Category Archives: decision-making

Decision-making research in autism and schizophrenia: Implications for each other

Today I would like to review two recent articles on decision-making: one concerned with autism or ASD and the other with Schizophrenia individuals. I would like to demonstrate how some of the findings fit in, in the larger context of Autism and Schizophrenia as diametrical poles on a continuum.

The first article is by Martino et al, and discusses a finding that those with ASD display more consistent and logical decision-making that is immune to framing effects.  Here is the abstract of the study:

The emotional responses elicited by the way options are framed often results in lack of logical consistency in human decision making. In this study, we investigated subjects with autism spectrum disorder (ASD) using a financial task in which the monetary prospects were presented as either loss or gain. We report both behavioral evidence that ASD subjects show a reduced susceptibility to the framing effect and psycho-physiological evidence that they fail to incorporate emotional context into the decision-making process. On this basis, we suggest that this insensitivity to contextual frame, although enhancing choice consistency in ASD, may also underpin core deficits in this disorder. These data highlight both benefits and costs arising from multiple decision processes in human cognition.

Here is the introduction:

Logical consistency across decisions, regardless of how choices are presented, is a central tenet of rational choice theory and the cornerstone of modern economic and political science. Empirical data challenge this perspective by showing that humans are highly susceptible to the manner or context in which options are cast, resulting in a decision bias termed the “framing effect”. We have previously shown that the amygdala mediates this framing bias, a finding that highlights the importance of incorporating emotional processes within models of human decision making. An ability to integrate emotional contextual information into the decision process provides a useful heuristic in decision making under uncertainty. This is a factor that is likely to assume considerable importance during social interactions in which information about others is often incomplete, ambiguous, and not easily amenable to standard inferential reasoning processes.

In this study, we investigated the effect of contextual frame on choice behavior of individuals with autistic spectrum disorder (ASD). Autism is a neurodevelopmental disorder characterized by deficits in social interaction, qualitative impairments in communication, and repetitive and stereotyped patterns of behavior, interests, and activities. From Kanner’s earliest description, it has been recognized that individuals with ASD have a strong tendency to focus on parts rather than global aspects of objects of interest and are unable to integrate disparate information into a meaningful whole (weak central coherence theory).

We previously proposed that susceptibility to a framing bias reflects the operation of an affect heuristic. Here, we show that individuals with ASD, a condition characterized by marked behavioral inflexibility, demonstrate a decreased susceptibility to framing resulting in an unusual enhancement in logical consistency that is paradoxically more in line with the normative prescriptions of rationality at the core of the current economics theory. Furthermore, insensitivity in these subjects to a contextual framing bias was associated with a failure to express a differential autonomic response to contextual cues as indexed in skin conductance responses (SCRs), a standard measure of emotional processing. Our findings suggest that a more consistent pattern of choice in the ASD group reflects a failure to incorporate emotional cues into the decision process, an enhanced economic “rationality” that may come at a cost of reduced behavioral flexibility.

The experimental procedure used framing of gambles in terms of loss and gain and it is a well established paradigm that shows that normal people are risk-averse when the same gamble is framed in gain terms and risk-prone when the same gamble is framed in loss terms. Autistcis were not only more risk-averse in general , but their responses did not differ in relation to whether the frame was of loss or of gain. Thus, they were consistent in both the framing conditions. also , a measure fo their skin conductance did not show differential activation in the two frames of loss and gain; while the SCR of controls differed significantly. thus, teh authors conclude that it is the inability to take into account emotional information, that results in the consistent response of the autistics.Here is the discussion:

These findings suggest the ASD group fail to integrate emotional contextual cues into the decision-making process. This is evident both in a reduced behavioral susceptibility of a framing effect and an absence of a differential SCR response to our contextual manipulation. The concept that ASD individuals fail to integrate information across cognitive domains also informs the suggestion that an uneven profile of abilities and deficiencies in autistic individuals may reveal an imbalance in empathizing and systemizing behaviors (Baron-Cohen and Belmonte, 2005)

They discuss these findings in terms of the two-system theory of decision-making and here is what they have to say:

Recent theoretical accounts of decision making have put forward a “two-systems” model of human judgment (Evans, 2003). This view proposes that human decision making arises through a combination of intuitive and analytic processes. This model proposes that intuitive reasoning is rapid and capable of processing large amounts of information in parallel; however, it is prone to mistakes and strongly influenced by contextual emotional information (Kahneman, 2003). In contrast, analytical reasoning is more accurate but slow and computationally demanding. According to this view, the framing bias reflects an affect heuristic by which normal individuals incorporate a potentially broad range of additional emotional information into the decision process. In evolutionary terms, this mechanism may confer a strong advantage because such contextual cues may carry useful, even critical, information that dictates a rapid response. We propose that this ability is particularly crucial in a social context in that subtle contextual cues communicate knowledge elements (possibly unconscious) that allow optimal decisions to be made in uncertain environments (Stanovich and West, 2002).

In the context of the “two-systems” model of decision making described above, these results suggest that ASD individuals have an increased tendency toward the analytic type of decision making, attributable to impairment within their intuitive reasoning mechanisms. This interpretation would also support the empathizing-systemizing (E-S) theory of autism (Baron-Cohen and Belmonte, 2005). The E-S theory proposes that the imbalance between analytic and empathic behavior underlies both the impairment in social skills in ASD and their enhanced analytical skills. During the framing task, ASD subjects were better able to ignore biasing contextual information and isolate the critical information about the numerical value of the sure and risky options. This result is consistent with other experimental findings showing that ASD have enhanced attention for the task’s details but reduced capacity to deal with the global aspect of the task as predicted by weak coherence theory (Frith and Happé, 1994).

Now, I am just overjoyed reading the above. It has always been my contention that Autistics use a more deliberate, rational approach to decisions while schizophrenics are at the opposite end relying on the intuitive part. I elaborated it in the form of Maximisers and Satisficers distinction that Barry Scwatrz has proposed and extended it to include exploration and exploitation in general. In short my thesis was, and remains, that autistics are more analytical while decision-making and schizophrenics more intuitive . the former does not take the context or frames into account while making decisions while the other takes into account too much context and is susceptible to too much framing effects.

If the above thesis is correct it leads to many testable predictions:

  • 1) Schizophnrenics/ Schizotypal individuals should be more susceptible to framing effects and should show greater inconsistencies in decision-making under uncertainity as compared to controls.
  • 2) They may also show more SCR variability when different frames of loss and gain are presented to them as compared to controls.
  • 3) They may have higher baseline risk-prone behavior than controls in all conditions.
  • 4) They may have higher activation in amygdala than controls as they use affect heuristic quite frequently while making decisions.

Part of this prediction may be satisfied by this decision-making and schizophrenia study by Ludwig et al  that found decision-making dysregulation in first episode Schizophrneia patients. Here is the abstract of the study:

Studies with chronic schizophrenia patients have demonstrated that patients fluctuate between rigid and unpredictable responses in decision-making situations, a phenomenon which has been called dysregulation. The aim of this study was to investigate whether schizophrenia patients already display dysregulated behavior at the beginning of their illness. Thirty-two first-episode schizophrenia or schizophreniform patients and 30 healthy controls performed the two-choice prediction task. The decision-making behavior of first-episode patients was shown to be characterized by a high degree of dysregulation accompanied by low metric entropy and a tendency towards increased mutual information. These results indicate that behavioral abnormalities during the two-choice prediction task are already present during the early stages of the illness.

The authors used the CT paradigm and it is important to explain that a bit here:

The purpose of the CT is to quantify decision-making characteristics based on the individuals’ sequential response patterns, which result from repeated selections of different alternatives associated with an uncertain outcome. Each subject received computerized instructions. The subject’s task is to predict on which side a stimulus (a car on the screen) will appear and select a response (to match up one of 2 figures shown on the screen) accordingly. The outcome is shown for 250 milliseconds after the subject has selected as response. A new trial begins immediately after the car has been displayed. The subject is not given any information about the sequence of the stimulus presentations, i.e., whether the stimulus is presented randomly or in any kind of order. Unbeknownst to the subjects, the location of the car shown is based on the subject’s response, i.e., the subject “correctly” predicts the location of the car in 64 trials. The basic measurements consist of the subject’s response, the presentation of the car and the latency of the response selection process, i.e., the time from the beginning of the trial to the pressing of the button. For the behavioral analysis, we used nonlinear methods— described elsewhere in detail (Paulus et al., 2001)—to obtain the following key measures:

Dysregulation: Dysregulation quantifies the range of response sequence entropies during the course of an experiment.A high dysregulation value indicates that the response sequences occurring during the experiment are characterized by botho¨perseverative tendencies“ and highly unpredictable or dynamically ”chaotic” strategies.

Metric entropy: Entropy measures the “sequential order” within sequences of responses. Whereas low entropy indicates that the response sequences are highly predictable, high entropy implies highly unpredictable response sequences. Thus, predictability is a collateral measure for the degree to which sequences of responses are based on a consistent internal strategy. However,this measure does not take into account the dependence of the response sequence on external stimuli, which is measured by the cross-mutual information (see below).

Mutual information: Mutual information quantifies the degree to which the previous response predicted the current response and provides a measure of the immediate influence of the past response on the decision in the current trial.

Cross-mutual information: Cross-mutual information quantifies the degree to which the previous location of the stimulus (presentation of the car on the LEFT or RIGHT hand side) is able to predict the current response. As opposed to entropy and mutual information, this measure quantifies the influence of external stimuli on the response sequences.

Switching probability: the probability of using the simple strategy RIGHT – LEFT.

Reaction time: the time between stimulus and response.

What they observed is summarized below:

As shown above in the results section, first-episode patients performing this decision-making test, irrespective of whether they were unmedicated or recently medicated, can be observed to have (a) more dysregulated behavior, (b) a reduced metric entropy, and (c) a tendency towards increased mutual information. As a specific response behavior (d), the patients used the switching strategy more intensely (switching between pushing the right and the left button). This study has supported our main hypothesis that decision-making dysfunctions are already present in first-episode schizophrenia (or SZ) patients.

I believe the results need some explanation, and I will stick my neck out here. More dysregulated behavior in my view, is due to the schizophrenic either trying too hard to remain consistent (when in self-aware frame of mind) or trying to be unpredictable (when in other-aware and being-watched frame of mind). The reduced metric entropy can be explained similarly . Tendency towards increased mutual information is quite informative in my view. It seems that the schizophenreic is working on the basis of an internal model and is ignoring external feedback: thus his reliance on previous response.I propose that an opposite pattern would be observed in Autistics with Autistics showing no or less mutual information, as they have poor self-models; but greater cross-mutual information , as they would base their decisions more on external stimuli or feedback.

Some other predictions, keeping in mind the autism is opposite of Schizophrenia theory are:

  • 1) Autistcis should show lesser dysregulation and more rational behavior than even controls.
  • 2) autistcis should show greater cross-mutual information than controls.
  • 3) Autistcis may or may not show lesser mutual information.
  • 4) Autistcis should use less switching strategy than controls.

All these are testable predictions and I hope someone out there tests these and lets me know!
ResearchBlogging.org
B. De Martino, N. A. Harrison, S. Knafo, G. Bird, R. J. Dolan (2008). Explaining Enhanced Logical Consistency during Decision Making in Autism Journal of Neuroscience, 28 (42), 10746-10750 DOI: 10.1523/JNEUROSCI.2895-08.2008
Cattapan-Ludewig Katja; Ludewig Stephan; Messerli Nadine; Vollenweider Franz X; Seitz Antonia; Feldon Joram; Paulus Martin P (2008). Decision-Making Dysregulation in First-Episode
Schizophrenia The Journal of nervous and mental disease, 196 (2), 157-160

Exploration/ Exploitation == Maximisers/ Satisficers?

There is an interesting research coverage at We are Only Human blog regarding whether people may have two different cognitive styles- one based on exploration of novel ideas and the other based on exploitation or focus on a particular familiar idea. The study employs evolutionary concepts and theorizes that these different cognitive styles may be a reflection of the different foraging styles that might have been selected for and relevant in EEA.

Specifically, while foraging for food in a habitat where the food supply and resources are unpredictable , one is faced with a choice when one has discovered a food source: whether to exploit this food source (a jungle area having sparse edible leaves) or to move ahead in search of a potentially better food source (a jungle area having abundant edible and nutritious fruits) . Both strategies , that of exploring or exploiting can be advantageous and may have been selected for. It is also possible that humans can use either of the strategies based on the environment- (food source distribution) , but may be inclined towards one strategy or the other. The authors of the study surmised that both the strategies have been selected for and we have the potential to use either of the strategy. Moreover, the same foraging strategy we use or are primed of, would also be visible in the cognitive strategy we use.

They used an ingenious technique to prime the subjects with either of the foraging strategies (go read the excellent We are only human blog post) and found that humans were flexible in the use of the appropriate strategy, given the appropriate context, and that the foraging strategy primed the corresponding cognitive strategy. To boot, those primed with an exploratory foraging strategy would be more prone to using exploratory cognitive strategies when confronted with a cognitive task and vice versa. They also found systematic differences between individuals cognitive and foraging styles- some were more exploratory than the others.

This reminds me of the Maximizers/ Satisficers distinction in decision-making style that Barry Scwatrz has introduced and brought to public attention. Basically a Maximizer , when faced with a decision and choice, would go on computing the utility of different choices and try to choose the option that maximizes his utility and is the ‘best’. A Satisficer, on the other hand would also explore options, but stop his exploration, when he finds an option that is ‘good enough’. I wonder, if just like the exploratory/ Exploitative cognitive and foraging styles, this is just another dimension of the same underlying phenomenon- whether to explore more – or to exploit what is available. To take an example, for marriage, a satisficing strategy may work best – as told in “The Little Prince” one should stop searching for more flowers if one has already had the fortune of possessing a flower.

“People where you live,” the little prince said, “grow five thousand roses in one garden… yet they don’t find what they’re looking for…”

“They don’t find it,” I answered.

“And yet what they’re looking for could be found in a single rose, or a little water…”

An interesting experiment would be to see, if the foraging style, the cognitive style, and the decisions style are all correlated within individuals and if priming one can influence the outcome of the other style.

If so, could there be an underlying neural phenomenon , common to all?

Wray, the author of We are only human blog makes a bold conjecture and relates this to the finding that dopamine levels.

Exploratory and inattentive foraging—actual or abstract—appears linked to decreases in the brain chemical dopamine.

He even relates this to cognitive disorders like Autism and ADHD.

By analogy, in conditions where baseline dopamine is more, like in bipolar and psychosis, one may be more inclined to a more staisficing/ ‘I’m feeling Lucky’ strategy in which the very first option is acceptable. This may explain the ‘jumping-to-conclusions’ bias in schizophrenia/ psychosis.

To make things more explicit, though the leading dopamine theory in vogue now is of ‘error-prediction’ , a competing, and to me more reasonable, view of dopamine function is incentive salience i.e. what ‘value’/ importance does the stimuli have for the person in question. The importance can be both positive and negative and thus we have found that dopamine is involved in both dread and desire. The dominant reward prediction theory faces many challenges, the least of which is response of dopamine neurons to novel events. A dopamine burst is also associated with ‘novel’ events and thus dopamine is somehow involved in/ triggered by Novelty. Baseline dopamine may constrain the dopamine surge felt on a novel event. Thus, in schizophrenia/ psychosis , with baseline dopamine high, a dopamine burst on novelty detection may be high enough so that it is meaningful and may not lead to more exploratory behavior. While in the disorders where baseline dopamine is low, one may require a more profound dopamine burst before the stimuli becoming meaningful and thus may go on seeking novel stimulus till one finds one ‘big enough to trigger salience’.

We may extend the salience argument to other domains than incentive. If the chief function of dopamine is to mark salience, then it may also be instrumental in memory and attention. Only what is Salient gets attention, and only what is salient gets into Working Memory. Thus,a high dopamine level may predispose to treating almost everything as salient, leading to delusions of reference (everything is meaningfully related to self etc) etc. Working Memory may be taxed due to everything trying to get in- and thus poor WM in people with schizophrenia. Also, every trivial thing may grab attention- leading to poor sensory gating and conditions like lack of pre-pulse inhibition. On the flip side, while making sense of ones experience, one may accept the first possible explanation and do not search further – thus leading to persistence of delusions.

An opposite scenario would be when one keeps exploring the environment and nothing seems novel due to low dopamine levels. This would be the classical Autistic repetitive and stereotype behaviors. There would be sensory over stimulation, as nothing is salient and one needs to explore more and more. On the other hand, WM capabilities may be good/ savant like, as not every piece of information grabs attention. Everything should seem insignificant and the only way to arrive at decision / choose action would be via exhaustive enumeration and logical evaluations of all options. even after obvious explanations for phenomenon, one may keep looking for a better explanation. No wonder , as per my theory, more scientists would be autistic.

Perhaps, I am stretching things too far, but to me the dopamine connection to Salience/ Meaning/ Importance is sort of worth exploring and I will write more about that in future. For now, let us be willing to associate Salience not just with stimuli related to motivation, but also with stimuli relevant in sensation, perception,learning and memory. If so the common underlying mechanism responsible for differentiating us as a exploratory and expolitatory forager (food) may also be related to our different cognitive styles, our different decision-making styles and our different baseline dopamine levels.

Dopamine though is most strongly related to food and sex. I could even stretch this argument and say this may be related to r and K reproductive styles (note these styles are species specific, but I believe individuals in a specie may also vary on the reproductive strategy along this dimension). Thus, while explorers may have r type of reproductive style, the exploiters may have a K reproductive style.

At one extreme are r-strategies, emphasizing gamete production, mating behavior, and high reproductive rates, and at the other extreme are K-strategies, emphasizing high levels of parental care, resource acquisition, kin provisioning, and social complexity.

If K-strategy is what humans have chosen, maybe exploitation in all areas (cognitive, decision-making, foraging) is more relevant and in tune with our nature. Maybe that’s why I’ll always be on the side of Psychosis than Autism!! Though, to put things in perspective, maybe humans have evolved to use both strategies as the situations demands , and the best thing would be to use the strategy situation-specific and not lean towards either extremes.

Psychology of security

This is an FYI post about a great article by Bruce Schneier, assessing the psychological issues involved in assessing various security trade-offs. He touches on all aspects of behavioral finance,psychological biases, prospect theory, decision-making etc that are relevant and affect our felling of security vis-a-vis actual and objective security. Although, he is not that strong when it comes to discussing the neurological basis of these, I would highly recommended reading the article in its entirety!

Moral Intuitions: Musings continued.

In the last post, we dwelled on the classical trolley problem as well as a new type of moral dilemma that may be termed as the Airplane dilemma.

In some versions of the Airplane (as well as the Trolley ) problem, the problem is framed so as to implore us into examining our notions of trusting or being suspicious of strangers (terrorists scenarios) and to take into account the past as well as future characteristics of these people (like high IQ and national celebrity status) to arrive at a moral decision, as to serving whom would be a more moral action for the doctor. The airplane problem mostly focuses on Trust Vs Suspiciousness dimension, is people-centered and focuses on assessing people and situations correctly in a limited amount of time. After the decision is made, then the action is more or less straight-forward.

The trolley problem is also similar, but of a somewhat different nature. Here, the focus is on actions and outcomes. The Morality of action is judged by its outcome as well as other factors like whether the (in) action was due to negligence, indirect, personalty motivated etc. The people centered focus is limited to using-as-means versus ends-in-themselves distinction and in the later problems (president-in-the-yard) that of guilty vs innocent. The innocent, careful child playing on unused track, while the careless , ignorant five idiots playing on the used track is another variation that plays on this careful action versus careless action distinction.

It is my contention that while the Trolley problem aptly makes clear the various distinction and subtleties involved in an Action predicate, viz whether the action is intentional, whether it is accidental- and if so how much negligence is involved; whether (in)action could be prevented/ executed differently for different outcomes etc; it does not offer much insight on how to evaluate Outcome Predicate or the Intention Predicates.

In the Trolley Problem, while the intentional vs accidental difference may guide our intuition regarding good and evil , in case of positive or negative outcomes; the careful versus careless (negligent) action guides our intuitions regarding the normal day-to-day good and bad acts. Here a distinction must be made between Evil (intentionally bad outcome) versus Bad acts(accidental or negligent bad outcome).One can even make a distinction between Good acts (performed with good intentions) versus Lucky acts (accidental good outcomes, maybe due to fortuitous care exhibited). Thus, a child playing on an unused track may juts be a ‘bad’ child; but five guilty men tied on tracks (even by a mad philosopher) are an ‘evil’ lot. Our intuitions, thus , would be different in the two cases and would not necessarily be determined by utilitarian concerns like number of lives.

Some formulations of the airplane problem, on the other hand , relate to quick assessment of people and situations and whether to trust or be suspicious. The problem is complicated by the fact that should the doctor invest time in gathering more data/ confirming/rejecting her suspicion versus acting quickly and potentially aggravating the situation/ long-term outcome. These formulations and our intuitive answers may tell us more about the intention predicates we normally use. Whether we intend to be trusting, innocent and trustworthy or suspicious, cautious and careful. If cautious and careful, how much assessment/ fact gathering we must first resort to to arrive at the correct decision, before committing to single-minded and careful action.
Should we juts look at the past for arriving at a decision, or should we also predict the future and take that into account? If we do predict the Outcomes, then the Consequence predicate is long-term or short-term? Is it an optimistic or a worst-case outcome scenario?

There are no easy answers. But neither is the grammar of any language supposed to be easy. Constructing valid and moral sentences as per a universal moral grammar should be an equally developmentally demanding task.

How to maximise your bets : become a schizophrenic or damage your amygdala, the orbitofrontal cortex, or the right insular cortex!

A couple of recent news articles on neuroeconomics, lead to some surprising insights regarding how addictions like Gambling could be self-addictive and how some specific neurological malfunctioning may lead to people fairing better in games of chances and making more ‘rational’ gambles.

The first article in the New Scientist refers to a recent research by Chris Frith et al at University College London, UK in which the authors found that people who had been given dopamine agonists (like L-DOPA) were able to determine the winning strategy involved in a gambling game early then those who were given placebo. The study contained choosing symbols – some of whom were associated with large chances of winning, while others were associated with average chances and still others were associated with financial penalties and should ideally be learned as avoidable symbols.

What they found was that dopamine facilitated the early learning of the symbols that were associated with (monetary) winning outcomes or rewards as compared to controls, but had no effect on the learning of the avoiding or punishment symbols. This, they hypothesize is due to the fact that people get a Dopamine surge whenever ‘rewarded’ and when base dopamine levels are high (it has already been administered prior to the betting game) this leads to greater strength of dopamine reward signal , thus leading to faster learning of the winning strategy. The fact that dopamine does not affect the learning of negative outcomes, confirms that the effect selective and due to the ‘rewarding’ nature of dopamine as opposed to a general improvement in learning due to dopamine administration.

The participants played a computer game in which they were repeatedly shown pairs of unmatched symbols, and had to choose one or the other without being told anything about them beforehand.

Unknown to the participants, one symbol gave them an 80% higher chance of winning £1, whereas another symbol gave them only a 20% higher chance of winning. Other symbols incurred financial penalties.

The volunteers on dopamine prospered because they identified the winning symbols faster than the haloperidol treated patients. And the winning effect was more pronounced if they actually received money in the study.

The dopamine recipients only noticed winning symbols, however. The chemical did not appear to alert recipients to “losing” symbols.

Learning from losing is controlled by other chemicals in the brain, the most dominant probably being serotonin, a chemical linked with depression, Frith concludes.

This brings up some interesting scenarios. If one has started gambling somehow, then as one keeps gambling further, the successive wins would generate more and more dopamine surges (as baseline dopamine increases after a few wins), the gambler would start identifying the winning patterns, and the strength of winning patterns and rewards associated with them would continue to get stronger in the gambler’s mind; there would be no corresponding effect on the learning of negative or losing strategies by him and consequently his learning would be skewed in such a way that winning outcomes would be disproportionately perceived as being rewarding as compared to the losing outcomes – thus in the gamblers mind loses are processed in a ‘normal’ way ; but wins or winning strategies are perceived differently in the sense that they would be learned more strongly, earlier and more persistently – as each win would result in more and more dopamine surge and thus skew the learning in favor of the winning strategy more and more. this is a vicious circle- the gambler is getting more and more dopamine surge and is also becoming better and better at identifying the winning strategies- thus its difficult to convince him otherwise that he is gambling in vain- what he doesn’t realize that he is not attaching a corresponding increased negative outcome to losses or is learning the losing strategies also at the same rate.

The other article is a good review of the field of neuroeconomics in the New Yorker. It touches on many current issues in neuroeconomics, but what is most relevant to us here is the concept of loss aversion, whereby people perceive losses of what they already have as more aversive than a wasted chance of making an equivalent or more gain. To paraphrase from the article:

If you present people with an even chance of winning a hundred and fifty dollars or losing a hundred dollars, most refuse the gamble, even though it is to their advantage to accept it: if you multiply the odds of winning—fifty per cent—times a hundred and fifty dollars, minus the odds of losing—also fifty per cent—times a hundred dollars, you end up with a gain of twenty-five dollars. If you accepted this bet ten times in a row, you could expect to gain two hundred and fifty dollars. But, when people are presented with it once, a prospective return of a hundred and fifty dollars isn’t enough to compensate them for a possible loss of a hundred dollars. In fact, most people won’t accept the gamble unless the winning stake is raised to two hundred dollars.

Further, the article notes that this loss aversion is due to the fact that under ambiguous situations (or situations that involve probabilistic estimates in face of incomplete information to make the probabilistic judgments), our ’emotional’ brain takes precedence over the ‘rational’ brain and prevents us from making ‘rational’ decisions.

In one study, Camerer and several colleagues performed brain scans on a group of volunteers while they placed bets on whether the next card drawn from a deck would be red or black. In an initial set of trials, the players were told how many red cards and black cards were in the deck, so that they could calculate the probability of the next card’s being a certain color. Then a second set of trials was held, in which the participants were told only the total number of cards in the deck.

The first scenario corresponds to the theoretical ideal: investors facing a set of known risks. The second setup was more like the real world: the players knew something about what might happen, but not very much. As the researchers expected, the players’ brains reacted to the two scenarios differently. With less information to go on, the players exhibited substantially more activity in the amygdala and in the orbitofrontal cortex, which is believed to modulate activity in the amygdala. “The brain doesn’t like ambiguous situations,” Camerer said to me. “When it can’t figure out what is happening, the amygdala transmits fear to the orbitofrontal cortex.”

The results of the experiment suggested that when people are confronted with ambiguity their emotions can overpower their reasoning, leading them to reject risky propositions. This raises the intriguing possibility that people who are less fearful than others might make better investors, which is precisely what George Loewenstein and four other researchers found when they carried out a series of experiments with a group of patients who had suffered brain damage.

Further, the article notes that people with orbitofrontal, right insular or amygdala damage, are less fearful or are less able to integrate the fearful or ’emotional’ response of the brain and are thus able to make decisions that are more risky then their normal counterparts. Thus, the counterintuitive conclusion that damages to these areas may make one a better investor/ gambler etc.

Each of the patients had a lesion in one of three regions of the brain that are central to the processing of emotions: the amygdala, the orbitofrontal cortex, or the right insular cortex. The researchers presented the patients with a series of fifty-fifty gambles, in which they stood to win a dollar-fifty or lose a dollar. This is the type of gamble that people often reject, owing to loss aversion, but the patients with lesions accepted the bets more than eighty per cent of the time, and they ended up making significantly more money than a control group made up of people who had no brain damage. “Clearly, having frontal damage undermines the over-all quality of decision-making,” Loewenstein, Camerer, and Drazen Prelec, a psychologist at M.I.T.’s Sloan School of Management, wrote in the March, 2005, issue of the Journal of Economic Literature. “But there are situations in which frontal damage can result in superior decisions.”

If we club the two studies together, one may come to a surprising conclusion that to become a good speculative investor or gambler you may need to temporarily knock out your parts of the brain involved in emotional decision making (one may use TMS here) and also additionally take a dopamine does to learn the rewarding strategies and actions early on. This may be the only way for us to counter the tyranny of loss aversion that nature has imposed on us and move towards that ideal of Homo Economicus.