How We Decide What We Decide

How We Decide What We Decide

    We make decisions thousands of times a day. Most of the time, we never stop to wonder how we came to this decision, what influences our decision-making, or where the decision is actually being processed within our brains. Many scientific studies have researched where in the brain there is activation when a decision is being made or thought about. These findings have greatly revealed answers to actions in the brain that affect the majority of everyone’s day.

There are different types of decisions that can be made. One of those types of decisions is a value decision. A value decision takes information about the choices available and quantifies which option would provide the maximum positive outcome. Different styles of decision making has the potential to be coded in the brain using different processes or even different parts of the brain entirely. A group of researchers in San Diego looked into this area of neuroscience, to better understand this specific type of decision making and what areas of the brain are associated with this process.  Reinforcement learning is the behavior that was used to optimize the value decision making in mice and the corresponding brain activity linked to those tasks were recorded and analyzed by the researchers. 

The results of this study went on to be discovered as finding a large quantity of brain activity in the cerebrum but more specifically the retrosplenial cortex within the cerebrum. These findings create the inference that value information is stored and potentially coded in this area of the mouse’s brain, and can open the door to future studies that look into how brain injuries of this area affect value decision-making, or how the different areas involved in different types of decision making code and process information differently, and how that affects the outcomes of each type of decision making. Current research furthering these results, by the same researchers is working to shift the findings into compatible AI programs to detect patterns of processing networks and codes.

Thorsten Kant and Fang Wang similarly studied decision-making, but more specifically inference-based decision-making. While this is a different type of decision making than what the Hattori and Komiyama study analyzed, understanding multiple types of decision-making allows for the differences and understanding of all types of decision-making in the brain. This study again took a specific type of decision making and optimized it into a recordable behavior that is associated with activating brain activity. The results of this study pointed towards a different area of the brain working to process and code decision-making when it is inference-based. The orbitofrontal cortex (OFC) lit up with activity when intentional behaviors produce these types of decision making ideas in a participant’s head. These results led to inferences that the OFC is central across many species in the process of coding inference-based decision making.

If future research continues following the paths of all forms of decision-making, soon it could be known why the brain has created such specific paths for each form and how each pathway is best fit for decision-making. The understanding of how other species' brains conduct these behaviors also can lead us to better understand the human brian and how similar or dissimilar it is to other species typically studied in neuroscience. Once we can pinpoint individual directions of decision-making pathways, focus can shift to how best to amplify those pathways when they are faced with obstacles, like mental illness, physical injury, or a cognitive disability. The opportunity to change lives by understanding our brain and why it works the way it does, is a motivation that hopefully future researchers keep deciding to pursue.

References:

Wang, F., & Kahnt, T. (2021). Neural circuits for inference-based decision-making. Current Opinion in Behavioral Sciences, 41, 10–14. https://doi.org/10.1016/j.cobeha.2021.02.004 

Hattori, R., & Komiyama, T. (2021). Context-dependent persistency as a coding mechanism for robust and widely distributed value coding. Neuron. https://doi.org/10.1016/j.neuron.2021.11.001