Can Humans Multitask Effectively? Research on Brain Processes - Essay Sample

Introduction

The researcher’s big question in the research project is the ability of humans to multitask. Identified as people’s everyday ability to change between tasks frequently, the researchers address how the brain handles multiple tasks at the same time and the effects that result. The research identifies the process as the reconfiguring of mental processes to meet the changes in tasks. The example offered is that of a professor sitting in front of his computer writing a paper, then the administrator demands for a form that is in his passion (Monsell, 2003). As the form is taken to the administration office, the professor exchanges greetings with his colleagues. Each of the events identified requires the brain to switch between tasks and resources utilized to meet the current objective (Monsell, 2003). For example, the first objective was to complete the paper, but it was disrupted by another task receiving the phone call from the administration.

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The specific question being asked by the researchers is based on how the brain can switch between tasks and the efficacy of the process. The primary hypothesis developed by the researchers from data collected is that each stimulus or task requires attention and classification for the brain to compute the different properties. However, the research discovered that the brain could be trained to switch between tasks with minimal losses in switching costs and residual cost (Monsell, 2003). The preparation effect also affects the efficacy of the brain when switching between tasks. The research was able to analyze the functioning of the brain but, at the basic level identifying the various factors that affect it.

From the basic understanding of task switching the Monsell (2003) acknowledged that the average subject is first able to address two or more simple tasks presented by a set of stimuli. Moreover, tasks in all cases alter from one problem to another, and in some cases, they do not. The purpose of the research is to examine the brain’s activation or performance when tasks change, searching for evidence of extra processing demands. The notion is based on the first hypothesis that switch cost, the time penalty required for switching tasks, lessens with repetition. Additionally, the preparation effect and the provision of time to prepare contribute to the reduction of switch cost. For example, mothers are well adopted in taking care of infants a few weeks after birth compared to being introduced, caring for different infants daily. The alternative hypothesis introduces a new aspect to the notion. The first is residual costs, which states that preparation effect does not wholly eliminate switch cost. Moreover, responses will remain slower on multiple tasks than single tasks, hence the term mixing cost. According to the second hypothesis, the brain can always improve its switching speed, as stated in the first hypothesis. However, the response speed may affect multiple tasks switching. It requires the consideration of numerous factors, not only the switching cost but also the effects of the stimuli. The process is highly random, as even task-cueing is ineffective due to the unpredictive nature.

From the perspective of Monsell (2003), task switching is improved with repetition as well as preparation effect. However, when it comes to multiple tasks switching, the randomness is introduced significantly affecting the process. Therefore, the research was designed to understand how predictability and unpredictability affect task switching. Both factors are affected by the four identified phenomena switch cost preparation effect residual cost and mixing cost. Numerous medical and psychological advances can be attained by comprehending the effects of the phenomena on predictability and unpredictability in task switching.

Methods

For better comprehension of how task switching is affected by the stated phenomena, data was collected from secondary sources. Mostly from research by other researchers over the topic. The limitations of the approach included the reliance on large sums of research data, considering the researcher wanted to understand the time taken by control operations, associative retrieval, and their combined effect. Nevertheless, from the research Monsell (2003) identified that TSR (task-set reconfiguration) as the main controlling factor determining the switching cost when handling different tasks. Moreover, the process can be controlled to some extent by internally initiating the process before the stimuli’s onset. However, further research resulted in numerous theories that attempted to explain TSR. Among them was the notion that TSR can be positively affected by the repetition of tasks, thereby making the engagement of the task shorter. It directly supports the notion that predictability can effectively reduce switching costs. However, the notion is refuted by other research hypotheses, which introduce another aspect of the process. Allport et al. (1994) proposed, for the brain to switch tasks, it has to apply extra restrain towards tasks with substantial familiarity to engage in weaker tasks. The process of overcoming the familiarity of the stronger task prolongs the response, thereby increasing switching costs.

The new paradigm introduced a new problem in which switch cost does not just involve one mechanism. Though single-task models are gaining popularity when attempting to explain the brain’s task switching process, most scientists acknowledge a multitude of causes. The outcome is more data supporting the notion of unpredictability when it comes to addressing switching costs. The data collected created the notion that long-term priming for tasks activates TSR with small sets of stimuli. However, with the introduction of new tasks after completing the previous creates uncertainty on the switching cost. The notion was supported by data identifying that residual switch costs were present even with univalent stimuli. It was considered interesting considering that in single stimuli tasks, there is associative competition. Additional data collected from Hunt and Klein (2002) identified that with bivalent stimuli, switching costs did not occur in some cases proposing a concept of the process based on the data.

Results

Transient carry-over of task-set activation or inhibition are the main factors that affect switching cost and residual cost with an emphasis on the latter. However, it is still unclear if the effects are predominant towards response selection or trigger for the extra control over the switching process. The most probable occurrence, according to Monsell (2003), is the combination of both suggestions.

Discussion

The research was initially based on the notion that predictability and unpredictability were the main contributors to switching costs. Predictability was based on the hypothesis that with univalent stimuli, the brain would switch between tasks with minimal to no switching cost. However, the hypotheses supporting the notion of unpredictability offered more supporting information. The first hypothesis lacks numerous considerations that were accounted for in the second proposition. Therefore, unpredictability affects task switching, as numerous factors have to be considered. All summed under transient carry-over of task-set activation or inhibition, it offers the best explanation to the effects of both external and internal factors on task switching. However, as initially stated, further research is required due to the limitations presented by the study. The current results attained were based on the data used for the research. However, other researchers offer compelling arguments that further complicate the comprehension of the process. Among them was a study conducted by Goschke (2000), where he stated that the reduction of switching cost offered by a preparation interval was negated with verbalism. It introduces the notion that verbal interactions adversely affects the switching cost between tasks. It only represents one of the numerous issues yet to be solved.

Among the numerous questions yet to be answered include the reasoning of the puzzling observations made by numerous researchers. It has been identified by numerous recreations of the study that preparation often reduces switching cost without having any effect on verbal interactions or the Stroop-like intervention. Additionally, switching costs are higher when the response to the task is similar to the previous objective. Therefore, increasing the set of variables further complicates the issue and increases unpredictability to the research. Overall, the process of understanding the task switching process of the brain is yet to be completed due to the increasing complexity of the process.

References

Hunt, A., & Klein, R. (2002). Eliminating the cost of task set reconfiguration. Memory & Cognition, 30(4), 529-539. doi: 10.3758/bf03194954

Monsell, S. (2003). Task switching. Trends In Cognitive Sciences, 7(3), 134-140. doi: 10.1016/s1364-6613(03)00028-7

Monsell, S., & Driver, J. (2000). Control of cognitive processes. Cambridge, MA: The MIT Press.