s) Inc. Con. This work was funded by a grant to ACT from the Sandia National Labs (#75111). We thank Amy Korzekwa, Masato Nakazawa, and Zhen Yang for assistance during data collection. Preceding trial number Preceding trial(s)

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