Research paper: Testing the Brain’s Decision-Making Process In Humans

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Underlying mechanisms of confidence and decision-making

Our data showed that anxiety and confidence have an important role in decision-making. The self-report of the amount of effort required to solve a problem doesn’t seem to have a big effect on decision-making. However our experiment showed a positive correlation (significant in almost – but not all cases) between effort and anxiety as demonstrated in table 1 and 2.  These results lead to the following questions: How is the brain making this decision? What cognitive processes are involved when the brain is  assessing to avoid or engage with a task? What specific areas of the brain are responsible for the decision-making?

A literature review of visual confidence in humans looks at the evidence related to the anatomical brain structures that might possibly be responsible for confidence and decision-making (Grimaldi., at al. 2015). Some of the experimental evidence in this review paper supports the hypothesis that confidence and decision-making are encoded in the same brain areas such as: the lateral intraparietal (LIP) area and superior colliculus. Other experimental evidence supports the hypothesis that confidence is performed by specialized circuits including the prefrontal cortex. This controversy might be due to the fact that  the experiments and studies were focusing mostly in the decision-making circuits when they also found information about the confidence, but as Grimaldi., at al 2005, argue is that this doesn’t necessarily mean that’s where the confidence is ultimately generated. They propose future research where imaging studies in humans and non-humans can translate to electrophysiological experiments which might help to understand how the brain encodes confidence.

Another literature review investigates the locus coeruleus-norepinephrine (LC-NE) system which recently has been found to play a specific role in behavior and decision-making(Aston-Jones & Cohen, D. J. 2005). This system is one of the several brain-stem neuromodulatory nuclei that regulates cortical functions (Aston-Jones & Cohen, D. J. 2005). The modeling studies in monkeys showed that the LC system consists of two modes: phasic and tonic. In the phasic mode, NE is quickly released and there is an increase in attentiveness to the task relevant which increased task performance. On the other hand, during the tonic mode the neurons are less excited, and the behavior is more distractable. Monkeys were responding more to the nontarget stimuli at this time which decreased the task performance. Aston-Jones & Cohen, D. J. 2005’theory of Locus Coeruleus -Norepinephrine proposes that the phasic mode optimizes task performances versus the tonic mode favors exploration. This happens due to the evaluation of the benefits and costs where there is an increasing evidence suggesting that the anterior cingulate (ACC) and the orbitofrontal cortices (OFC) play an important role in this evaluation (Aston-Jones & Cohen, D. J. 2005). One of the limitations of the study they reported was its inclusion  of animals only.

In real life, the switching between these two modes is important because it allows us to focus on relevant tasks but also to explore our environment, so we don’t miss out on opportunities that can change our life for the better. However, when it comes to learning and focusing while in the classroom, the tonic phase would be costly for students. The LC activity – is, however,-  adaptive and changes in the teaching methods and rewards might help to encourage both modes in students. This would allow them to engage in both effortful and effortless tasks.

Limitations and future research

Since we didn’t look at performance, continuing research and experiments can be done to look at the relationship between performance, anxiety, and effort. Our study had some limitations including conducting it online. It has been reported that environment plays an important role in students’ behavior and thinking, (Closs, L., Mahat, M. & Imms, W 2021) but due to the restrictions of the pandemic, for safety reasons we conducted the experiment online.  Another limitation is the language. We didn’t ask if English was the participant’s native language. It is possible that had an effect on the decision to choose the reading and comprehension task. Also, our scale for rating and measuring anxiety, effort, and confidence must be validated.

If the experiments were to be done in person or in classroom environment, it could be expanded by adding a second part where students instead of choosing the cognitive tasks they want, would be given a task that would most likely avoid. We could then look at their performance and measure their level of anxiety and their attention. We cannot always choose what we want or how we want to feel in life, so this could help us understand the behavior and the performance of students when facing academic challenges, they may want to avoid.

   References

Aston-Jones & Cohen, D. J. (2005). An Integrative Theory of Locus Coeruleus-Norepinephrine Function: Adaptive Gain and Optimal Performance.  Annual Review Neuroscience, 28, 403-50.

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Closs, L., Mahat, M. & Imms, W. Learning environments’ influence on students’ learning experience in an Australian Faculty of Business and Economics. Learning Environ Res (2021).

Grimaldi, P., Lau, H., & Basso, A. M. (2015). There are things that we know, and there are things that we don’t know we do not know: Confidence in decision-making. Neuroscience&Biobehavioral Reviews. 55, 88-97.

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Teman, E. D. (2013). A Rasch Analysis of the Statistical Anxiety Rating Scale. Journal of Applied Measurement, 14 (4), 414-434.

Székely, M., Michael, J, (2020). The Sense of Effort: A Cost-Benefit Theory of Phenomenology of Mental Effort. Rev.Phil.Psych. 

Shiffrin, M. R., Schneider, W. (1977).Controlled and Automatic Human Information Processing: II Perceptual learning, automatic Attending and a General Theory. Psychological Review, 84: 127-190.