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Humans sometimes share with others whom they may never meet or know, in violation of the dictates of pure self-interest. Research has not established which neuropsychological mechanisms support lending decisions, nor whether their influence extends to markets involving significant financial incentives. In two studies, we found that neural affective mechanisms influence the success of requests for microloans. In a large Internet database of microloan requests (N = 13,500), we found that positive affective features of photographs promoted the success of those requests. We then established that neural activity (i.e., in the nucleus accumbens) and self-reported positive arousal in a neuroimaging sample (N = 28) predicted the success of loan requests on the Internet, above and beyond the effects of the neuroimaging sample's own choices (i.e., to lend or not). These findings suggest that elicitation of positive arousal can promote the success of loan requests, both in the laboratory and on the Internet. They also highlight affective neuroscience's potential to probe neuropsychological mechanisms that drive microlending, enhance the effectiveness of loan requests, and forecast market-level behavior.

Advances in brain-imaging design and analysis have allowed investigators to use neural activity to predict individual choice, while emerging Internet markets have opened up new opportunities for forecasting aggregate choice. Here, we review emerging research that bridges these levels of analysis by attempting to use group neural activity to forecast aggregate choice. A survey of initial findings suggests that components of group neural activity might forecast aggregate choice, in some cases even beyond traditional behavioral measures. In addition to demonstrating the plausibility of neuroforecasting, these findings raise the possibility that not all neural processes that predict individual choice forecast aggregate choice to the same degree. We propose that although integrative choice components may confer more consistency within individuals, affective choice components may generalize more broadly across individuals to forecast aggregate choice.

In temporal discounting, individuals often prefer smaller immediate rewards to larger delayed rewards, implying a trade off between the magnitude and delay of future rewards. While recent functional magnetic resonance imaging (fMRI) investigations of temporal discounting have generated conflicting findings, no studies have focused on whether distinct neural substrates respond to the magnitude and delay of future rewards. Combining a novel, temporally distributed discounting task with event-related fMRI, we found that while nucleus accumbens (NAcc), mesial prefrontal cortical (MPFC), and posterior cingulate cortical (PCC) activation positively correlated with future reward magnitude, dorsolateral prefrontal cortical (DLPFC) and posterior parietal cortical (PPC) activation negatively correlated with future reward delay. Further, more impulsive individuals showed diminished NAcc activation to the magnitude of future rewards and greater deactivations to delays of future rewards in the MPFC, DLPFC, and PPC. These findings suggest that while mesolimbic dopamine projection regions show greater sensitivity to the magnitude of future rewards, lateral cortical regions show greater (negative) sensitivity to the delay of future rewards, potentially reconciling different neural accounts of temporal discounting.

•Researchers have raised concerns about decreasing replicability of FMRI task-related findings but have not examined the potential impact of concurrent changes in scanning protocols.•Meta-analysis of studies using the monetary incentive delay task suggests that multi-band versus single-band scanning decreases effect sizes of NAcc responses during reward anticipation by over a half.•Direct within-subjects comparison of single-band versus multi-band data controlling for scanner, subject, and task indicates that multi-band scanning induces temporal noise in the center of the brain, which compromises detection of reward-related responses.•Multi-band FMRI scanning may compromise detection of mesolimbic activity during tasks and rest. Recent innovations in Functional Magnetic Resonance Imaging (FMRI) have sped data collection by enabling simultaneous scans of neural activity in multiple brain locations, but have these innovations come at a cost? In a meta-analysis and preregistered direct comparison of original data, we examined whether acquiring FMRI data with multi-band versus single-band scanning protocols might compromise detection of mesolimbic activity during reward processing. Meta-analytic results (n = 44 studies; cumulative n = 5005 subjects) indicated that relative to single-band scans, multi-band scans showed significantly decreased effect sizes for reward anticipation in the Nucleus Accumbens (NAcc) by more than half. Direct within-subject comparison of single-band versus multi-band scanning data (multi-band factors = 4 and 8; n = 12 subjects) acquired during repeated administration of the Monetary Incentive Delay task indicated that reductions in temporal signal-to-noise ratio could account for compromised detection of task-related responses in mesolimbic regions (i.e., the NAcc). Together, these findings imply that researchers should opt for single-band over multi-band scanning protocols when probing mesolimbic responses with FMRI. The findings also have implications for inferring mesolimbic activity during related tasks and rest, for summarizing historical results, and for using neuroimaging data to track individual differences in reward-related brain activity.

'Anticipatory affect' refers to emotional states that people experience while anticipating significant outcomes. Historically, technical limitations have made it difficult to determine whether anticipatory affect influences subsequent choice. Recent advances in the spatio-temporal resolution of functional magnetic resonance imaging, however, now allow researchers to visualize changes in neural activity seconds before choice occurs. We review evidence that activation in specific brain circuits changes during anticipation of monetary incentives, that this activation correlates with affective experience and that activity in these circuits may influence subsequent choice. Specifically, an activation likelihood estimate meta-analysis of cued response studies indicates that nucleus accumbens (NAcc) activation increases during gain anticipation relative to loss anticipation, while anterior insula activation increases during both loss and gain anticipation. Additionally, anticipatory NAcc activation correlates with self-reported positive arousal, whereas anterior insula activation correlates with both self-reported negative and positive arousal. Finally, NAcc activation precedes the purchase of desirable products and choice of high-risk gambles, whereas anterior insula activation precedes the rejection of overpriced products and choice of low-risk gambles. Together, these findings support a neurally plausible framework for understanding how anticipatory affect can influence choice.

Neuroeconomics research shows that brain areas that generate emotional states also process information about risk, rewards, and punishments, suggesting that emotions influence financial decisions in a predictable and parsimonious way. We find that positive emotional states such as excitement induce people to take risks and to be confident in their ability to evaluate investment options, while negative emotions such as anxiety have the opposite effects. Beliefs are updated so as to maintain a positive emotional state by ignoring information that contradicts individuals’ prior choices. Marketplace features or outcomes of past choices may change emotions and thus influence future financial decisions.

Which brain regions are causally involved in reward-related behavior? Ferenczi et al. combined focal, cell type-specific, optogenetic manipulations with brain imaging, behavioral testing, and in vivo electrophysiology (see the Perspective by Robbins). Stimulation of midbrain dopamine neurons increased activity in a brain region called the striatum and was correlated with reward-seeking across individual animals. However, elevated excitability of an area called the medial prefrontal cortex reduced both striatal responses to the stimulation of dopamine neurons and the behavioral drive to seek the stimulation of dopamine neurons. Finally, modulating the excitability of medial prefrontal cortex pyramidal neurons drove changes in neural circuit synchrony, as well as corresponding anhedonic behavior. These observations resemble imaging and clinical phenotypes observed in human depression, addiction, and schizophrenia. Science , this issue p. 10.1126/science.aac9698 ; see also p. 10.1126/science.aad9698 Optogenetic and brain imaging approaches reveal a causal brainwide dynamical mechanism for the hedonic-anhedonic transition. [Also see Perspective by Robbins ] Motivation for reward drives adaptive behaviors, whereas impairment of reward perception and experience (anhedonia) can contribute to psychiatric diseases, including depression and schizophrenia. We sought to test the hypothesis that the medial prefrontal cortex (mPFC) controls interactions among specific subcortical regions that govern hedonic responses. By using optogenetic functional magnetic resonance imaging to locally manipulate but globally visualize neural activity in rats, we found that dopamine neuron stimulation drives striatal activity, whereas locally increased mPFC excitability reduces this striatal response and inhibits the behavioral drive for dopaminergic stimulation. This chronic mPFC overactivity also stably suppresses natural reward-motivated behaviors and induces specific new brainwide functional interactions, which predict the degree of anhedonia in individuals. These findings describe a mechanism by which mPFC modulates expression of reward-seeking behavior, by regulating the dynamical interactions between specific distant subcortical regions.

Price is a key factor in most purchases, but it can be presented at different stages of decision making. The authors examine the sequencedependent effects of price and product information on the decisionmaking process at both neural and behavioral levels. During functional magnetic resonance imaging, the price of a product was shown to participants either before or after the product itself was presented. Early exposure to price, or \"price primacy,\" altered the process of valuation, as observed in altered patterns of activity in the medial prefrontal cortex immediately before making a purchase decision. Specifically, whereas viewing products first resulted in evaluations strongly related to products' attractiveness or desirability, viewing prices first appeared to promote overall evaluations related to products' monetary worth. Consistent with this framework, the authors show that price primacy can increase purchase of bargain-priced products when their worth is easily recognized. Together, these results suggest that price primacy highlights considerations of product worth and can thereby influence purchasing.

The growth of the internet has spawned new “attention markets,” in which people devote increasing amounts of time to consuming online content, but the neurobehavioral mechanisms that drive engagement in these markets have yet to be elucidated. We used functional MRI (FMRI) to examine whether individuals’ neural responses to videos could predict their choices to start and stop watching videos as well as whether group brain activity could forecast aggregate video view frequency and duration out of sample on the internet (i.e., on youtube.com). Brain activity during video onset predicted individual choice in several regions (i.e., increased activity in the nucleus accumbens [NAcc] and medial prefrontal cortex [MPFC] as well as decreased activity in the anterior insula [AIns]). Group activity during video onset in only a subset of these regions, however, forecasted both aggregate view frequency and duration (i.e., increased NAcc and decreased AIns)—and did so above and beyond conventional measures. These findings extend neuroforecasting theory and tools by revealing that activity in brain regions implicated in anticipatory affect at the onset of video viewing (but not initial choice) can forecast time allocation out of sample in an internet attention market.

Neuroimaging methods with enhanced spatial resolution such as functional magnetic resonance imaging (FMRI) suggest that the subcortical striatum plays a critical role in human reward processing. Analysis of FMRI data requires several preprocessing steps, some of which entail tradeoffs. For instance, while spatial smoothing can enhance statistical power, it may also bias localization towards regions that contain more gray than white matter. In a meta-analysis and reanalysis of an existing dataset, we sought to determine whether spatial smoothing could systematically bias the spatial localization of foci related to reward anticipation in the nucleus accumbens (NAcc). An activation likelihood estimate (ALE) meta-analysis revealed that peak ventral striatal ALE foci for studies that used smaller spatial smoothing kernels (i.e. <6mm FWHM) were more anterior than those identified for studies that used larger kernels (i.e. >7mm FWHM). Additionally, subtraction analysis of findings for studies that used smaller versus larger smoothing kernels revealed a significant cluster of differential activity in the left relatively anterior NAcc (Talairach coordinates: −10, 9, −1). A second meta-analysis revealed that larger smoothing kernels were correlated with more posterior localizations of NAcc activation foci (p<0.015), but revealed no significant associations with other potentially relevant parameters (including voxel volume, magnet strength, and publication date). Finally, repeated analysis of a representative dataset processed at different smoothing kernels (i.e., 0–12mm) also indicated that smoothing systematically yielded more posterior activation foci in the NAcc (p<0.005). Taken together, these findings indicate that spatial smoothing can systematically bias the spatial localization of striatal activity. These findings have implications both for historical interpretation of past findings related to reward processing and for the analysis of future studies. ► Localization of striatal FMRI activity is systematically biased by spatial smoothing. ► Two meta-analytic techniques and reprocessing of a dataset support this claim. ► These findings have implications for interpreting reward processing studies. ► These findings also have implications for conducting future studies.