As expected, LORETA analysis highlighted a prominent activation of the pMFC, with the strongest activity in the BA6 (for x, y, z and BA coordinates, see Table 1); this finding is similar to previous studies that investigated the ERN generator in the Eriksen Flanker task (Herrmann et al., 2004). With respect to cognitive neuroscience, the goal is to know which cognitive functions are associated with specific task manipulations and to – Neurology research can include information involving brain research, neurological disorders, medicine, brain cancer, peripheral nervous systems, central nervous systems, nerve damage, brain tumors, seizures, neurosurgery, electrophysiology, BMI, brain injuries, paralysis and spinal cord treatments. If at the same time, you realize that you believe that smoking is unhealthy and that you regularly smoke, that would be inconsistent. Robotics articles will cover robotics research press releases. We also analyzed the SoA in trials with the highest cognitive dissonance: Self-difficult trials and control Post-ex choice trials. NeuroscienceNew. Here we suggest that the magnitude of cognitive dissonance can be predicted by the resting-state neuronal dynamics recorded with an EEG before a cognitive dissonance-inducing task. We explored the dynamics of subjective coherence in an experimental paradigm (the "free choice "paradigm) originating for the field of cognitive dissonance. Difficult choices generate psychological (cognitive) dissonance, which is reduced by the post-decisional devaluation of unchosen options. Overall, our results showed that (1) participants deevaluated previously rejected items (SoA effect); (2) the SoA effect for rejected items was stronger for more difficult choices associated with stronger cognitive dissonance; and (3) difficult choices are reflected by longer decisional RT. Chen and Risen (2010) indeed found a significant preference change, even in the rate-rate-choose condition, demonstrating that the preference change measured in a typical free-choice paradigm can occur in the absence of cognitive dissonance. For DFA, we used 30 time windows, from 5 to 50 s, distributed equidistantly on a logarithmic scale. LRTCs are characterized by a slow (power-law) decay of autocorrelation, which in turn indicates that past neuronal events might affect the activity of the remote upcoming neuronal activity. Thus, LRTCs do not indicate the connectivity of the brain region but rather its functional state. Because the Eriksen Flanker task is simpler than the free-choice paradigm, a smaller ERN-like potential could reflect more complex and slower mechanisms underlying relatively complex decisions during food choices. Choice-induced preference changes are reflected in the choice-related activity of the pMFC as part of the general performance-monitoring circuitry. For example, pMFC activity is associated with preference changes to reduce cognitive dissonance ( van Veen et al., 2009 ; Izuma et al., 2010 , 2015) and with increases in social conformity upon detecting divergences between one’s stated opinions and group consensus ( Klucharev et al., 2009 ; Izuma and Adolphs, 2013). To the best of our knowledge, the present study is the first EEG study to directly investigate neural correlates of cognitive dissonance during the decisional process. To keep a mental balance, we start thinking that the car we didn’t choose wasn’t that good at all’. At the beginning of the study, subjects sat comfortably in a chair for 10 min with their eyes open while a resting-state recording was performed. New Multiple Sclerosis Subtypes Identified Using Artificial Intelligence, Virtual Humans Are Equal to Real Ones in Helping People Practice New Leadership Skills, Gene That Could Help Prevent or Delay Onset of Alzheimer’s Disease Identified, Neural Plasticity Depends On This Long Noncoding RNA’s Journey From Nucleus to Synapse, Estrogen Status, Not Sex, Protects Against Heightened Fear Recall, I Ain’t Afraid of No Ghosts: People With Mind-Blindness Not So Easily Spooked, Neuroscience Graduate and Undergraduate Programs, Epidural Use At Birth Not Linked to Autism Risk. Cognitive dissonance is a mental conflict that occurs when your beliefs don’t line up with your actions. We provide several examples of cognitive dissonance in this article. Overall, our approach allowed us to investigate similarity between neural mechanisms involved in choice-induced preference changes and more general reinforcement-learning mechanisms. Participants were reminded about their choices (if any) during the Choice task (e.g., “You rejected it”). You may also experience cognitive dissonance, which means that you believe two competing thoughts simultaneously. Next, during Choice task in Self-trials, subjects freely selected one of two food items (Self-difficult trials evoked strong cognitive dissonance, Self-easy trials evoked weak cognitive dissonance), whereas in Computer trials, subjects had to select the item that has been selected by the computational algorithm (highlighted by a red square). Such conflict was indeed reported by participants at the end of the experiment. We reanalyzed the preference changes for food items in Self-easy trials with an initial rating of “3.” Taking into account that the maximum postdecisional preference change in our study was −1.3, these items should be fully susceptible to a downward valuation. Gray line indicates p = 0.083. It suggests that inconsistencies among cognitions (i.e., knowledge, opinion, or belief about the environment, oneself, or one’s behavior) generate an uncomfortable motivating feeling (i.e., the cognitive dissonance state). For example, you might know that the narcissist does awful things. To increase their motivation, participants were informed that they would receive one of the selected food items along with monetary compensation. Original Research: Full open access research for “Neural mechanisms of cognitive dissonance (revised): An EEG study” by Marco Colosio, Anna Shestakova, Vadim V. Nikulin, Evgeny Blagovechtchenski and Vasily Klucharev in Journal of Neuroscience. B, Left, Grand-averaged ERPs (FCz) for Self-difficult, Self-easy, and Computer trials in the free-choice paradigm. Neuroscience News posts science research news from labs, universities, hospitals and news departments around the world. Think of the feeling one could have while eating donuts during a healthy diet or smoking cigarettes while attempting to stop. The SoA for items that were rejected during Self-difficult trials was significantly stronger than it was for items rejected or selected in the control Computer trials: t(41) = −7.143, p < 0.001 and t(41) = −7.263, p < 0.001), respectively. This fMRI study explored the neural substrates of cognitive dissonance during dissonance ‘induction’. The significant cluster is widely distributed, covering the frontal and central part of the head. ERN is generated in the pMFC (Holroyd and Coles, 2002; Holroyd et al., 2004; Ridderinkhof et al., 2004; Debener et al., 2005) and has been associated with processing errors (Holroyd et al., 2003), monitoring of action outcomes (Luu et al., 2004), and behavioral adjustments (Gehring et al., 2011). The ERN′s time course and topographical map are illustrated in Figure 3A. – What is neurology? SIGNIFICANCE STATEMENT Contrary to traditional decision theory, behavioral studies repeatedly demonstrate that our preferences are modulated by the mere act of choosing. Such neuronal dynamics were shown to reflect a delicate balance between excitation and inhibition (Poil et al., 2012), thus relating to the performance in a given experimental task (Palva et al., 2013; Smit et al., 2013; Samek et al., 2016). Our psychology articles cover research in mental health, psychiatry, depression, psychology, schizophrenia, autism spectrum, happiness, stress and more. We also compared response-locked ERPs in incorrect responses to response-locked ERPs in correct responses in the Eriksen Flanker task. Genetics articles related to neuroscience research will be listed here. Importantly, LRTCs indicate the presence of temporal autocorrelations within the measured cortical area (i.e., LRTCs describe the temporal development of the neuronal activity). Science articles can cover neuroscience, psychology, AI, robotics, neurology, brain cancer, mental health, machine learning, autism, Parkinson's, Alzheimer's, brain research, depression and other topics related to cognitive sciences. The results of the study have been published in the paper ‘Open Access Neural Mechanisms of Cognitive Dissonance (Revised): an EEG Study’ in The Journal of Neuroscience. A choice between two similarly valued alternatives creates psychological tension (cognitive dissonance) that is reduced by a postdecisional reevaluation of the alternatives. 2). It’s an uncomfortable state of mind when someone has contradictory values, attitudes, or perspectives about the same thing. Cognitive dissonance theory argues tha… Further technical details on the application of DFA for the estimation of LRTCs in EEG/MEG signals can be found in Hardstone et al. The present study also does not allow for the investigation of the relationship between the amplitude of electrophysiological signatures of difficult choices and the level of postdecisional adjustments on a trial-by-trail basis. Importantly, the efficiency of the control conditions for the free-choice paradigm is still debated (Coppin et al., 2014), and further investigation is needed. Indeed, our study demonstrates that difficult decisions (high cognitive dissonance) trigger a more prominent ERN-like neural signal than easy decisions. During Preference task II, participants had to rate the same set of food items again. In the present study, we focused on the analysis of alpha oscillations in the resting state for two reasons. Post hoc analyses revealed that participants' preferences for items that were rejected during Self-difficult trials significantly decreased compared with both the rejected items in Self-easy trials (t(41) = −11.090, p < 0.001) and the selected items in Self-difficult trials (t(41) = −12,005, p < 0.001). Off-line downregulation of the right pMFC just after the Choice task induced a reduction of choice-induced preference changes (SoA). First, alpha oscillations have been shown to be involved in many cognitive operations, including memory, attention, and decision making (Klimesch, 1999, 2012; Jensen et al., 2002; Cohen et al., 2009). Second, alpha oscillations have a large signal-to-noise ratio, which facilitates extraction of their amplitude without it being strongly affected by muscle activity (Palva et al., 2005; Palva and Palva, 2007; Klimesch, 2012; Frey et al., 2015). A significance of the differences between the conditions was assessed with permutation tests based on cluster statistics (Maris and Oostenveld, 2007). Initially, we analyzed cognitive dissonance-related activity in frontocentral sites (FCz, Cz, and Fz), which often demonstrate the largest ERN. However, if there are persistent LRTCs, the exponent will lie in the 0.5–1 range. The LORETA time window's parameters matched those of the Flanker task (±11 ms around the grand-averaged maximum peak for Self-difficult trials, Self-easy trials, and difference waves). During the control Eriksen Flanker task, error responses were followed by larger frontocentral negativity-ERN compared with correct responses ∼60 ms after the button press. Importantly, even if two items are rated equally during the Preference task I, it does not necessarily mean that real preferences for these two items are the same. Similar to the Eriksen Flanker task, we applied the LORETA transform to explore the source generator of cognitive dissonance-related activity. Furthermore, the frontocentral resting-state activity predicted the individual magnitude of preference change and the strength of cognitive dissonance-related neural activity. The researchers therefore uncovered a link between the individual index of self-organization in the frontal cortices during rest and the subsequent neural and behavioural effects of cognitive dissonance. Starting in the late 1950s, people started to look at cognitive dissonance, particularly Leon Festinger and his students at Stanford, who wrote the book A Theory of Cognitive Dissonance.According to Festinger, the important factor in cognitive dissonance theory is the principle of cognitive consistency. What is Psychology? As Figure 3A shows, sources of the difference wave were localized in the occipital cortex, ventral prefrontal cortex, and the pMFC, with the greatest activity occurring within the BA6. Indeed, we found that the largest cognitive dissonance-related activity was observed in FCz. Self and dissonance in two cultures, EEG alpha and theta oscillations reflect cognitive and memory performance: a review and analysis, Alpha-band oscillations, attention, and controlled access to stored information, Do amnesics exhibit cognitive dissonance reduction? . Because strong cognitive dissonance should occur during difficult decisions (Self-difficult trials and Post-ex choice), we predicted that magnitude of the SoA should be enhanced as a function of choice difficulty. Research Articles, Behavioral/Cognitive Neural Mechanisms of Cognitive Dissonance (Revised): An EEG Study Marco Colosio , Anna Shestakova , Vadim V. Nikulin , … Eddie Harmon-Jones is professor of psychology at the University of New South Wales.He is recognized for his research on social neuroscience, cognitive dissonance, and the motivating aspects of emotions. A positive preference change indicated an increased postdecisional preference for the food item (more liking), whereas a negative preference change suggested a decreased postdecisional preference for the food item (less liking). 3B) were very similar to the frontocentral distribution of ERN in the standard Flanker task (Fig. Contrary to traditional decision theory, behavioral studies repeatedly demonstrate that our preferences are modulated by the mere act of choosing. sonality, and cognitive and affective neuroscience. Algorithmically, DFA captures fluctuations of the signal at different time scales, and the slope of the corresponding line is called a scaling exponent. For the extraction of the instantaneous amplitude, we used an analytic signal concept based on the Hilbert transform. Right, Topographical map for voltage distribution of the difference wave and LORETA solutions (scale range: 0–0.005 μA/mm2) within 36 ms time window. Figure 5B shows a topography of this correlation. Furthermore, an important role of the pMFC in cognitive dissonance and choice-induced preference changes (Izuma et al., 2010) suggests that its ongoing, spontaneous (resting state) activity may affect follow-up neural and behavioral effects of cognitive dissonance. Artificial Intelligence articles involve programming, neural engineering, artificial neural networks, artificial life, a-life, floyds, boids, emergence, machine learning, neuralbots, neuralrobotics, computational neuroscience and more involving A.I. Feel free to share this Neuroscience News. In psychology, cognitive dissonance is viewed as mental stress (discomfort) experienced by a person who simultaneously holds two or more contradictory beliefs, ideas, or values (i.e., when performing an action that contradicts one of those beliefs, ideas, or values; or when confronted with new information that contradicts one of those beliefs, ideas, and values). In this case, because we had calculations of multiple correlations, we applied permutation tests based on cluster statistics (Maris and Oostenveld, 2007). Cognitive dissonance is thought to reveal a human's internal desire for consistency. As participants passively observed a computer “selecting” food items, they could implicitly compare the selection to their own preferences for items and prepare motor responses. Although previous studies found similar activity in the late stages of the decisional process in the free-choice paradigm (Preference task II), our data favor a central role of the pMFC in cognitive dissonance detection during the decisional process (Choice task). Black lines indicate p < 0.001. To assess the effect of cognitive dissonance on behavioral preference changes, or SoA, we calculated preference change by subtracting the average rating made during Preference task II − from the average rating made during Preference task I, separately for the selected and rejected items and the four experimental conditions (Self-difficult trials, Self-easy trials, Computer choice, and Post-ex choice). As predicted, we observed a significantly larger SoA for rejected items in Self-difficult trials than for rejected items in Self-easy trials (Fig. Publication of an advertisement or other product mention in JNeurosci should not be construed as an endorsement of the manufacturer’s claims. In conclusion, our results provide strong evidence that postdecisional preference changes and performance monitoring demonstrate similar neural signatures. Importantly, as all ERPs were response-locked to the motor responses, the difference in RTs was controlled for between Self-difficult and Self-easy trials. A novel task was developed based on the results of a separate item selection study (n=125). 3A). A choice between two similarly valued alternatives creates psychological tension (cognitive dissonance) that is reduced by a post-decisional reevaluation of the alternatives. Thus, we explored whether difficult choice-induced preference changes can be driven by a neural mechanism similar to the general mechanism of performance monitoring and behavioral adjustment. According to the action-based model of cognitive dissonance, activity in the posterior medial frontal cortex (pMFC) underlies detection of cognitive conflicts and the reduction of cognitive dissonance (Carter et al., 1998; Amodio et al., 2004; Izuma et al., 2010). In the control study, we recorded the standard ERN during the Flanker task (Falkenstein et al., 1995; Holroyd and Coles, 2002; Gehring et al., 2011) to test the spatial and temporal correspondence of the ERN-like potential generated during the free-choice paradigm with standard ERN. The cognitive processes during Computer trials should be further investigated in future studies. Here, we used LORETA to identify the neural generator of the ERN and cognitive dissonance-related ERPs recorded in the Eriksen Flanker task and the free-choice paradigm. [/cbtab][/cbtabs], Neural mechanisms of cognitive dissonance (revised): An EEG study. Each item appeared at the center of the screen for 3 s. During the Choice task, two food items were presented on the screen at the same time (up to 210 pairs altogether). Thus, the preference change found in the present study could be inflated due to this aspect of the experimental design. If participants responded too late (slower than 800 ms), a message, “you are too late,” prompted them to respond faster. Subjects were instructed to relax and not move during the recordings. This correlation indicates that the more pronounced frontal LRTC at the rest predicts a stronger decrease in preference for the rejected items in Self-difficult trials later on. You can cancel your subscription any time. Researchers Predict Cognitive Dissonance By Looking At Brain Activity. Researchers from the HSE Centre for Cognition & Decision Making carried out an experiment aimed at investigating what happens in the human brain when a person experiences cognitive dissonance. This study also indicated that decisions associated with higher levels of cognitive dissonance elicited a fast frontal electrophysiological signal that peaked ~60 ms after the difficult decision. EEG signals were referenced to arithmetically link mastoids. Furthermore, amplitudes of ERN-like potentials predicted individual differences in postdecisional preference changes: A larger ERN-like potential was associated with larger preference changes. However, all the remaining comparisons showed a significant effect (all p < 0.001), except for the SoA between accepted and rejected items in Computer trials (t(41) = −1.402, p = 0.168). Error bars indicate SEM. Difficult choices generate psychological (cognitive) dissonance, which is reduced by the postdecisional devaluation of unchosen options. In Preference task II, participants rated the same food items again. Black lines below the histogram indicate statistically significant postdecisional preference change between Preference task I and Preference task II for rejected items. NeuroscienceNews, 17 May 2017. Importantly, LRTCs are indeed most pronounced when excitation and inhibition are balanced (Poil et al., 2012). What is neuroscience? The existence of ERN has been proven in a large set of experimental designs and paradigms, such as the Stroop task and Flanker task. Figure 3B shows the grand-averaged ERPs and the difference wave at the frontocentral midline electrode FCz, as well as a topographical map of the voltage distribution for the difference wave (Self-difficult − Self-easy trials). Thus, neurocomputational mechanisms of choice- and feedback-induced preference changes may be more strongly intertwined than previously thought. The amplitude of the alpha oscillations recorded during rest did not correlate with the evoked responses (Fig. Qizilbash, M. (1994).Corruption, Temptation and Guilt: Moral Character in Economic Theory. Importantly, our ERP study suggests that an earlier neural process might also be involved in the subsequent preference changes for rejected items. Neuroscience can involve research from many branches of science including those involving neurology, brain science, neurobiology, psychology, computer science, artificial intelligence, statistics, prosthetics, neuroimaging, engineering, medicine, physics, mathematics, pharmacology, electrophysiology, biology, robotics and technology. Recent studies have demonstrated that a large variety of complex processes, including forest fires, earthquakes, financial markets, heartbeats, and human coordination exhibit self-organization (or ‘critical states’). This activity shares similar spatial and temporal features as error-related negativity (ERN)—the electrophysiological correlate of performance monitoring. In this new and fully-updated edition, editor Eddie Harmon-Jones brings the study of cognitive dissonance into the 21st century. A two-way (factor trial type: Self-difficult, Post-ex choice; factor choice: selected, rejected) repeated-measures within-subject ANOVA showed a significant main effect of choice (F(1,41) = 202.92, p < 0.001) but not trial type (F(1,41) < 1, p = 0.770). Unlike Preference task I, an additional text indicated either the participant's or the computer's decision during the Choice task (e.g., “you chose it,” “you rejected it,” or “computer chose it,” “computer rejected it”). The data were inspected for artifacts (amplitudes exceeding ±100 μV), and <10% of all trials in each condition and with each participant were rejected. Sign up to receive our recent neuroscience headlines and summaries sent to your email once a day, totally free. Moreover, a recent transcranial magnetic stimulation study demonstrated a causal role for the pMFC in choice-induced preference change: Repetitive transcranial magnetic stimulation of the pMFC following the choice stage significantly reduced choice-induced preference changes compared with control stimulations over a different brain region (Izuma et al., 2015). Neural Mechanisms of Cognitive Dissonance (Revised): An EEG Study. Thus, 42 and 24 subjects participated in the analysis of the free-choice paradigm and Eriksen Flanker task, respectively. Therefore, Chen and Risen (2010) designed a control condition in which participants made a choice after they had made two preference ratings (rate-rate-choose condition, Post-ex Choice task).
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