Processing conflicting information: Facilitation, interference, and functional connectivity
Section snippets
The size congruity paradigm
In the current study we used another conflict paradigm, the size congruity paradigm. In this paradigm, participants had to compare either the numerical value or the physical size of two digits. They indicated their choices by pressing one of two keys corresponding to the side of the display with the selected digit. The two digits differed in both numerical value and physical size, which amounted to a Stroop-like situation (Cohen Kadosh, 2008; Cohen Kadosh, Cohen Kadosh, Linden et al., 2007;
Until what stage does conflict continue?
In a recent study of the SCE (Cohen Kadosh et al., 2007a), we examined whether the conflict between the numerical and the physical comparison occurs at a response-related stage or earlier (e.g., a conceptual stage) by using event-related potential (ERP) and functional magnetic resonance imaging (fMRI). In the fMRI we examined the blood oxygenation level-dependent (BOLD) signal in the motor cortex, using a measure that is equivalent to the lateralized BOLD response (LBR) (Dehaene et al., 1998).
Materials and methods
We analysed fMRI data from a previous study (Cohen Kadosh et al., 2007a) where the general methods were described in full.
Behavioral data
For every participant in each condition the mean RT was calculated for correct trials only. The two-way interaction between task and congruency was not significant (F < 1, p > .2). The main effect for congruency was significant [F(2, 26) = 118.40, p < 0.001, Fig. 1]. Planned comparisons revealed that participants were significantly slower in incongruent than neutral conditions (interference) [F(1, 13) = 76.63, p < .001]. Conversely, they were significantly faster in congruent than neutral conditions
Discussion
We employed the size congruity paradigm to reveal brain areas that are modulated by facilitation and interference in a conflict task, and the functional connectivity of the conflict monitoring and resolution areas.
Conflict of interest
None.
Acknowledgements
The authors wish to thank Vincent van de Ven for help with the functional connectivity analysis, Desiree Meloul and the anonymous referees for valuable comments.
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2019, NeuropsychologiaCitation Excerpt :Although our data doesn’t demonstrate an association with the behavioral update, it seems consistent that this region plays a role in the recognition of social conflict. Not only has this been established in terms of social conflict (see also Seehausen et al., 2014), neuroimaging studies have also shown the PCC to be sensitive in monitoring nonsocial prediction errors and conflict in general (Christoffels et al., 2007; Kadosh et al., 2008). The STG has some similar implications in the monitoring of social conflict (Christoffels et al., 2007).
Conflict detection and resolution rely on a combination of common and distinct cognitive control networks
2017, Neuroscience and Biobehavioral ReviewsCitation Excerpt :However, compared with congruent trials, neutral trials in contrast to incongruent trials indicated greater activation in the dorsal ACC and medial frontal gyrus that related with the competition between the relevant and irrelevant dimensions (Milham et al., 2002), interference monitoring and suppression (Blasi et al., 2006). By contrast, compared with neutral trials, congruent trials as contrast for incongruent trials indicated greater activation in the DLPFC and PC, reflecting the increased attentional requirements (Posner and DiGirolamo, 1998) and the facilitation effects (Mitchell, 2005; Cohen Kadosh et al., 2008; Carter et al., 1995). In this study, we found specific conflict-control loops for the S-S and S-R conflicts, which supports the notion that conflict-driven control mechanisms operate in a conflict-specific manner (Egner, 2008; Egner et al., 2007; Wendt et al., 2006).
Brain stimulation, mathematical, and numerical training: Contribution of core and noncore skills
2016, Progress in Brain ResearchCitation Excerpt :Note that these results were specific to learned materials, but not to noncore skills such as visuospatial abilities as assessed using control tasks. Given that tDCS was applied over the parietal lobes, known as the hub of core numerical processing skills such as facilitation and interference during automatic numerical processing (Cohen Kadosh et al., 2008a), it is unsurprising that the effects were highly specific to trained materials. These results expand to show that the contribution of the parietal lobes toward automatic number processing and representation might be hemispheric-dependent.
Does the learning of two symbolic sets of numbers affect the automaticity of number processing in children?
2014, Journal of Experimental Child PsychologyCitation Excerpt :They found that the differences in the facilitation and interference effects in children and in adults are not a result of numerical or physical magnitude processing alone but rather a result of a stronger response interference in children than in adults (see also Girelli et al., 2000; Rubinsten et al., 2002). These findings also suggest that caution is needed when reaching conclusions about numerical processing skills while interpreting behavioral data of the numerical Stroop task (Szucs et al., 2007; for additional studies of the neuronal components of the SiCE, see also Cohen Kadosh, Cohen Kadosh, Henik, & Linden, 2008; Cohen Kadosh, Cohen Kadosh, Linden, Berger, et al., 2007; Szucs & Soltész, 2008; for additional findings showing the differences in brain activations of children and adults with regard to interference and magnitude processing, see Wood, Ischebeck, Koppelstätter, Gotwald, & Kaufmann, 2009). Another strong effect related to the associations between digits and their numerical value is the distance effect—the larger the numerical difference between two digits, the shorter the time to decide which digit is larger.
Are low and high number magnitudes processed differently while resolving the conflict evoked by the SNARC effect?
2012, International Journal of PsychophysiologyCitation Excerpt :It is well known that the more familiar and practiced the stimuli, the more efficient the retrieval of the numerical magnitude and the faster the reaction time. This finding was confirmed, for instance, with number notations (Campbell and Epp, 2004; Cohen Kadosh et al., 2008). The main effect of the number magnitude on RTs in the SNARC tasks was rarely observed in studies and even if it was, the differences in RTs between the low and high number magnitude stimuli are not discussed in detail.