Go to the content. | Move to the navigation | Go to the site search | Go to the menu | Contacts | Accessibility

| Create Account

Tafuro, Alessandra (2019) Tracking Cognitive Control: How do we solve interference? [Ph.D. thesis]

Full text disponibile come:

[img]
Preview
PDF Document
10Mb

Abstract (italian or english)

Selecting relevant information in the presence of distracting one is a core component of cognitive control, referred as interference resolution. This process has been often investigated through the Stroop task, where responses are longer when two stimulus features are incongruent, compared to when they are congruent (Stroop effect). Despite a large body of literature about this process, the mechanisms of interference resolution are still matter of debate. The present PhD project aimed at shedding light on the temporal dynamics of interference resolution and the related neural underpinnings. In Study 1 we focused on investigating the brain oscillations involved in this process during a spatial Stroop task, aiming at understanding if these correlates and their temporal course change across the lifespan by recruiting younger and older adults. We found age-related differences in theta and beta bands. Theta may represent an early mechanism signalling the need to exert control, which seems to be impaired with aging. Beta may correspond to the process of relevant information selection and older adults showed an over-recruitment of these frequencies. Previous evidence suggested that these results may be attributed to age-related differences in the use of proactive and reactive control, in line with the DMC (Dual Mode of Control) model. Proactive control is defined as an anticipatory attentional bias, whereas reactive control as a late correction mechanism. To study more in depth the different contribution of these control modes, we developed Study 2. We used the same task, manipulating the percentage of congruency (PC) at different levels, list or item, to elicit proactive and reactive control respectively. We also recorded computer mouse trajectories because the high temporal resolution of this tool can shed light on the underlying temporal dynamics of these control modes. Analysis of mouse-derived measures showed that the Stroop effect was present as costs in responding to incongruent trials, reflected in a greater attraction toward the irrelevant information, less smooth trajectories, and longer time to respond due to the updating and adjustments of the trajectories. We found that the magnitude of the interference varied as a function of the PC manipulations, with smaller Stroop interference for low-PC manipulations. Our results suggested also that reactive control may work faster than previously thought, possibly triggering a rapid attentional bias toward the relevant information similar to the one predicted for proactive control. To investigate further the role of proactive control it was necessary to study the time preceding stimulus appearance. Hence, we developed Study 3 in which we used the same mouse-tracking task, manipulating the PC at the list level to mainly elicit proactive control, and we recorded EEG signal to have a window on the brain dynamics before stimulus presentation. We found clear PC-dependent modulations of the interference, both at the behavioural and the neural level, for which we found smaller Stroop effect for blocks with low PC. Behavioural results generally replicated those of Study 2. EEG results showed PC-related modulations of interference, which mirrored the same pattern observed in mouse-derived measures and mainly involved theta and beta bands. This project provides confirmations and new suggestions in the study of interference resolution. We confirmed the involvement of theta in this process, interpreted as an early mechanism of interference detection that signals the need to exert control. We also found a main involvement of beta that may represent the imposition of early attentional biases toward the relevant information. We interpreted these results in line with the Cascade of Control and the DMC models. This project represents a first attempt to evaluate more deeply the temporal course of proactive and reactive control, taking advantages of two techniques with high temporal resolution.


Statistiche Download
EPrint type:Ph.D. thesis
Tutor:Vallesi, Antonino
Ph.D. course:Ciclo 32 > Corsi 32 > SCIENZE PSICOLOGICHE
Data di deposito della tesi:25 November 2019
Anno di Pubblicazione:25 November 2019
More information:Chapter 1 is derived from the following publication: Tafuro, A., Ambrosini, E., Puccioni, O., & Vallesi, A. (2019). Brain oscillations in cognitive control: A cross-sectional study with a spatial stroop task. in: Neuropsychologia, 107190. https://doi.org/10.1016/j.neuropsychologia.2019.107190
Key Words:controllo cognitivo/cognitive control, controllo dell'interferenza/interference control, effetto Stroop/Stroop effect, EEG, tracciamento del mouse/muose-tracking
Settori scientifico-disciplinari MIUR:Area 11 - Scienze storiche, filosofiche, pedagogiche e psicologiche > M-PSI/02 Psicobiologia e psicologia fisiologica
Struttura di riferimento:Dipartimenti > Dipartimento di Neuroscienze
Codice ID:12097
Depositato il:25 Jan 2021 11:23
Simple Metadata
Full Metadata
EndNote Format

Bibliografia

I riferimenti della bibliografia possono essere cercati con Cerca la citazione di AIRE, copiando il titolo dell'articolo (o del libro) e la rivista (se presente) nei campi appositi di "Cerca la Citazione di AIRE".
Le url contenute in alcuni riferimenti sono raggiungibili cliccando sul link alla fine della citazione (Vai!) e tramite Google (Ricerca con Google). Il risultato dipende dalla formattazione della citazione.

Ambrosini, E., & Vallesi, A. (2017). Domain-general Stroop performance and hemispheric asymmetries: a resting-state EEG study. Journal of cognitive neuroscience, 29(5), 769-779. Cerca con Google

Antzoulatos, E. G., & Miller, E. K. (2016). Synchronous beta rhythms of frontoparietal networks support only behaviorally relevant representations. ELife, 5. Cerca con Google

Appelbaum, L. G., Boehler, C. N., Davis, L. A., Won, R. J., & Woldorff, M. G. (2014). The dynamics of proactive and reactive cognitive control processes in the human brain. Journal of cognitive neuroscience, 26(5), 1021-1038. Cerca con Google

Association, W. M. (2013). World Medical Association Declaration of Helsinki: Ethical Principles for Medical Research Involving Human SubjectsWorld Medical Association Declaration of HelsinkiSpecial Communication. JAMA, 310(20), 2191-2194. doi:10.1001/jama.2013.281053 Cerca con Google

Augustinova, M., Parris, B. A., & Ferrand, L. (2019). The Loci of Stroop Interference and Facilitation Effects With Manual and Vocal Responses. Frontiers in psychology, 10. Cerca con Google

Augustinova, M., Silvert, L., Spatola, N., & Ferrand, L. (2018). Further investigation of distinct components of Stroop interference and of their reduction by short response-stimulus intervals. Acta psychologica, 189, 54-62. Cerca con Google

Aulická, Š. R., Jurák, P., Chládek, J., Daniel, P., Halámek, J., Baláž, M., . . . Rektor, I. (2014). Subthalamic nucleus involvement in executive functions with increased cognitive load: a subthalamic nucleus and anterior cingulate cortex depth recording study. Journal of neural transmission, 121(10), 1287-1296. Cerca con Google

Axmacher, N., Henseler, M. M., Jensen, O., Weinreich, I., Elger, C. E., & Fell, J. (2010). Cross-frequency coupling supports multi-item working memory in the human hippocampus. Proceedings of the National Academy of Sciences, 107(7), 3228-3233. Cerca con Google

Baayen, R. H., Davidson, D. J., & Bates, D. M. (2008). Mixed-effects modeling with crossed random effects for subjects and items. Journal of memory and language, 59(4), 390-412. Cerca con Google

Baillet, S., Riera, J., Marin, G., Mangin, J., Aubert, J., & Garnero, L. (2001). Evaluation of inverse methods and head models for EEG source localization using a human skull phantom. Physics in medicine & biology, 46(1), 77. Cerca con Google

Banich, M. T. (2009). Executive function: The search for an integrated account. Current directions in psychological science, 18(2), 89-94. Cerca con Google

Banich, M. T., Milham, M. P., Atchley, R., Cohen, N. J., Webb, A., Wszalek, T., . . . Shenker, J. (2000). fMRI studies of Stroop tasks reveal unique roles of anterior and posterior brain systems in attentional selection. Journal of cognitive neuroscience, 12(6), 988-1000. Cerca con Google

Bates, D., Maechler, M., Bolker, B., & Walker, S. (2014). lme4: Linear mixed-effects models using S4 classes. R package version 1.1-7. URL http://CRAN. R-project. org/package= lme4. Vai! Cerca con Google

Blais, C., & Bunge, S. (2010). Behavioral and neural evidence for item-specific performance monitoring. Journal of Cognitive Neuroscience, 22(12), 2758-2767. Cerca con Google

Botvinick, M. M., Braver, T. S., Barch, D. M., Carter, C. S., & Cohen, J. D. (2001). Conflict monitoring and cognitive control. Psychological review, 108(3), 624. Cerca con Google

Botvinick, M. M., Cohen, J. D., & Carter, C. S. (2004). Conflict monitoring and anterior cingulate cortex: an update. Trends in cognitive sciences, 8(12), 539-546. Cerca con Google

Boulinguez, P., Ferrois, M., & Graumer, G. (2003). Hemispheric asymmetry for trajectory perception. Cognitive brain research, 16(2), 219-225. Cerca con Google

Box, G. E., & Cox, D. R. (1964). An analysis of transformations. Journal of the Royal Statistical Society: Series B (Methodological), 26(2), 211-243. Cerca con Google

Braver, T. S. (2012). The variable nature of cognitive control: a dual mechanisms framework. Trends in cognitive sciences, 16(2), 106-113. Cerca con Google

Braver, T. S., Gray, J. R., & Burgess, G. C. (2007). Explaining the many varieties of working memory variation: Dual mechanisms of cognitive control. Variation in working memory, 75, 106. Cerca con Google

Braver, T. S., Paxton, J. L., Locke, H. S., & Barch, D. M. (2009). Flexible neural mechanisms of cognitive control within human prefrontal cortex. Proceedings of the National Academy of Sciences, 106(18), 7351-7356. Cerca con Google

Bugg, J. M. (2014). Evidence for the sparing of reactive cognitive control with age. Psychology and Aging, 29(1), 115. Cerca con Google

Bugg, J. M. (2017). Context, conflict, and control. The Wiley handbook of cognitive control, 79-96. Cerca con Google

Bugg, J. M., & Chanani, S. (2011). List-wide control is not entirely elusive: Evidence from picture–word Stroop. Psychonomic bulletin & review, 18(5), 930-936. Cerca con Google

Bugg, J. M., & Crump, M. J. (2012). In support of a distinction between voluntary and stimulus-driven control: A review of the literature on proportion congruent effects. Frontiers in psychology, 3, 367. Cerca con Google

Bugg, J. M., DeLosh, E. L., Davalos, D. B., & Davis, H. P. (2007). Age differences in Stroop interference: Contributions of general slowing and task-specific deficits. Aging, Neuropsychology, and Cognition, 14(2), 155-167. Cerca con Google

Bugg, J. M., & Hutchison, K. A. (2013). Converging evidence for control of color–word Stroop interference at the item level. Journal of Experimental Psychology: Human Perception and Performance, 39(2), 433. Cerca con Google

Bugg, J. M., Jacoby, L. L., & Chanani, S. (2011). Why it is too early to lose control in accounts of item-specific proportion congruency effects. Journal of Experimental Psychology: Human Perception and Performance, 37(3), 844. Cerca con Google

Bugg, J. M., Jacoby, L. L., & Toth, J. P. (2008). Multiple levels of control in the Stroop task. Memory & cognition, 36(8), 1484-1494. Cerca con Google

Bugg, J. M., McDaniel, M. A., Scullin, M. K., & Braver, T. S. (2011). Revealing list-level control in the Stroop task by uncovering its benefits and a cost. Journal of Experimental Psychology: Human Perception and Performance, 37(5), 1595. Cerca con Google

Bundt, C., Ruitenberg, M. F., Abrahamse, E. L., & Notebaert, W. (2018). Early and late indications of item-specific control in a Stroop mouse tracking study. PloS one, 13(5), e0197278. Cerca con Google

Cabeza, R. (2002). Hemispheric asymmetry reduction in older adults: the HAROLD model. Psychology and aging, 17(1), 85. Cerca con Google

Canolty, R. T., Edwards, E., Dalal, S. S., Soltani, M., Nagarajan, S. S., Kirsch, H. E., . . . Knight, R. T. (2006). High gamma power is phase-locked to theta oscillations in human neocortex. science, 313(5793), 1626-1628. Cerca con Google

Canolty, R. T., & Knight, R. T. (2010). The functional role of cross-frequency coupling. Trends in cognitive sciences, 14(11), 506-515. Cerca con Google

Cavanagh, J. F., & Frank, M. J. (2014). Frontal theta as a mechanism for cognitive control. Trends in cognitive sciences, 18(8), 414-421. Cerca con Google

Cavanagh, J. F., Zambrano‐Vazquez, L., & Allen, J. J. (2012). Theta lingua franca: A common mid‐frontal substrate for action monitoring processes. Psychophysiology, 49(2), 220-238. Cerca con Google

Cerella, J. (1990). Aging and information-processing rate. In Handbook of the Psychology of Aging (Third Edition) (pp. 201-221): Elsevier. Cerca con Google

Chang, A., Ide, J. S., Li, H.-H., Chen, C.-C., & Li, C.-S. R. (2017). Proactive control: Neural oscillatory correlates of conflict anticipation and response slowing. eNeuro, 4(3). Cerca con Google

Cohen, M. X. (2014). A neural microcircuit for cognitive conflict detection and signaling. Trends in neurosciences, 37(9), 480-490. Cerca con Google

Cohen, M. X. (2017). Where does EEG come from and what does it mean? Trends in neurosciences, 40(4), 208-218. Cerca con Google

Colás, I., Capilla, A., & Chica, A. B. (2018). Neural modulations of interference control over conscious perception. Neuropsychologia, 112, 40-49. Cerca con Google

Cooper, P. S., Karayanidis, F., McKewen, M., McLellan-Hall, S., Wong, A. S., Skippen, P., & Cavanagh, J. F. (2019). Frontal theta predicts specific cognitive control-induced behavioural changes beyond general reaction time slowing. Neuroimage, 189, 130-140. Cerca con Google

Cooper, P. S., Wong, A. S., Fulham, W. R., Thienel, R., Mansfield, E., Michie, P. T., & Karayanidis, F. (2015). Theta frontoparietal connectivity associated with proactive and reactive cognitive control processes. Neuroimage, 108, 354-363. Cerca con Google

Cooper, P. S., Wong, A. S., McKewen, M., Michie, P. T., & Karayanidis, F. (2017). Frontoparietal theta oscillations during proactive control are associated with goal-updating and reduced behavioral variability. Biological psychology, 129, 253-264. Cerca con Google

Crump, M. J., Gong, Z., & Milliken, B. (2006). The context-specific proportion congruent Stroop effect: Location as a contextual cue. Psychonomic bulletin & review, 13(2), 316-321. Cerca con Google

De Houwer, J. (2003). On the role of stimulus-response and stimulus-stimulus compatibility in the Stroop effect. Memory & Cognition, 31(3), 353-359. Cerca con Google

Delorme, A., & Makeig, S. (2004). EEGLAB: an open source toolbox for analysis of single-trial EEG dynamics including independent component analysis. Journal of neuroscience methods, 134(1), 9-21. Cerca con Google

Delorme, A., Sejnowski, T., & Makeig, S. (2007). Enhanced detection of artifacts in EEG data using higher-order statistics and independent component analysis. Neuroimage, 34(4), 1443-1449. Cerca con Google

Derrfuss, J., Brass, M., Neumann, J., & von Cramon, D. Y. (2005). Involvement of the inferior frontal junction in cognitive control: Meta‐analyses of switching and Stroop studies. Human brain mapping, 25(1), 22-34. Cerca con Google

Diamond, A. (2013). Executive functions. Annual review of psychology, 64, 135-168. Cerca con Google

Egner, T., & Hirsch, J. (2005). Cognitive control mechanisms resolve conflict through cortical amplification of task-relevant information. Nature neuroscience, 8(12), 1784. Cerca con Google

Engel, A. K., & Fries, P. (2010). Beta-band oscillations—signalling the status quo? Current opinion in neurobiology, 20(2), 156-165. Cerca con Google

Ergen, M., Saban, S., Kirmizi-Alsan, E., Uslu, A., Keskin-Ergen, Y., & Demiralp, T. (2014). Time–frequency analysis of the event-related potentials associated with the Stroop test. International Journal of Psychophysiology, 94(3), 463-472. Cerca con Google

Eriksen, B. A., & Eriksen, C. W. (1974). Effects of noise letters upon the identification of a target letter in a nonsearch task. Perception & psychophysics, 16(1), 143-149. Cerca con Google

Eschmann, K. C., Bader, R., & Mecklinger, A. (2018). Topographical differences of frontal-midline theta activity reflect functional differences in cognitive control abilities. Brain and cognition, 123, 57-64. Cerca con Google

Faul, F., Erdfelder, E., Buchner, A., & Lang, A.-G. (2009). Statistical power analyses using G*Power 3.1: Tests for correlation and regression analyses. Behavior Research Methods, 41(4), 1149-1160. doi:10.3758/brm.41.4.1149 Cerca con Google

Faust, M. E., Balota, D. A., Spieler, D. H., & Ferraro, F. R. (1999). Individual differences in information-processing rate and amount: implications for group differences in response latency. Psychological bulletin, 125(6), 777. Cerca con Google

Ferreira, C. S., Maraver, M. J., Hanslmayr, S., & Bajo, T. (2019). Theta oscillations show impaired interference detection in older adults during selective memory retrieval. Scientific reports, 9(1), 9977. Cerca con Google

Fischl, B., Sereno, M. I., Tootell, R. B., & Dale, A. M. (1999). High‐resolution intersubject averaging and a coordinate system for the cortical surface. Human brain mapping, 8(4), 272-284. Cerca con Google

Fjell, A. M., & Walhovd, K. B. (2010). Structural brain changes in aging: courses, causes and cognitive consequences. Reviews in the Neurosciences, 21(3), 187-222. Cerca con Google

Floden, D., Vallesi, A., & Stuss, D. T. (2011). Task context and frontal lobe activation in the Stroop task. Journal of Cognitive Neuroscience, 23(4), 867-879. Cerca con Google

Forstmann, B. U., Tittgemeyer, M., Wagenmakers, E.-J., Derrfuss, J., Imperati, D., & Brown, S. (2011). The speed-accuracy tradeoff in the elderly brain: a structural model-based approach. Journal of Neuroscience, 31(47), 17242-17249. Cerca con Google

Freeman, J., Dale, R., & Farmer, T. (2011). Hand in motion reveals mind in motion. Frontiers in Psychology, 2, 59. Cerca con Google

Freeman, J. B., & Ambady, N. (2010). MouseTracker: Software for studying real-time mental processing using a computer mouse-tracking method. Behavior research methods, 42(1), 226-241. Cerca con Google

Freeman, J. B., & Ambady, N. (2011). A dynamic interactive theory of person construal. Psychological review, 118(2), 247. Cerca con Google

Friedman, N. P., & Miyake, A. (2004). The relations among inhibition and interference control functions: a latent-variable analysis. Journal of experimental psychology: General, 133(1), 101. Cerca con Google

Fries, P. (2005). A mechanism for cognitive dynamics: neuronal communication through neuronal coherence. Trends in cognitive sciences, 9(10), 474-480. Cerca con Google

Gazzaley, A., & D'esposito, M. (2007). Top‐down modulation and normal aging. Annals of the New York Academy of Sciences, 1097(1), 67-83. Cerca con Google

Goh, J. O. (2011). Functional dedifferentiation and altered connectivity in older adults: neural accounts of cognitive aging. Aging and disease, 2(1), 30. Cerca con Google

Gonthier, C., Braver, T. S., & Bugg, J. M. (2016). Dissociating proactive and reactive control in the Stroop task. Memory & Cognition, 44(5), 778-788. Cerca con Google

Gould, I. C., Nobre, A. C., Wyart, V., & Rushworth, M. F. (2012). Effects of decision variables and intraparietal stimulation on sensorimotor oscillatory activity in the human brain. Journal of Neuroscience, 32(40), 13805-13818. Cerca con Google

Gramfort, A., Papadopoulo, T., Olivi, E., & Clerc, M. (2010). OpenMEEG: opensource software for quasistatic bioelectromagnetics. Biomedical engineering online, 9(1), 45. Cerca con Google

Greenwood, P. M. (2000). The frontal aging hypothesis evaluated. Journal of the International Neuropsychological Society, 6(6), 705-726. Cerca con Google

Haegens, S., Nácher, V., Hernández, A., Luna, R., Jensen, O., & Romo, R. (2011). Beta oscillations in the monkey sensorimotor network reflect somatosensory decision making. Proceedings of the National Academy of Sciences, 108(26), 10708-10713. Cerca con Google

Hanslmayr, S., Pastötter, B., Bäuml, K.-H., Gruber, S., Wimber, M., & Klimesch, W. (2008). The electrophysiological dynamics of interference during the Stroop task. Journal of Cognitive Neuroscience, 20(2), 215-225. Cerca con Google

Hasher, L., & Zacks, R. T. (1988). Working memory, comprehension, and aging: A review and a new view. In Psychology of learning and motivation (Vol. 22, pp. 193-225): Elsevier. Cerca con Google

He, W., Goodkind, D., & Kowal, P. (2016). US Census Bureau, international population reports. An Aging World: 2015, 16-11. Cerca con Google

Hehman, E., Stolier, R. M., & Freeman, J. B. (2015). Advanced mouse-tracking analytic techniques for enhancing psychological science. Group Processes & Intergroup Relations, 18(3), 384-401. Cerca con Google

Horn, J. L. (1965). A rationale and test for the number of factors in factor analysis. Psychometrika, 30(2), 179-185. Cerca con Google

Incera, S., & McLennan, C. T. (2016). Mouse tracking reveals that bilinguals behave like experts. Bilingualism: Language and Cognition, 19(3), 610-620. Cerca con Google

Jacoby, L. L., Lindsay, D. S., & Hessels, S. (2003). Item-specific control of automatic processes: Stroop process dissociations. Psychonomic Bulletin & Review, 10(3), 638-644. Cerca con Google

Jensen, O., Kaiser, J., & Lachaux, J.-P. (2007). Human gamma-frequency oscillations associated with attention and memory. Trends in neurosciences, 30(7), 317-324. Cerca con Google

Jiang, J., van Gaal, S., Bailey, K., Chen, A., & Zhang, Q. (2013). Electrophysiological correlates of block-wise strategic adaptations to consciously and unconsciously triggered conflict. Neuropsychologia, 51(13), 2791-2798. Cerca con Google

Jurkiewicz, M. T., Gaetz, W. C., Bostan, A. C., & Cheyne, D. (2006). Post-movement beta rebound is generated in motor cortex: evidence from neuromagnetic recordings. Neuroimage, 32(3), 1281-1289. Cerca con Google

Kayser, J. (2009). Current source density (CSD) interpolation using spherical splines-CSD Toolbox (Version 1.1). New York State Psychiatric Institute: Division of Cognitive Neuroscience. Cerca con Google

Kleiner, M., Brainard, D., & Pelli, D. (2007). What's new in Psychtoolbox-3? Cerca con Google

Kornblum, S., & Stevens, G. (2002). Sequential effects of dimensional overlap: Findings and issues. Common mechanisms in perception and action, 19, 9-54. Cerca con Google

Kuznetsova, A., Brockhoff, P. B., & Christensen, R. H. B. (2017). lmerTest package: tests in linear mixed effects models. Journal of Statistical Software, 82(13). Cerca con Google

Kybic, J., Clerc, M., Abboud, T., Faugeras, O., Keriven, R., & Papadopoulo, T. (2005). A common formalism for the integral formulations of the forward EEG problem. IEEE transactions on medical imaging, 24(1), 12-28. Cerca con Google

Lindsay, D. S., & Jacoby, L. L. (1994). Stroop process dissociations: The relationship between facilitation and interference. Journal of Experimental Psychology: Human Perception and Performance, 20(2), 219. Cerca con Google

Logan, G. D. (1998). What is learned during automatization? II. Obligatory encoding of spatial location. Journal of Experimental Psychology: Human Perception and Performance, 24(6), 1720. Cerca con Google

Logan, G. D., & Zbrodoff, N. J. (1979). When it helps to be misled: Facilitative effects of increasing the frequency of conflicting stimuli in a Stroop-like task. Memory & cognition, 7(3), 166-174. Cerca con Google

Luo, C. R. (1999). Semantic competition as the basis of Stroop interference: Evidence from color-word matching tasks. Psychological Science, 10(1), 35-40. Cerca con Google

MacLeod, C. M. (1991). Half a century of research on the Stroop effect: an integrative review. Psychological bulletin, 109(2), 163. Cerca con Google

MacLeod, C. M., Dodd, M. D., Sheard, E. D., Wilson, D. E., & Bibi, U. (2003). In opposition to inhibition. Psychology of learning and motivation, 43, 163-215. Cerca con Google

Meindertsma, T., Kloosterman, N. A., Engel, A. K., Wagenmakers, E.-J., & Donner, T. H. (2018). Surprise about sensory event timing drives cortical transients in the beta frequency band. Journal of Neuroscience, 38(35), 7600-7610. Cerca con Google

Milham, M., Banich, M., Claus, E., & Cohen, N. (2003). Practice-related effects demonstrate complementary roles of anterior cingulate and prefrontal cortices in attentional control. Neuroimage, 18(2), 483-493. Cerca con Google

Milham, M., Banich, M., Webb, A., Barad, V., Cohen, N., Wszalek, T., & Kramer, A. (2001). The relative involvement of anterior cingulate and prefrontal cortex in attentional control depends on nature of conflict. Cognitive Brain Research, 12(3), 467-473. Cerca con Google

Milham, M. P., & Banich, M. T. (2005). Anterior cingulate cortex: an fMRI analysis of conflict specificity and functional differentiation. Human brain mapping, 25(3), 328-335. Cerca con Google

Milham, M. P., Banich, M. T., & Barad, V. (2003). Competition for priority in processing increases prefrontal cortex’s involvement in top-down control: an event-related fMRI study of the stroop task. Cognitive brain research, 17(2), 212-222. Cerca con Google

Milham, M. P., Erickson, K. I., Banich, M. T., Kramer, A. F., Webb, A., Wszalek, T., & Cohen, N. J. (2002). Attentional control in the aging brain: insights from an fMRI study of the stroop task. Brain and cognition, 49(3), 277-296. Cerca con Google

Miller, E. K., & Cohen, J. D. (2001). An integrative theory of prefrontal cortex function. Annual review of neuroscience, 24(1), 167-202. Cerca con Google

Miyake, A., Friedman, N. P., Emerson, M. J., Witzki, A. H., Howerter, A., & Wager, T. D. (2000). The unity and diversity of executive functions and their contributions to complex “frontal lobe” tasks: A latent variable analysis. Cognitive psychology, 41(1), 49-100. Cerca con Google

Mullen, T., Kothe, C., Chi, Y. M., Ojeda, A., Kerth, T., Makeig, S., . . . Jung, T.-P. (2013). Real-time modeling and 3D visualization of source dynamics and connectivity using wearable EEG. Paper presented at the 2013 35th annual international conference of the IEEE engineering in medicine and biology society (EMBC). Cerca con Google

Munakata, Y., Herd, S. A., Chatham, C. H., Depue, B. E., Banich, M. T., & O’Reilly, R. C. (2011). A unified framework for inhibitory control. Trends in cognitive sciences, 15(10), 453-459. Cerca con Google

Nasreddine, Z. S., Phillips, N. A., Bédirian, V., Charbonneau, S., Whitehead, V., Collin, I., . . . Chertkow, H. (2005). The Montreal Cognitive Assessment, MoCA: a brief screening tool for mild cognitive impairment. Journal of the American Geriatrics Society, 53(4), 695-699. Cerca con Google

Nigbur, R., Ivanova, G., & Stürmer, B. (2011). Theta power as a marker for cognitive interference. Clinical Neurophysiology, 122(11), 2185-2194. Cerca con Google

Nigg, J. T. (2000). On inhibition/disinhibition in developmental psychopathology: views from cognitive and personality psychology and a working inhibition taxonomy. Psychological bulletin, 126(2), 220. Cerca con Google

Norman, D. A., & Shallice, T. (1986). Attention to action. In Consciousness and self-regulation (pp. 1-18): Springer. Cerca con Google

Oldfield, R. C. (1971). The assessment and analysis of handedness: the Edinburgh inventory. Neuropsychologia, 9(1), 97-113. Cerca con Google

Park, D. C., & Reuter-Lorenz, P. (2009). The adaptive brain: aging and neurocognitive scaffolding. Annual review of psychology, 60, 173-196. Cerca con Google

Paxton, J. L., Barch, D. M., Racine, C. A., & Braver, T. S. (2007). Cognitive control, goal maintenance, and prefrontal function in healthy aging. Cerebral cortex, 18(5), 1010-1028. Cerca con Google

Perrin, F., Pernier, J., Bertrand, O., & Echallier, J. (1989). Spherical splines for scalp potential and current density mapping. Electroencephalography and clinical neurophysiology, 72(2), 184-187. Cerca con Google

Pratte, M. S., Rouder, J. N., Morey, R. D., & Feng, C. (2010). Exploring the differences in distributional properties between Stroop and Simon effects using delta plots. Attention, Perception, & Psychophysics, 72(7), 2013-2025. Cerca con Google

Puccioni, O., & Vallesi, A. (2012). High cognitive reserve is associated with a reduced age-related deficit in spatial conflict resolution. Frontiers in human neuroscience, 6, 327. Cerca con Google

Reuter-Lorenz, P. A., & Park, D. C. (2010). Human neuroscience and the aging mind: a new look at old problems. The Journals of Gerontology: Series B, 65(4), 405-415. Cerca con Google

Reuter-Lorenz, P. A., & Park, D. C. (2014). How does it STAC up? Revisiting the scaffolding theory of aging and cognition. Neuropsychology review, 24(3), 355-370. Cerca con Google

Roach, B. J., & Mathalon, D. H. (2008). Event-related EEG time-frequency analysis: an overview of measures and an analysis of early gamma band phase locking in schizophrenia. Schizophrenia bulletin, 34(5), 907-926. Cerca con Google

Roelofs, A. (1997). The WEAVER model of word-form encoding in speech production. Cognition, 64(3), 249-284. Cerca con Google

Ruitenberg, M. F., Braem, S., Du Cheyne, H., & Notebaert, W. (2019). Learning to be in control involves response-specific mechanisms. Attention, Perception, & Psychophysics, 1-12. Cerca con Google

Salinas, E., & Sejnowski, T. J. (2001). Correlated neuronal activity and the flow of neural information. Nature reviews neuroscience, 2(8), 539. Cerca con Google

Salthouse, T. A. (1996). The processing-speed theory of adult age differences in cognition. Psychological review, 103(3), 403. Cerca con Google

Sauseng, P., Griesmayr, B., Freunberger, R., & Klimesch, W. (2010). Control mechanisms in working memory: a possible function of EEG theta oscillations. Neuroscience & Biobehavioral Reviews, 34(7), 1015-1022. Cerca con Google

Schmidt, J. R., & Besner, D. (2008). The Stroop effect: why proportion congruent has nothing to do with congruency and everything to do with contingency. Journal of Experimental Psychology: Learning, Memory, and Cognition, 34(3), 514. Cerca con Google

Siegel, M., Engel, A. K., & Donner, T. H. (2011). Cortical network dynamics of perceptual decision-making in the human brain. Frontiers in human neuroscience, 5, 21. Cerca con Google

Simon, J. R., & Small Jr, A. (1969). Processing auditory information: interference from an irrelevant cue. Journal of Applied Psychology, 53(5), 433. Cerca con Google

Smith, S. M., & Nichols, T. E. (2009). Threshold-free cluster enhancement: addressing problems of smoothing, threshold dependence and localisation in cluster inference. Neuroimage, 44(1), 83-98. Cerca con Google

Spitzer, B., & Haegens, S. (2017). Beyond the status quo: A role for beta oscillations in endogenous content (re) activation. Eneuro, 4(4), ENEURO. 0170-0117.2017. Cerca con Google

Spivey, M. J., Grosjean, M., & Knoblich, G. (2005). Continuous attraction toward phonological competitors. Proceedings of the National Academy of Sciences, 102(29), 10393-10398. Cerca con Google

Stroop, J. R. (1935). Studies of interference in serial verbal reactions. Journal of experimental psychology, 18(6), 643. Cerca con Google

Sturz, B. R., Green, M. L., Locker Jr, L., & Boyer, T. W. (2013). Stroop interference in a delayed match-to-sample task: Evidence for semantic competition. Frontiers in psychology, 4, 842. Cerca con Google

Stuss, D. T. (2011). Functions of the frontal lobes: relation to executive functions. Journal of the international neuropsychological Society, 17(5), 759-765. Cerca con Google

Stuss, D. T., & Alexander, M. P. (2007). Is there a dysexecutive syndrome? Philosophical Transactions of the Royal Society B: Biological Sciences, 362(1481), 901-915. Cerca con Google

Stuss, D. T., & Levine, B. (2002). Adult clinical neuropsychology: lessons from studies of the frontal lobes. Annual review of psychology, 53(1), 401-433. Cerca con Google

Sullivan, N., Hutcherson, C., Harris, A., & Rangel, A. (2015). Dietary self-control is related to the speed with which attributes of healthfulness and tastiness are processed. Psychological science, 26(2), 122-134. Cerca con Google

Szczepanski, S. M., & Knight, R. T. (2014). Insights into human behavior from lesions to the prefrontal cortex. Neuron, 83(5), 1002-1018. Cerca con Google

Tadel, F., Baillet, S., Mosher, J. C., Pantazis, D., & Leahy, R. M. (2011). Brainstorm: a user-friendly application for MEG/EEG analysis. Computational intelligence and neuroscience, 2011, 8. Cerca con Google

Vallesi, A. (2012). Organisation of executive functions: hemispheric asymmetries. Journal of Cognitive Psychology, 24(4), 367-386. Cerca con Google

Vallesi, A., Stuss, D. T., McIntosh, A. R., & Picton, T. W. (2009). Age-related differences in processing irrelevant information: evidence from event-related potentials. Neuropsychologia, 47(2), 577-586. Cerca con Google

Van Driel, J., Ort, E., Fahrenfort, J. J., & Olivers, C. N. (2019). Beta and theta oscillations differentially support free versus forced control over multiple-target search. Journal of Neuroscience, 39(9), 1733-1743. Cerca con Google

van Maanen, L., Forstmann, B. U., Keuken, M. C., Wagenmakers, E.-J., & Heathcote, A. (2016). The impact of MRI scanner environment on perceptual decision-making. Behavior research methods, 48(1), 184-200. Cerca con Google

Van Wijk, B., Daffertshofer, A., Roach, N., & Praamstra, P. (2008). A role of beta oscillatory synchrony in biasing response competition? Cerebral Cortex, 19(6), 1294-1302. Cerca con Google

Velicer, W. F., Eaton, C. A., & Fava, J. L. (2000). Construct explication through factor or component analysis: A review and evaluation of alternative procedures for determining the number of factors or components. In Problems and solutions in human assessment (pp. 41-71): Springer. Cerca con Google

Verhaeghen, P., & De Meersman, L. (1998). Aging and the Stroop effect: A meta-analysis. Psychology and aging, 13(1), 120. Cerca con Google

Wang, K., Li, Q., Zheng, Y., Wang, H., & Liu, X. (2014). Temporal and spectral profiles of stimulus–stimulus and stimulus–response conflict processing. Neuroimage, 89, 280-288. Cerca con Google

Weintraub, S., & Mesulam, M.-M. (1987). Right cerebral dominance in spatial attention: Further evidence based on ipsilateral neglect. Archives of neurology, 44(6), 621-625. Cerca con Google

West, R. (2004). The effects of aging on controlled attention and conflict processing in the Stroop task. Journal of cognitive neuroscience, 16(1), 103-113. Cerca con Google

West, R., Bailey, K., Tiernan, B. N., Boonsuk, W., & Gilbert, S. (2012). The temporal dynamics of medial and lateral frontal neural activity related to proactive cognitive control. Neuropsychologia, 50(14), 3450-3460. Cerca con Google

Winkler, I., Debener, S., Müller, K.-R., & Tangermann, M. (2015). On the influence of high-pass filtering on ICA-based artifact reduction in EEG-ERP. Paper presented at the 2015 37th Annual International Conference of the IEEE Engineering in Medicine and Biology Society (EMBC). Cerca con Google

Zavala, B., Brittain, J.-S., Jenkinson, N., Ashkan, K., Foltynie, T., Limousin, P., . . . Zaghloul, K. (2013). Subthalamic nucleus local field potential activity during the Eriksen flanker task reveals a novel role for theta phase during conflict monitoring. Journal of Neuroscience, 33(37), 14758-14766. Cerca con Google

Zhang, H., & Kornblum, S. (1998). The effects of stimulus–response mapping and irrelevant stimulus–response and stimulus–stimulus overlap in four-choice Stroop tasks with single-carrier stimuli. Journal of Experimental Psychology: Human Perception and Performance, 24(1), 3. Cerca con Google

Zhao, J., Liang, W.-K., Juan, C.-H., Wang, L., Wang, S., & Zhu, Z. (2015). Dissociated stimulus and response conflict effect in the Stroop task: Evidence from evoked brain potentials and brain oscillations. Biological psychology, 104, 130-138. Cerca con Google

Download statistics

Solo per lo Staff dell Archivio: Modifica questo record