Human emotion and its electrophysiological correlates are still poorly understood. The present study examined whether the valence of perceived emotions would differentially influence EEG power spectra and heart rate (HR). Pleasant and unpleasant emotions were induced by consonant and dissonant music. Unpleasant (compared to pleasant) music evoked a significant decrease of HR, replicating the pattern of HR responses previously described for the processing of emotional pictures, sounds, and films. In the EEG, pleasant (contrasted to unpleasant) music was associated with an increase of frontal midline (Fm) theta power. This effect is taken to reflect emotional processing in close interaction with attentional functions. These findings show that Fm theta is modulated by emotion more strongly than previously believed. Descriptors: Emotion, Music, Dissonance, EEG, Fm theta, Heart rate During the past 15 years, numerous imaging studies have provided considerable insights into the neural basis of pleasant and unpleasant emotions (e.g., Dalgleish, 2004; Davidson & Irwin, 1999; Phan, Wager, Taylor, & Liberzon, 2002). On the other hand, electrophysiological correlates of pleasant emotions remain

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The eye may be window to the soul, but neuroscientists aim to get inside and measure the interior directly. There’s also talk about moving some walls. Congress christened the 1990s “the decade of the brain, ” and this was apt from the vantage point of the early 21st Century. Great strides were made in both basic and clinical neuroscience. What the current decade may, in retrospect, be remembered for is the growth of neuroscience beyond those two categories, “basic ” and “clinical, ” into a host of new applications. From the measurement of mental processes with functional neuroimaging to their manipulation with ever more selective drugs, the new capabilities of neuroscience raise unprecedented ethical and social issues. These issues must be identified and addressed if society is to benefit from the neuroscience revolution now in progress. Like the field of genetics, cognitive neuroscience raises questions about the biological foundations of

Our understanding of political phenomena, including political attitudes and sophistication, can be enriched by incorporating the theories and tools of cognitive neuroscience— in particular, the cognitive neuroscience of nonconscious habitual cognition (akin to bicycle riding). From this perspective, different types of informational “building blocks” can be construed from which different types of political attitudes may arise. A reflectionreflexion model is presented that describes how these blocks combine to produce a given political attitude as a function of goals, primes, expertise, and inherent conflict in considerations relevant to the attitude. The ways in which neuroimaging methods can be used to test hypotheses of political cognition are reviewed. KEY WORDS: social cognitive neuroscience, automaticity, habit, political sophistication Scholars since Plato and Aristotle have asked themselves many questions about the intriguingly political nature of the human mind. It is unlikely, however, that many have asked themselves whether political thinking is like riding a bicycle. This isn’t altogether surprising, of course, given that casting a vote and pedaling down the road seem like very different behaviors. Beneath this surface of dissimilarity, however, political thinking and bike riding may frequently depend on flexing a common set of mental “muscles ” that support the formation and expression of habits across a variety of domains (Lieberman, 2000). Political thinking and bicycle riding may seem to be very dissimilar behaviors. But in some circumstances, they may both depend on a common set of mental “muscles ” that support the formation and expression of habits across a variety of domains

Despite the rapidly growing number of meta-analyses in functional neuroimaging, the field still lacks formal mathematical tools for the quantitative and qualitative evaluation of meta-analytic data. We propose to use replicator dynamics in the meta-analysis of functional imaging data in order to address an important aspect of neuroimaging research, the search for functional networks of cortical areas that underlie a specific cognitive task. The replicator process requires as input only a list of activation locations, and it results in a network of locations that jointly show significant activation in the majority of the studies included in the meta-analysis. These locations are likely to play a critical role in solving the investigated cognitive task. Our method was applied to a meta-analysis of the Stroop interference task using data provided by the publicly accessible database BrainMap DBJ.

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Investors systematically deviate from rationality when making financial decisions, yet the mechanisms responsible for these deviations have not been identified. Using event-related fMRI, we examined whether anticipatory neural activity would predict optimal and suboptimal choices in a financial decision-making task. We characterized two types of deviations from the optimal investment strategy of a rational risk-neutral agent as risk-seeking mistakes and risk-aversion mistakes. Nucleus accumbens activation preceded risky choices as well as risk-seeking mistakes, while anterior insula activation preceded riskless choices as well as risk-aversion mistakes. These findings suggest that distinct neural circuits linked to anticipatory affect promote different types of financial choices and indicate that excessive activation of these circuits may lead to investing mistakes. Thus, consideration of anticipatory neural mechanisms may add predictive power to the rational actor model of economic decision making.

Promises are one of the oldest human-specific psychological mechanisms fostering cooperation and trust. Here, we study the neural underpinnings of promise keeping and promise breaking. Subjects first make a promise decision (promise stage), then they anticipate whether the promise affects the interaction partner’s decision (anticipation stage) and are subsequently free to keep or break the promise (decision stage). Findings revealed that the breaking of the promise is associated with increased activation in the DLPFC, ACC, and amygdala, suggesting that the dishonest act involves an emotional conflict due to the suppression of the honest response. Moreover, the breach of the promise can be predicted by a perfidious brain activity pattern (anterior insula, ACC, inferior frontal gyrus) during the promise and anticipation stage, indicating that brain measurements may reveal malevolent intentions before dishonest or deceitful acts are actually committed.

voxel intensity and cluster extent with permutation

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