The authors have declared that no competing interests exist.
Conceived and designed the experiments: RY. Performed the experiments: YH. Analyzed the data: YH RY. Contributed reagents/materials/analysis tools: YH. Wrote the paper: RY YH.
People often evaluate money based on its face value and overlook its real purchasing power, known as the money illusion. For example, the same 100 Chinese Yuan can buy many more goods in Tibet than in Beijing, but such difference in buying power is usually underestimated. Using event related potential combined with a gambling task, we sought to investigate the encoding of both the real value and the face value of money in the human brain. We found that the self-reported pleasantness of outcomes was modulated by both values. The feedback related negativity (FRN), which peaks around 250ms after feedback and is believed to be generated in the anterior cingulate cortex (ACC), was only modulated by the true value but not the face value of money. We conclude that the real value of money is rapidly encoded in the human brain even when participants exhibit the money illusion at the behavioral level.
Money is a commodity accepted by general consent as a medium of economic exchange. Its real value lies only on its buying power in economic transactions, which is the number of goods/services that can be purchased with a unit of currency. The face value of money may still remain the same when its real value changes dramatically. For example, 100 dollars in 1912 may worth much more than 100 dollars in 2012. If you had taken one dollar to a store in 1912, you would have been able to buy a greater number of items than you would in 2012, indicating that you would have had a greater purchasing power in 1912. Similarly, the same 100 Chinese Yuan can buy much more goods in Tibet (a city with low price level) than in Beijing (a city with high price level), indicating that the purchasing power in Tibet is higher than that in Beijing. However, people usually evaluate money based on its face value and ignore its real purchasing power. People are generally not sensitive to variations in inflation and prices and treat 100 dollars in different situations similarly. The way human decisions are frequently affected by the nominal rather than the real value of money is referred as the money illusion
However, the presence of money illusion is only inferred indirectly from its effects on behavior. Much of the evidence that has been put forward in favor of money illusion can also be explained by alternative rational theories
Although this study demonstrates that certain brain regions encode nominal representation rather than the real value of money, it is still unclear whether the true value of money is encoded or not and how. It is unknown whether the true value of money is encoded in certain brain regions but such signals are overridden by the face value signals or the true value has never been registered in the brain?
Here, we use event related potential combined with a gambling task to investigate the encoding of both real value and the face value of money in the human brain. There were two conditions: In the expensive price condition incomes and catalog prices were higher than in the second, cheap price condition. Thus, the face value was identical in the expensive and the cheap price conditions but real purchasing power differed. For low magnitude in cheap condition and high magnitude in expensive condition, the true value was identical but the face value differed. We examined the feedback-related negativity (FRN) and the P300, two even-related potential (ERP) components implicated in reward processing
Nineteen healthy, right-handed participants (9 male; mean age ± SD, 21.21±1.75 years) participated in return for payment. All the participants were right- handed, and had normal or corrected-to-normal vision, and were screened for neurological or psychiatric disorders. The study was approved by the Academic Committee of the School of Psychology at South China Normal University. All participants gave written, informed consent. They were informed of their right to discontinue participation at any time.
1120 landscape images were downloaded online, carefully divided into 560 pairs. In a pilot study, for each image pair, ten individuals were asked to choose one image, which they think most people would choose. To minimize the predictability of one’ choice in each image pair, we selected image pairs in which one particular image was selected by half of the ten individuals. These image pairs were used in the experiment without replacement.
At the beginning of each trial, participants were first presented with the price condition for that trial: “cheap price” or “expensive price” for 2 seconds. To this end participants did not earn their income in cash but had to spend it on a large but fixed menu of items. We created 2 catalogs with 40 items including books, CDs, DVDs, sports articles, cosmetics, and consumer electronics. The catalogs were identical with the exception that all prices were 50% higher in expensive price condition than in cheap price condition. Prices in the catalog with “cheap price” ranged from ¥1.4 to ¥24.6.
Then two photos of landscapes were presented and participants were required to select one of them by pressing the left or right keys in keyboard within 2 seconds. Participants were told that one photo of landscape was associated with a win and the other photo of landscape was associated with a loss. They had to guess which one was associated with a win. The selected photo was highlighted. Then the amount of winning or losing (from ¥2.8 to ¥49.2) associated with the chosen card was shown for 1 second. Participants were informed about the range of winning or losing magnitude (from ¥2.8 to ¥49.2). Unknown to the participants, outcomes were predetermined and fully randomized across conditions. The next trial began 1 second after the offset of the feedback (
At the beginning of each trial, the cheap price or the expensive price context information was shown. Then participants performed a simple gambling game in which they win or lose money on the basis of unpredictable outcomes. Participants chose one gambling card from the two and received winning or losing feedback.
Before participants began the task, they read the instructions for the experiment and were given the opportunity to familiarize themselves with the 2 catalogs. Then they were asked to answer several control questions to make sure that they had understood the difference between the 2 catalogs; e.g., participants were asked how much an item with price
After the electroencephalogram (EEG) session, participants were required to indicate their feelings (pleasantness and surprise) about the eight types of outcomes (i.e. losing/winning ¥10/¥20 in cheap/expensive price condition) they experienced in the experiment on a 10-point Likert scale. After completion of the experiment, five trials in each catalog (5 trials in expensive condition and 5 trials in cheap condition) were randomly selected for actual payment. The accumulated total winnings were used for participants to buy things only in the corresponding catalog. For example, the accumulated total winnings of five trials in cheap condition were used for participants to buy things in the low price catalogue, whereas the accumulated total winnings of five trials in expensive condition were used to buy things in the high price catalogue. Participants did not earn their income in cash but had to spend it to buy things. Before the experiment, participants were clearly informed of these rules and were familiar with the two catalogues. They were not endowed with initial money and if the accumulated total winnings of five trials were negative or smaller than the cheapest price in the corresponding catalog, they cannot buy any item in that catalog. Thus, losing money in our experiment meant losing the opportunity to buy items in the respective catalog rather than losing out of pocket money.
Standard ERP recording and analysis were applied. EEGs were recorded from 64 scalp sites using Ag/AgCl electrodes embedded in an elastic cap (NeuroScan Inc., USA) according to the international 10–20 system, with the reference to the right mastoid. Eye blinks were recorded from electrodes located above and below the left eye. The horizontal electro-oculogram (EOG) was recorded from electrodes placed 1.5 cm lateral to the left and right external canthi. The EEGs were re-referenced ofine to the linked mastoids. All electrode impedances were maintained below 5 kΩ. The EEG and EOG were amplified using a 0.05–70 Hz bandpass and continuously sampled at 500 Hz/channel for off-line analysis.
Ocular artifacts were corrected with an eye-movement correction algorithm
According to visual inspection of ERP waveforms, the FRN for both win and loss trials were measured as the mean amplitudes in the time window of 200 to 350 ms post-onset of the feedback. The peak value of the P300 was detected as the most positive value in the 300 to 500 ms post-stimulus time window at electrode Pz. We focused on the FRN responses on the anterior frontal midline electrodes (Fz) and the P300 responses on the posterior midline electrodes (Pz), since the FRN and P300 effects were the largest on these electrodes, respectively.
Post experiment ratings for 8 conditions were plotted in
The self-reporting satisfaction scores (mean ± SE) for the eight experimental conditions were shown in (A). The difference in satisfaction between losses (in red) and wins (in blue) was larger when the price was cheap versus expensive (B). The difference in satisfaction between losses and wins was larger for large magnitude in expensive context than for small magnitude in cheap context, showing money illusion (C). The self-reported surprise scores (mean ± SE) for the eight conditions were shown in (D). The experienced surprise was not modulated by the true value of money (E) or the face value of money (F). S: small magnitude; L: large magnitude; All: across small and large magnitude. * p<0.05, ** p<0.001.
To test whether there was a money illusion effect on satisfaction, we compared winning or losing small magnitude in cheap price context with winning or losing the large magnitude in expensive price context (
The behavioral money illusion effect for 19 participants (numerically ordered). The y axis represents the differences in satisfaction (difference between win and loss for large magnitude in expensive context - difference between win and loss for small magnitude in cheap context).
For the self-reported surprise in response to outcomes (
For the FRN amplitude (
(A) Grand-average waveforms at channel Fz and Pz for conditions that differed in real value but were identical in face value of money. (B) Grand-average waveforms at channel Fz and Pz for conditions that differed in face value but were identical in real value of money. Cheap_Loss: losing in cheap price context across magnitude; Cheap_Win: winning in cheap price context across magnitude; Expensive_Loss: losing in expensive price context across magnitude; Expensive_Win: winning in expensive context across magnitude; Cheap_Small_Loss: losing the small magnitude in cheap condition; Cheap_Small_Win: winning the small magnitude in cheap condition; Expensive_Small_Loss: losing the large magnitude in expensive condition; Expensive_Small_Win: winning the large magnitude in expensive condition.
The FRN amplitudes (mean ± SE, in µV) for the eight experimental conditions were shown in (A). The difference in FRN amplitude between losses (in red) and wins (in blue) was larger when the price was cheap versus expensive, suggesting that the FRN is sensitive to the true value of money (B). The FRN effect (losses minus wins) was similar between large magnitude in expensive context and small magnitude in cheap context (C). The P300 amplitudes (mean ± SE, in µV) for the eight conditions were shown in (D). No effect of true value (E) and face value (F) on P300 was found. S: small magnitude; L: large magnitude; All: across small and large magnitude. * p<0.005.
To test whether the FRN shows money illusion effect, we first compared winning or losing small magnitude in cheap price context with winning or losing the large magnitude in expensive price context (
(A) Difference waveform (loss-win) and maps of cheap condition. (B) Difference waveform (loss-win) and topographical maps in expensive condition. (C) Difference waveform (loss-win) and topographical maps in small magnitude and cheap condition. (D) Difference waveform (loss-win) and topographical maps in large magnitude and expensive condition.
Similar analysis was also conducted for the P300 (
Our study demonstrates behavioral money illusion in laboratory using self-reported satisfaction ratings. Participants felt more satisfied for winning large magnitude reward in expensive context than for winning small magnitude reward in cheap context, although the two types of reward have an identical real value. Similarly, they felt more dissatisfied for losing large reward in expensive context than for losing small magnitude reward in cheap context. At the neural level, we found that the FRN, which was believed to be generated in the ACC, was modulated by the true value but not the face value. The P300 was not modulated by either the face value or the true value.
An intriguing question about money illusion is whether the true value has ever been computed in the brain or not. Our findings suggest that the true value is encoded in the ACC (indexed by the FRN) at an early stage. The ACC is anatomically well positioned to integrate reward information given its cortico-cortico, sensorimotor, and subcortical connections
Our FRN results, however, seems at odds with the previous findings that the magnitude of reward does not affect the FRN
Previous research has demonstrated that various aspect of reward values (e.g. action values, relative values, expected values, and experienced values) are represented in different brain areas. Neuroimaging studies have already identified a number of regions that are sensitive to reward magnitude, including the orbitofrontal cortex, insula, and ventral striatum
Previous studies have shown that P300 is implicated in a large number of cognitive and affective processes and is traditionally associated with allocation of mental resources. It is often elicited using a simple discrimination task called “oddball paradigm”, in which participants are required to respond to infrequent stimuli presented among a series of frequent stimuli
Although all outcomes were predetermined and randomized, it is possible that participants may still actively try to learn associations among cues (some arbitrary features), responses (left/right) and outcomes (win/loss). However, post-experiment debriefing did not identify any performance strategies deliberately used (although unconscious strategies cannot be ruled out) and it is unlikely that the learning would differ between expensive and cheap conditions. Nevertheless, the subjective values of the same outcomes may be modulated by learning (e.g. predictions and prediction errors) and may fluctuate across trials. Future studies may use computational models to quantify the subjective utility of outcomes in each trial more precisely.
In the present study, we used the method of EEG which carries its own advantages to study the value computation. Several previous studies have demonstrated that several early ERP components (e.g. FRN and P300) are modulated by the valence, magnitude and expectancy of reward feedback
In conclusion, we show that money illusion does exist and can be demonstrated using simple self-reported ratings. Even when robust money illusion occurs, at the neural level, the FRN is modulated by the true value of money, suggesting that the human brain rapidly computes the true value but may ignore such signal subsequently.