The Cognition of Investment

The Cognition of Investment

Brian M. Sweis’ article “Sensitivity to ‘sunk costs’ in mice, rats, and humans” intrigues the idea that certain cognitive processes that were previously assumed to be unique to humans are present in a variety of higher-intelligence species. Although this statement is true for a variety of cognitive abilities, the neurological phenomenon of “sunk cost” is particularly surprising due to its modern correlation to economics. The dictionary definition of “sunk cost” is the “traditional economic theory suggests that decisions should be based on valuations of future expectations that ignore spent resources that cannot be recovered.” This has been denoted in humans as an adaptation that evolved around the necessity of planning for the future, with special consideration for the energy given towards progress. Despite this, when considering the predicament logically, past results do not dictate future returns, so a present choice of whether to continue to invest time and energy in something should be determined from the circumstances of a given moment, not the amount of resources previously invested. Despite the typical correlation of “sunk cost” to humans in financial terms, Brian M. Sweis’ study delves into the fact that other animals, such as mice and rats, are also capable of such cognitive decisions. 

Similar to the research on the ability of animals to understand and utilize investing, the article “Cuttlefish Delay Gratification, a Sign of Smarts” published on The Scientist by Asher Jones describes how Alex Schnell observed and studied the investment responses of a cuttlefish. The article begins by describing a peculiar pattern observed in a cuttlefish in a lab where it would respond negatively in the morning yet be more open for interaction at night. With interest in the observation of “episodic-like memory” seen in the cuttlefish, Dr. Shnell went on to conduct an experiment to see if there was any response to investment. Typically known as the “marshmallow test” (a test in which a child is offered one marshmallow, but is told that if they can wait 15 minutes, they can have another), a similar scenario is presented to the cuttlefish where it is offered its second favorite food immediately or if it can wait a given amount of time, it is offered its favorite food. Interestingly enough, the cuttlefish were able to withstand anywhere from 50 to 130 seconds in order to receive their preferred food. During this period, the option of receiving the immediate reward was always available, which the cuttlefish would settle with once a certain threshold of invested time was reached. 

I found it particularly interesting that in the newfound study, another observation was made regarding the cuttlefish waiting for their reward. Due to the difficulty of temptation present in the study with the immediate reward being available, it was observed that the cuttlefish had a tendency to turn away from the reward. This is presumed to be due to the cuttlefish avoiding the temptation of the immediate reward in order to focus on the task at hand. This has also been observed in dogs, chimpanzees, and children, who will decide to find distractions such as playing with toys in order to pass time for the reward. The significance of this finding, and its respective correlation to Sweis’ findings is that the ability to understand investments is not a unique trait to humans, but rather a cognitive perception that is present in a variety of animals. The ability to perceive a correlation between investment and reward is an evolutionary trait that allows for greater future outcome, and has ultimately resulted in the success of higher-intelligence animals.

References:

Jones, Asher. “Cuttlefish Delay Gratification, a Sign of Smarts.” The Scientist Magazine®, www.the-scientist.com/news-opinion/cuttlefish-delay-gratification-a-sign-of-smarts-68516.

Sweis, Brian M., et al. “Sensitivity to ‘Sunk Costs’ in Mice, Rats, and Humans.” Science, American Association for the Advancement of Science, 13 July 2018, science.sciencemag.org/content/361/6398/178.full.

How Crossword Puzzles and Visual Cues are Linked to Short-Term Memory Capacity

 

How Crossword Puzzles and Visual Cues are Linked to Short-Term Memory Capacity

        Memories encode through steps of sensory memory to short-term memory to long-term memory. Within this process, attention is drawn to keep retaining information. Attention can be from associating an action or an image with the memory. Once an encoding of that memory happens, it is able to be stored in long term memory. Raphel, Matsukura, and Zerr et al. all show how short-term memory encodes memories into long term using visual images, games, or plain practice. 

Games such as crosswords require short-term memory to solve problems. In the article, "This is Your Brain on Crosswords," Adrienne Raphel dives into how crosswords are brain teasers relating to memory. Raphel claims that the memories used in “crosswords are in-between short-term memories and long-term memories” as you have to retrieve old memories and encode new ones (Raphel, 2020). This middle stage was labeled by Baddley as the episodic buffer which combines visuospatial and verbal information. Crossword experts were found to have a strong episodic buffer. This would make sense as visuospatial cues are used to form a word along with verbally spelling out the word helps restore and store memories. This indirectly shows the large capacity that the short-term memory holds as it uses verbal and visuospatial information to simultaneously store information.

While visuospatial information is useful for short-term memory, visual images can also affect the visual short-term memory capacity. In the article, “Does Visual Short-Term Memory have a High-Capacity Stage?,” Matsukura et al. explores how different types of visual stimuli affect the visual short-term memory (VSTM). While Raphel observed how real written crosswords affected short-term memory, Matsukura approached this topic with digital visual cues. This eliminates the verbal factors to focus on only the VSTM. Matsukura also noted that attention can further encode memories and decay can occur with distractions. There was a controlled environment in which orientation and color were manipulated to have more accurate results. Matsukura found that more valid cues were encoded as they had the most attention by the participants . This can also explain the episodic buffer in Raphel’s study as more attention is noted to words that involve more retrieval or visuospatial observation. Matsukura’s experiment also found that practice helped perceptual features encode better as well.

Practice is a large part in encoding short-term memories as it requires understanding and attention towards information or objects. In the article, “The development of retro-cue benefits with extensive practice: Implications for capacity estimation and attentional states in visual working memory, ” Zerr et al. used retro-cues to help aid recall in multiple memories and distribute resources within the same type of memory. Practice was also a large focus of this study as it is a technique used to provide better access to a larger memory storage. Practice was also predicted to lead to better retrieval of encoded memories. They showed the participants retro-cues multiple times and asked them to record if the item was the same or different. After many trials, the results showed that retro-cues are not the most beneficial way to test redistributing objects and drawing attention to the prioritized object. They also predicted that the visual working memory has a larger set capacity than the short-term memory as there is more organization and prioritizing of information. As practice was a main focus in this experiment, there were 500 trials run before collecting data to find a more conclusive result. While retro-cues work with the visual working memory, there were not significant results to prove that the cues accessed high-capacity storage. Overall, practice was the biggest indicator of encoding information efficiently.

In conclusion, all these articles emphasize different ways short-term memory can encode information. Raphael talked about how episodic buffering in crossword games allowed better encoding in short-term memory. Matsukura talked about valid cues that showed attention retention creating better encoding. Zerr et al. talked about how practice was beneficial for any retro-cues to be encoded in the visual working memory. All of these articles involved significant attention in order to complete the task which is why they all showed encoding into the short-term memory. Matsukura and Zerr et al.’s studies showed a theme about how the VSTM’s limited capacity creates the need for organization of important information to retrieve or encode. This organization is done by the working memory (Zerr et al., 2021). While practice was emphasized in Zerr et al.’s study, there was an overlapping concept about how practice creates a better technique for memorizing. This is evident in how crossword experts showed a high episodic buffer and many trails were done to find valid cues as the best encoded cue. Along with practice, standard visual set-ups such as crossword puzzles or objects in a certain color or orientation help encode items as there is more attention towards it. All in all, practice and attention towards visual images and games helps better encode information into short-term memory which leads to long-term memory with further repetition and retrieval.

Works Cited:

Matsukura, M., & Hollingworth, A. (2011). Does visual short-term memory have a high-capacity stage? Psychonomic Bulletin & Review, 18(6), 1098–1104. https://doi.org/10.3758/s13423-011-0153-2

Raphel, A. (2020, March 17). This Is Your Brain on Crosswords. Retrieved March 05, 2021, from https://blogs.scientificamerican.com/observations/this-is-your-brain-on-crosswords/

Zerr, P., Gayet, S., van den Esschert, F., Kappen, M., Olah, Z., & Van der Stigchel, S. (2021). The development of retro-cue benefits with extensive practice: Implications for capacity estimation and attentional states in visual working memory. Memory & cognition, 1–14. Advance online publication. https://doi.org/10.3758/s13421-021-01138-5

     

Quantitative EEG and Precision fMRI: The Future of Psychometric Testing in Clinical Evaluation

                     References: 

Gratton, C., et al. (2019). Defining individual-specific functional neuroanatomy for

precision psychiatry. Biological Psychiatry, 88(1), 28-39. doi:10.1016/j.biopsych.2019.10.026

McVoy, M., Lytle, S., Fulchiero, E., Aebi, M. E., Adeleye, O., & Sajatovic, M. (2019). A

systematic review of quantitative EEG as a possible biomarker in child psychiatric disorders. Psychiatryresearch, 279 331- 344. https://doi.org/10.1016/j.psychres.2019.07.004                 

                    Traditionally used as pivotal research techniques to further quantify the human brain, fMRI and EEG are invaluable to the fields of Psychology and Neuroscience. While both fMRI and EEG have strong roots within research, both research methods have their pros and cons. While fMRI has great spatial resolution, it lacks temporal resolution, with EEG having great temporal but poor spatial. Thus, research has relied on data collected from fMRI and EEG to work in concert to explore the concurrent hypotheses. In addition to the usefulness of fMRI and EEG in research, both psychometric tools are useful in clinical psychiatry and diagnosis. But with the aforementioned limitations in both methods, both fMRI and EEG remain constricted psychometric tests along with cost, inaccessibility, and immobility requirements during the test. However, recent breakthroughs in fMRI and EEG technology research has led to new, refined research methods that can be implemented in psychiatric diagnosis. Such refinements reveal the evolving and self-seeking prowess within Neuroscientists and Neuropathological researchers to yield more accurate diagnoses for psychiatric patients. In this blog, both precision fMRI (pfMRI) and qualitative EEG (qEEG) will be explored as pivotal and refined approaches in the diagnosis of psychiatric disorders.

                        In "Defining individual-specific functional neuroanatomy for precision psychiatry," Gratton et al. (2019) advocate for the use of precision fMRI due to the increased validity and individualization this research technique may provide in psychiatric testing. Precision fMRI confronts challenges typically seen in fMRI data collection by 1.) further understanding the normal versus pathological brain by individual scan studies, 2.) providing tools for accurate diagnosis and prognosis at the individual level, 3.) a subject-specific targeting of the specific pathology, and 4.) treatment tracking for efficiency and remission. In this present study, there is strong supportive evidence of the pfMRI model of collecting "larger quantities of fMRI data in single individuals as opposed to smaller quantities of data averaged over groups" (Gratton et al. 2019). Such a strategy emphasizes the connection between individual differences and differences in brain functions. Ultimately, the refined pfMRI benefits psychiatry diagnoses through increasing validity and data specification. Whereas the fMRI scan would be compared to a normal scan to determine pathology, the pfMRI scan relies on the individual changes that lead to the production of such pathology. Through this new approach, further individualization can be applied to psychiatric diagnoses to be accurately applied to each unique patient.

                      In "A systematic review of quantitative EEG as a possible biomarker in child psychiatric disorders," McVoy et al. (2019) demonstrate the usefulness of quantitative EEG in psychiatric diagnoses, particularly in children. While an EEG records raw data, the electrical activity encoded from the brain in real-time, the qEEG has statistical and mathematical formulas directly integrated and recording in the data collection process. Such a device is useful in comparing direct changes in latency in specific alpha, beta, theta, or delta bands. Researchers McVoy et al. (2019) review such qEEG biomarker patterns in children and their evidence reveal qEEG-specific patterns in psychiatric disorders. By compiling and comparing the biomarkers, psychiatric diagnoses can be narrowed, aiding diagnosticians and researchers alike. 

            To conclude, the fields of Neuroscience and Psychology are ever-expanding, and research conducted not only better serves the understanding of the complexities of the mind but promotes an important clinical application. By researching and modifying current tools available to researchers and diagnosticians, a further level of refinement and validity can be obtained and applied. Not only yielding more effective evidence and understanding of the brain but also being more accurate in the diagnoses of psychiatric patients. The Gratton et al. (2019) and McVoy et al. (2019) studies reflect the overall goal of this trend: utilize the research and apply it to psychiatric diagnoses, improving the validity and access to accurate diagnoses. Even though neither pfMRI and qEEG are perfect psychometric devices, this attention to refining our research collecting tools moves us to a future of cost-effective testing for our patients and higher confidence in psychiatric diagnosing and treatment. 

The Mystery of Saccadic Suppression

 The Mystery of Saccadic Suppression 

The process of moving our eyes several times per second is characterized by saccadic movements, which are vast images shifting on the retina. Visual stability across saccades tends to vary throughout the visual system, and has different effects on prioritization as opposed to fixation. The process of fixation seems to be more feasible and time efficient when looking at prioritization effects, due to saccadic suppression occurring. Studies have shown evidence for saccadic suppression by comparing fixation points and saccadic eye movements when viewing real-world objects.

In the study “Overt Attentional Prioritization of New Objects and Feature Changes During Real-world Scene Viewing,” Michi Matsukura and colleagues observed the extent to which a color change or appearance of a new object would have a greater effect on subjects during real-world scene viewing. Matsukura et al. (2009) found that both types of these scene changes produced effects in capturing gaze, but the appearance of new objects caught more attention than a color change during fixation. During saccadic eye movements, however, none of these scene changes captured attention due to saccadic suppression. Despite this suppression, memory-based mechanisms still have the ability to prioritize these scene changes compared to other stagnant objects in the picture. Matsukura and colleagues concluded that online memory for object identity and some object features work in detecting changes to live scenes. Fixations were accompanied by transient motion signals, which was why attention was captured more quickly than during saccades, which eliminated these transient signals. 

An article published on ScienceDaily called, “The Mystery of Visual Stability” from Tohoku University explains the mechanisms underlying saccadic eye movements. These fast movements of the eye force the visual system to work hard to uphold a stable perceptual world. This is compensated for by remapping the retinal image; however, even with remapping, errors in actual eye movements cause image shifts. Research led by Professor Satoshi Shiorir investigated the processes underlying Saccadic Suppression of Displacement (SSD). Similar to the study with Matsukura et al. (2009), this psychological experiment included subjects staring at a fixation point, and after this point disappeared, the subjects shifted their eyes to a target on the opposite side. Researchers observed the targets before and after saccades occurred in order to control the retinal input power. The article discusses the results from this experiment, explaining that there are two visual pathways responsible for two different effects. These two major pathways are the parvo-pathway and magno-pathway, which are involved in suppressing inaccurate motion information through saccades, and detecting displacements, respectively. The bridge between this news article and the research conducted by Matsukura et al. (2009) is the suppression of saccadic eye movements, resulting in quicker prioritization during fixation. 

While much more work needs to be done to fully grasp the understanding of visual stability across saccades, the work of Matsukura et al. (2009) and Professor Satoshi Shiorir of Tohoku University provides a strong foundation for how these processes occur. Even though SSD stays a mystery to neuroscientists, improvements in technology and methods can help them further understand the processes associated with saccadic eye movements, particularly saccadic suppression. 

Sources: 

Brockmole, J.R., Henderson, J.M., Matsukura, M. (2009). Overt attentional prioritization of new objects and features changes during real-world scene viewing. Visual Cognition, 17 (6/7), 835-855. https://doi.org/10.1080/13506280902868660

Tohoku University (2020). The mystery of visual stability. ScienceDaily. https://www.sciencedaily.com/releases/2020/06/200611094213.htm

Possible Explanations for Lack of Comprehension of Digital Formatting

    In response to the onset of the coronavirus pandemic, our country and others worldwide shifted online in order to make a compromise between minimal contact and continued education. With this shift online along with the continuous evolution in technology, the consumption of digital media increased. According to Forbes, broadband providers reported traffic surges between 30%-50% within the first month of quarantine, with total internet usage estimated to have increased by 50%-70%. Much of this is accounted for by the massive migration to online educational platforms. As the future generations’ educations are being impacted, it is essential to further understand how the COVID-19 pandemic has impacted their education beyond this displacement.  

    With moving online, the majority of resources available to students are in a digital format. Digital formatting can sometimes make learning more hard, especially when students are already digital for the majority of their class time. According to Lauren Singer Trakhman who studies reading comprehension at the University of Maryland, College Park, it’s easier to miss details when reading screens. For screen usage, she offers that perhaps the light causes more visual strain and thus mental fatigue. Anne Mangen, a literacy professor at the University of Stavanger in Norway, presented that even the physical act of turning a page improves comprehension in comparison to scrolling or clicking a button because of the sensorimotor cues formed. While we read, our brains form a cognitive map of the text that allows us to better comprehend and recall what we’ve read. For digital formatting, the ability to move pages has a large impact on why our comprehension is lessened. In their article “Cognitive Map or Medium Materiality? Reading On Paper and Screen,” Jinghui Hou, et al. (2017) hypothesized and found support that, as long as reading format facilitates the ability to construct a cognitive map, our overall comprehension doesn’t decrease. For a cognitive map, it allows us to better comprehend and recall what we’ve read because of the ability to remember what happened on each section of a page. For digital formatting, the movement of pages doesn’t allow this as well as physical text does. Digital formatting doesn’t feature fixed locations and thus doesn’t allow readers to form a permanent or adequate cognitive map of the text, lowering their overall comprehension. This is inherently detrimental to students and hurts their ability to learn, leading students more susceptible to failure during an already difficult pandemic.

    To further understand visual comprehension in a digital form, it might be important to understand visual short term memory better. In their article "Does Visual Short-Term Memory Have A High-Capacity Stage," Michi Matsukura and Andrew Hollingworth explored recent work by Sligte et al. that offered the hypothesis that "relatively early after the removal of a memory array, a cue allowed participants to access a fragile, high-capacity stage of VSTM [visual short term memory] that is distinct from iconic memory." Matsukura and Hollingworth provided further support of the hypothesis that, in comparison to the experiment done by Sligte et al. in which the estimated storage capacity was 16 items, the storage capacity of the VSTM is actually much smaller, supporting the standard limited capacity view of  VSTM. They found that "overall accuracy was higher for color discrimination than for orientation discrimination." Along with previous findings for digital reading that formatting impacts comprehension due to its hindrance on forming a cognitive map, Matsukura and Hollingworth’s research found that orientation has an impact on the amount of items correctly stored in the VSTM.

    Given the inadequate processing associated with reading in a digital format, it’s necessary to consider what possible neuroanatomical aspects lead to lower comprehension levels. Given Hou’s, Singer Trakhman’s, and Mangen’s research, it’s possible that digital formatting, lack of cues, and strain might all contribute to lower comprehension. Given Matsukura’s and Hollingworth’s research, formatting and orientation overall impacts VSTM. This would support the idea that formatting impacts comprehension in some way. Perhaps strain or lack of an adequate cognitive map contributes to a weakened ability of storing items in the visual short term memory at that given time, something that then wouldn’t be as present during reading in a more physical format. Perhaps an inadequate cognitive map requires more working memory and thus less literature details can be stored. Further research to determine what the correct reasoning behind lack of comprehension with digital media is needed, but the idea that orientation and formatting might be essential is important. For schools and businesses alike, the resources given should be rethought to better fit current scientific research, especially in a time where the majority of what we receive is digitally formatted.

References:

Beech, M. (2020, March 25). COVID-19 Pushes Up Internet Use 70% And Streaming More Than 12%, First Figures Reveal. Forbes. COVID-19 Pushes Up Internet Use 70% And Streaming More Than 12%, First Figures Reveal (forbes.com)

Benson, K. (2020, July 28). Reading on Paper VS Screens: What’s the Difference? BrainFacts. Reading on Paper Versus Screens: What’s the Difference? (brainfacts.org)

Hou, J. et. al (2017). Cognitive map or medium materiality? Reading on paper and screen. Computers in Human Behavior, 67: 84-94.

Matsukura, M., Hollingworth, A. (2011). Does visual short-term Memory have a high-capacity stage? Psychon Bull Rev (2011) 18:1098–1104

Sligte, I. G., Scholte, H. S., & Lamme, V. A. F. (2008). Are there multiple visual short-term memory stores? PloS One, 3,e1699

Do We All Feel Regret?

 Do We All Feel Regret?

    The word regret can be defined as feeling sad or disappointed over something that has happened or something that has been done. It is almost impossible for a human to say that they have never experienced regret. Our biggest regrets sometimes even make up our character and shape up who we are. We often hear the phrase “we learn from our mistakes’ which is true in most cases. We don’t want to make the same mistake twice, or else the feeling of regret feels even worse. There have been countless studies on the memory of humans and animals. In terms of regret, we find an interesting study on mouse memory conducted by a group of researchers led by Brian M. Sweis. By comparing models of memory and regret within human and nonhuman psychology, we can make inferences bases on the similarities and differences found in these studies

    The first study involving the mice talked how about how regret can be defined and measured. They pointed out how current and recent studies show that the feeling of short-term regret has be examined, but there are not too many studied conducted on the long-term feelings or effects of regret. This article explains how mice were able to feel long-term regret after a long and conclusive experiment. How the researchers came up with a method to test their hypothesis was very intriguing. The mice were able to adapt and use strategies to make decisions in order to conserve their resource. At first, the mice would consume their resource relatively quickly. However soon after learning that they couldn’t attain the resources, their regret prevented from making the same mistake again in the in future. Repetition of this experiment showed that the mice were learning to avoid the same mistakes they had made.

    Another article shows that although young children won’t really understand the meaning of regret until the age of 9, studies have shown that they will demonstrate a feeling of regret and learn from it. The article explains that by the age of 6, most children will have experienced the emotion of regret, but they wouldn’t necessarily be able to explain it. McCormack, T. et al were able to find that although children aren’t able to explain or define regret, they can still see the impact and effects of regret after a child has gone through some level of it. Their study showed that after a child experiences regret after making a certain decision, that child will be less likely to make that same decision and be more likely to make a more positive choice the next time. This research also showed that regret taught children to postpone enjoyment of any sort and have an improved behavior towards others. 

    These studies show different yet similar results amongst the psychology of humans and nonhumans. First we see that the mice are able to feel regret and learn from their mistakes. Now it’s a given that the mice can’t really feel regret and that maybe they are just conditioned to receiving their resources when best suited. Then we see children who don’t really understand regret but show similar results to the mice. After feeling regret following a decision they made, they tend to avoid that same decision in order to avert that same feeling of regret again. It would be interesting to see if we can see feelings of regret within other animals or we can see how different cultures show and handle regret. 

Reference

McCormack, Teresa, et al. “Regret and Decision-Making: A Developmental Perspective.” Current Directions in Psychological Science, vol. 29, no. 4, 2020, pp. 346–350., doi:10.1177/0963721420917688. 

Sweis, Brian M., et al. “Mice Learn to Avoid Regret.” PLOS Biology, vol. 16, no. 6, 2018, doi:10.1371/journal.pbio.2005853. 

Sunk Costs in Humans, Mice, Monkeys, and even Role-Playing Games

 

It is often observed in humans that once enough time has been invested into something, it is difficult to just outright give up on it. This type of economic phenomenon is known as “Sunk Costs” and is seen in many different forms. It can take the form of many different situations in humans from something as simple as whether it is worth waiting for a better model phone or buying a new one now to more serious choices such as whether it is a good idea to leave an entire career path or change one’s area of study after investing years of one’s life into it. Indeed, sunk costs is observed extensively in humans. But is this behavior seen in different species? If so than what sort of thought processes influence such behaviors in animals that can perceive sunk costs? Or perhaps this is a behavior simply observed in just humans, implying a special level of thought that is exclusive to humanity. This is what researcher set to find out.

 

Dr. Sweiss was able to observe this pattern of behavior in mice by creating a maze that offers mice a “sunk cost” situation. The rates were placed into a “restaurant” that offered four different foods for the mice to choose from: plain pellets, grape, chocolate, or banana. The key in this experiment is that the foods were locked behind different wait zone for each of the different foods. For example, a rat was presented to the restaurant and “shops across the different options for a piece of food that it desires, such as grape. It would then go to the grape area and wait for a certain amount of time until the food dispenses. However, the mouse also has the choice in forgoing the grape and instead can move to a plain pellet and wait for less time. It was recorded that some mice were able to wait long enough to receive a higher reward such as a grape, though some mice only learned of this after opting for a more immediate option such as a plan pellet. The mice were able to prioritize foraging strategies accordingly once an economically bad decision had been made upon seeing alternatives that could have been taken instead. This demonstrates that animals, such as mice, are also able to experience Sunk Costs just like humans when given decisions.

 

It is not just rats that exemplify this understanding of costs and benefits, this type of behavior is also found in species of monkey such as Capuchin and Rhesus monkeys. Dr. Watzek had the monkeys play a game in which using a joystick, they operated a cursor that can dispense a treat if the cursor stays in line, if not, no treat is dispensed. Although initial trials showed that the monkeys were not that impressive with most monkeys not being able to attain the treat, some subjects later learned that a longer participation in the game will result in a reward, being the treat, and so learned to continue with the game despite initial difficulties. The results were found to be similar across the two species. This experiment also affirms the idea that Sunk Costs is not just a Human trait, but is also found across different species.

 

While Sunk Costs have been observed extensively in the lab in different animals, there are other more unorthodox ways to observe such phenomena in humans. One such medium that presents Sunk Costs is role playing video games such as The Elder Scrolls V: Skyrim. The game has a form of skill currency known as “skill points” which is a form of character advancement currency that advances a player’s skill as they play and they cannot be moved around unless heavy amounts of time is invested in-game. Skill points are used across different skill trees can be divided to essentially three different “career” choices: mage, thief, and warrior. By using skills and acting a certain way in game, different skill points are earned to help advance these traits. There may be times however that the player will find that investing in certain skill will be beneficial for one situation, but maladaptive for another. For example, a more warrior centric character will be able to go through with using the sword and shield proficiently to go about playing the game. However, when presented with an opportunity to make more money by playing as a thief, it becomes difficult to decide if it is worth a trade off due to the investment already as a warrior in terms of time. This replicates the “regret” found in Dr. Weiss’ experiments. Role playing games offer a different medium from the traditional studies on animals and the more dubious ethical experiments done on humans as the setting provides a near limitless medium to experiment with different levels and concepts of decision making that can be associated with Sunk Costs.

 

Future experiments such as those conducted by Dr. Sweiss and Watzek offer an opportunity to learn more about how humans and animals invest resources and times according to the ideas of sunk costs. Such research will be able a better understand the nature of resource allocation affects the behaviors of humans and animals and bring a better insight on what thought processes could drive different species to make the economic situations that they do, as well as how they deal with the consequences of making disadvantageous decisions.

References:

Sweis, B. M., Thomas, M. J., & Redish, A. D. (2018). Mice learn to avoid regret. PLOS Biology, 16(6). https://doi.org/10.1371/journal.pbio.2005853

Watzek, J., & Brosnan, S. (2020). Capuchin and rhesus monkeys show sunk cost effects in a psychomotor task. https://doi.org/10.31234/osf.io/qtgru