Tough Decision Making

Every person’s life can be broken down into the decisions that they make. Decisions can range from easy ones, like stopping by the gas station before driving into work, to the hard ones like waking up at the first alarm or snoozing for a couple more minutes, or to the seemingly impossible decision of choosing which restaurant to have dinner at. Though these choices can vary in difficulty, timing, emotional weight, and consequences, popular theories of decision making propose two opposing systems compete to make choices. One system is affective, fast, and typically autonomic while the other is slow and deliberative. With the growing scientific evidence on the complexity of the structure and function of the brain, it is unlikely that there are distinct neural circuits that coincide with these predominant dual-process theories, and that the true nature of how decisions are made is much more dynamic and flexible.

Many decisions occur without conscious approval. One such decision is where and when to move one’s eyes. While reading this sentence, your eyes move in a saccade motion from point to point. According to single cell recordings done by Meister, Hennig, and Huk on rhesus monkeys, this  unconscious decision to move from one focus point to the next results in part by the integration of signals in the lateral intraparietal region. This area performs the complex integration of decision signals with visual information from association areas. The resolution of this brain region suggests that a broader scoped region then receives this integrated information to make the actual decision. This experiment showed that a quick, autonomic decision can be made through a complex integration without any affective circuitry.

Brain imaging studies show significant overlap in brain regions involved in conscious decision making. The dual process theory states that while the two ways to make decisions may compete with each other, they should be distinct. However, many areas of the brain seem to be involved both in the affective system and the deliberative system. The insula especially shows a cross over in function. Countless studies have shown the insula’s function in interoception, and it’s contributions to the ventral striatum during emotional decision making. However, as seen in Philiastides and Sajda’s fMRI study, the insula is also active during difficult decisions requiring more deliberative processes as well.

The dual process theory acts as a proficient generalization of the complex decision making process. But maybe decision making should be thought of as a gradient, not two competing processes. A decision is theorized to be made when a threshold is reached, whether that be in the ventral striatum or in refutable association cortices. Emotions tend to have strong ties to incoming sensory information, and therefore contribute quickly to the decision making process. As time progresses, however, additional regions of the brain are recruited (Philiastides et al.). So the recruitment of more and more functional regions allows this threshold to be reached. Maybe the deliberative method is only the continuation of the decision making process that starts with the most salient memory information we have, and proceeding up to the higher cognitive functions that take broader information into account.

There are some limitations that occur when studying the temporal structure of decision making. The most common brain imaging procedure, fMRI, does not have the temporal resolution to fully study this idea. EEG data does have this ability, but lacks the spatial resolution to map the brain activity to specific regions. However, combinations of the two coupled with creative experimental procedures may shine a light on not only the nature of the central decision-making region of the brain, but also the recruitment of different brain regions over time.

 

References:

Philiastides, Marios G., & Sajda, Paul. (2007) EEG-Informed fMRI Reveals Spatiotemporal Characteristics of Perceptual Decision Making. The Journal of Neuroscience, 27(48), 13082-13091. retrieved from http://www.jneurosci.org/content/27/48/13082.full.pdf+html?sid=6b692f84-4648-4fb8-a47c-08ada1b47bee

Philiastides, Marios G., Sajda, Paul, & Ratcliff, Roger. (2006) Neural Representation of Task Difficulty and Decision Making during Perceptual Categorization: A Timing Diagram. The Journal of Neuroscience, 26(35), 8965-8975. Retrieved from http://www.jneurosci.org/content/26/35/8965.full.pdf+html?sid=6b692f84-4648-4fb8-a47c-08ada1b47bee

Miriam L. R. Meister, Jay A. Hennig, and Alexander C. Huk. (2013) Signal Multiplexing and Single-Neuron Computations in Lateral Intraparietal Area During Decision-Making. The Journal of Neuroscience, 33(6), 2254-2267. retrieved from http://www.jneurosci.org/content/33/6/2254.full.pdf+html?sid=409ee253-8233-4125-bd02-b48ad6a7b155

Alan N. Hampton, Peter Bossaerts, and John P. O’Doherty. (2006) The Role of the Ventromedial Prefrontal Cortex in Abstract State-Based Inference during Decision Making in Humans. The Journal of Neuroscience, 26(32), 8360-8367. retrieved from http://www.jneurosci.org/content/26/32/8360.full.pdf+html?sid=6b692f84-4648-4fb8-a47c-08ada1b47bee

Thielscher, Axel, & Pessoa, Luiz. (2007) Neural Correlates of Perceptual Choice and Decision Making during Fear-Disgust Discrimination. The Journal of Neuroscience, 27(11), 2908-2917. retrieved from http://www.jneurosci.org/content/27/11/2908.full.pdf+html?sid=6b692f84-4648-4fb8-a47c-08ada1b47bee

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