Critical Evaluation of McGuire and Botvinick's Study - Article Example

Critical Evaluation of McGuire and Botvinick’s Study Critical Evaluation of McGuire and Botvinick’s Study Introduction The study has critically examined the connection between decision-making processes and cognitive responds by different human characters (McGuire & Botvinick, 2010). It has provided an in-depth basis on human choice behavior based on the internal decision costs. The basis of the study is to provide comprehension on the relationship of decision costs and that affect making of rational decisions. It has carried out experiments that provide knowledge on different human character and their response on demanding situations to make decisions. With the help of the other three articles, the study has highlighted theories from different scholars that support human behavioral changes. Internal and external factors affect the making of choices. The study has exposed internal factors that affect ways of making choices. Objective of the Article The article emphasizes in the human choice behavior and its effect on making rational decisions. Intensive information processing requires differentiated internal costs (McGuire & Botvinick, 2010). This principle means that in order to make deter decisions, the brain will require advanced cognitive and response efforts. Decision makers have to balance motives to ensure minimal decision costs. The article provides more information on the cost-benefit analysis of decision-making. It has used simple decisions to help the reader comprehend various responses. Clinical depressions can be caused by increased decision cost in an individual. This is the reason why most decision makers prefer the minimizing demands to increase the working memory. What the study has done The study has carried out various experiments to prove the hypothesis that tasks configurations and other made decision depend on the costs. It has also highlighted neural mechanisms that contribute to costs of decision-making. During the investments, costs are evaluated through various degrees of engagement based on the brain regions (McGuire & Botvinick, 2010). Sections of the brain include the dorsomedial frontal cortex and the lateral prefrontal cortex. The experiments test the activities in administrative control-related brain section. Measurements are done through the applicant’s tendency to avoid any demanding task allocated to him/her. The research takes into account external factors leading to controlled environments. Methods used The study has used laboratory testing methods that have included 12 participants to document costs incurred during decision-making in selected tasks (McGuire & Botvinick, 2010). The tests include changing of trials frequently that require executive control. Assumptions are that the participants will choose less demanding tasks. Its effects will be recorded on different parts of the brain that will be investigated for any activities. The participants were Princeton University Members aged 18-22 in the second experiment and 18-34 in the first experiment. Programming of the behavioral test was done using E-prime that was obtained from Psychology Software Tools Inc. (McGuire & Botvinick, 2010). The choice signal appeared to the participants as a patch of to reveal colored numbers using a computer. Each participant was to complete 75 trails where he/she would respond through use of the left hand. The time interval between the switches was 250ms, but individual choices were self-placed. Angles of 45 degrees separated the choice cues. Mouse pointers were strategically placed in the middle of two tests. Experiment 1 It presents reports of participant-experienced decision costs. All participants registered a yearning to perform less demanding tasks. The costs were measured in the registered desire to avoid the allocated tasks. They were issued with ten trial blocks in which they were to make simple decisions in an assignment switching model. The participants were informed about each specific stimulus sequence that they would register. The sequence on the brain regions was measured in undisclosed algorithms. Rating of these blocks was done individually to prevent the participant from predicting future talks. Assumptions It was assumed that endogenous variability in brain action was generated using a uniform procedure. Brain activity varied in the basis of age and neural conditions in the brain. The procedure could be uniform but electrical signatures in the brain could vary. The ratings were set to reflect similar internal factors affecting the behaviors of the participants. The internal factors included neural mechanisms and body health. For example, anxiety would affect the neural processes that register impacts on choices made. Brain activity and avoidance ratings depend on the reaction time rating and the errors that have been put into account. Constants such as time taken and brain activity have been catered for to reduce error margins. Avoidance ratings were signatures to show that participants avoided decisions that required much thinking. Experiment 2 This test examined the significance of the LPFC on the impact of decision costs. Measurements are through observation of the avoidance behavior. Participants were exposed to low and high tasks. The MRI scanner was used to monitor brain activity. The experiments are different in both cognitive demand and mental efforts. These scientific methods are capable of measuring brain activities that act as responses to various motivations. Assumptions Variation of decision costs depended on the time factors and individual characters. Time was varied depending of the task offered to the participant. Time taken to monitor the cost to a choice was also monitored and computed with the constant value. It has held other determinants constant such as economic, political, and behavioral disorders that may affect the choices participants make. These factors cause changes in neural signatures due to depression. Disorders also cause distortion in neural mechanisms in the brain. A constant factor was used to ensure all determinants have been catered for in the results. Results Positive correlations were observed in participants between the provided ratings. The average rate (r) was at 0.5 and a constant time of (t) 9 (McGuire & Botvinick, 2010). The mean error rate was 3.2%. The results show that the participants have minimized internal decision costs. The research has helped solve the effect of these costs on made choices at a neural level. They have also identified a relationship between the activities on the left LPFC and the decision costs. The activities together with self-reported avoidance tendency have a direct effect on the choices made by the participant. The second experiment has visually observed the avoidance rates across the participants. There are cases cognitively demanding decisions have led to performance differences. Errors and slow RTs have also affected the operation decision costs. The results have also helped identify the fact that LPTC activities are directly affected by the RT. The brain has a constellation of recognizing past decision leading to similar internal costs that have impacts on the decision-making processes. The LPFC region has special roles that prevent fluctuation in the analyzing of choice costs. The DMFC on the other hand accounts for over performance in the relationship between costs and choices made. It is also highly activated for task switching between the cues. Demands of the decisions also affect the rate of internal cost choices (McGuire & Botvinick, 2010). Its roles include information processing, efficiency, and monitoring outcomes of the decisions. Discussion in light of other 3 studies Article 1 ‘The timing of exploratory decision-making revealed by single-trial topographic EEG analyses’ It has highlighted on two core factors that affect decision making (Tzovara, Murray, Bourdaud, Chavarriage Millan and Lucia, 2012). They include the exploration of different environments to gather knowledge and exploiting of the data to maximize chances of reward. Functional magnetic resonance imaging has helped in the study of exploratory decision-making. The study revolves around the two principles where their decisions are made in uncertain environments. It has also been based on situations where an individual is offered different rewards to show the way he/she makes decisions. Procedures and tasks are similar to the main study where students use computers to show up different choices. The study first includes stages where the participants are offered time to explore and gather data on the situation he/she is exposed. They are later issued with a short time to conceptualize and then presented with the computers. The exploration helps in gathering knowledge that includes various rewards that were to be offered if the right choices were made at the slots. Scanning was also done while the participants were performing their choices to record brain activity (Tzovara, Murray, Bourdaud, Chavarriage Millan and Lucia, 2012). Through the use of behavioral models and single trial analysis, the participants were closely monitored to study the brain activities. The TANOVA analysis was used to show differences in brain activity during exploration and exploitation. The cognitive tasks differences have different values of risk-taking situation that reduce the probability of receiving rewards. In relation to the main study, the article has highlighted internal and external factors. Externally, the participant is affected by topography values to make internal decisions. The rewards are also used to show the variances in behavioral changes among individuals. Internally, the exploitation of the perceived thoughts and sceneries help the individual to make decisions. It affects the time taken by participants to make decisions. The results through typical time latencies are able to accurately predict an individual’s choice. Reward evaluation can be used to predict subsequent decision by monitoring EEG Topography. Article 2 ‘How the brain integrates costs and benefits during decision-making’ This article provides knowledge on the understanding of decision-making procedures based on the brains ability to integrate benefits and costs that arise (Basten, Biele, Heekeren and Fiebach, 2010). Unlike the main study that focuses on costs, this article emphasizes on both costs and benefits. Humans have various tendencies that contribute to the choices they make. Behavioral and cognitive approaches have been used to understand these propensities (Basten, Biele, Heekeren and Fiebach, 2010). However, the article has exposed other modes of electrical studies of the brain activity. Choice modeling and functional magnetic resonance imaging have been used to study the effects of benefits and costs of the human thinking perception. To present sufficient knowledge from both cortexes, the Model driven functional MRI is used to monitor neural signatures that represent the situation of benefits and cost rewards to the brain. It is known that benefits represent situations that require less stress. The brain seems to weigh the impact of the issued task on whether it has a reward or need more effort to accomplish. Where situations do not have presentable rewards, costs are more than benefits leading to a negative response (Basten, Biele, Heekeren and Fiebach, 2010). For example, unfriendly situations may lead to making decisions that affect thinking processes. It is evident in cases of depression that takes place where the cost-benefit analysis has an imbalance. Experiments have 19 participants who are exposed to single visual stimuli that that consist of colors and shapes. Stimulus-associated benefits are compared against stimulus-associated costs. The results prove that the participants were able to learn stimulus-reward association through analysis from a variety of models. Results have been presented through graphs that represent average brain activity. In relation to the main article, the study has used neural signatures to decode decision related rewards and losses (Basten, Biele, Heekeren and Fiebach, 2010). Observation of the parietal cortex through neural imaging provides a strong hypothesis on the integration of costs and benefits towards decision-making procedures. However, the analysis of the two principles depends on other factors such as age and behavioral disorders. For example, there are disorders that may lead an individual to make a choice despite the costs presented on the brain. Article 3 ‘Decision Making and the Avoidance of Cognitive Demand’ It focuses on cognitive demand as the driving factor for decision-making procedures. Unlike the other studies that have come up with the ‘law of less work’, avoidance of cognitive demand exposes the effect of controlled information processing on individual choices. Judgment made depend on the avoidance of errors, maximization of reward or goal achievement and the minimization of time used on perpetration of an act. The study has shown that these factors have both positive and negative effects on the decision made. According to the experiments, avoidance of demand had direct effects on the task incentives. Cognitive demand plays a responsibility in behavioral decision making. The study has used knowledge from the main article that suggest human make decision that require least mental effort. The decision-making process is continuous and has to integrate with current environments to provide valid choices. Its six experiments carried out analysis to validate switch manipulation strategies based on verbal and visual features. With constant observation on all participants, the study revealed the need for cognitive demand in decision making. However, the study also works on the principle of low mental effort to help in fast decisions. Limitations and shortcomings and how they can be avoided The cognitive demand styles can vary based on individual principles. They can present different thinking and conceptual responses. Unlike the cost and benefit driven theories, cognitive demand has different values. In some cases, the cognitive demand may not have an effect on the behavioral aspects of individuals leading to different decisions. In the law of less work, there are misunderstandings that come up due to various situational behaviorisms. For example, one may make decisions based on rewards. However, the rewards may require more mental and physical effort to be accomplished. This condition causes a conflict on the cost-benefit analysis and the reward response system. The study has taken into account internal factors only. Its psychoanalysis depends on brain activity on specific regions. However, it does not focus on other determinants such as inborn or acquired behavioral changes. It does not also focus on disorder such as autism that affects the brain activity in the study regions. Conclusion The articles have supplied sufficient knowledge on the process of decision-making in humans. Neural studies have shown brain activity in various sections to ensure rapid decisions. However, all studies have revealed that time is a key factor in making rational decisions. References Basten, U., Biele, G., Heekeren, H. R., & Fiebach, C. J. (2010). How the brain integrates costs and benefits during decision making. Proceedings of the National Academy of Sciences, 107(50), 21767-21772. Kool, W., McGuire, J. T., Rosen, Z. B., & Botvinick, M. M. (2010). Decision Making And The Avoidance Of Cognitive Demand.. Journal of Experimental Psychology: General, 139(4), 665-682. McGuire, J., & Botvinick, M. (2010). Prefrontal cortex, cognitive control, and the registration of decision costs. Proceedings of the National Academy of Sciences, 107(17), 7922--7926. Tzovara, A., Murray, M. M., Bourdaud, N., Chavarriaga, R., Millan, J. D., & Lucia, M. D. (2012). The timing of exploratory decision-making revealed by single-trial topographic EEGanalyses. NeuroImage, 60(4), 1959-1969. Read More