Sleep plays an instrumental role in consolidating motor memory and overall learning. According to Johnson et al. (2019), sleep improves training and rehabilitation through non-rapid eye movement throughout the night or during a nap. Various methods have proven helpful in enhancing the process of training and rehabilitation during sleep. Targeted Memory Reactivation, TMR, is one such method. It involves combining external cues with the performance of tasks during initial motor skills acquisition and replaying the same external signal when an individual sleeps (Johnson et al., 2019). TMR process hypothesizes that aligning the initial motor skills improves task and behavioral performance in different age groups. Paller, Creery & Schechtman (2021) defined TMR as a method memory reactivation probing technique that involves unobtrusive presentation of learning cues during sleep, which biases and consolidates the memories, hence facilitating learning. While the TMR method has been applied in testing whether sleep improves behavioral and task performance, new applications of the model have emerged, seeking to establish whether the process can enhance learning a new language. Research evidence suggests that sleep enhances memory consolidation (Rasch et al., 2007). Researchers use TMR as a methodology for manipulating memory processing during sleep (Hu et al., 2018). Establishing whether TMR is applicable in language learning is critical in expanding the scope of its application in psychology.
Another paradigm that has proven helpful in improving motor skills, task performance, and behavior through sleep is the Naturalistic Longitudinal Observation, NLO. This methodology involves observing participants in their natural settings to determine their behaviors without any intervention (Erdley & Jankowski, 2020). NLO methodologies enable researchers to measure and determine participants’ natural level of performance towards a task, which is critical in assessing the performance of the same job with an intervention. Therefore, naturalistic longitudinal observation provides essential baseline data for comparison when measuring the effectiveness of an intervention. According to Cherry (2019), the naturalistic longitudinal approach is a critical research methodology that allows practitioners to gather invaluable insights regarding participants’ performances and reactions in real-world contexts and compare the results with the respondents’ performances with empirical evidence interventions. While researchers are likely to overlook NLO as a research methodology because it does not involve integrating interventions, the method offers crucial insights for determining the effectiveness of these interventions.
Contributions and Limitations of Targeted Memory Reactivation
TMR has substantial contributions to psychology, particularly in investigating the relationship between sleep and psychological concepts such as cognition. One of the significant contributions of TMR as a methodology is that it provides high ecological validity, which is a measure of the ability of test performances to determine real-world behavior (Sanders et al., 2019). Therefore, tests conducted using the TMR methodology are generalizable to the target population that exhibits similar characteristics as the test subjects, although outside the test environment. Since TMR is an experimental study involving interventions to assess behavior and reactions, it is conducted in a controlled test environment. However, the application of the interventions does not occur in similar environments, hence the need for a design methodology with high ecological validity. Therefore, one significant contribution of the TMR study designs is that the results are generalizable.
Another significant contribution of the TMR design is that it is theory-based, providing higher quality evidence regarding interventions. According to Cairney et al. (2014), TMR is a theory-driven scientific investigation that uses literature to test hypotheses. The methodology produces high-quality evidence because theory facilitates balancing between assumptions, the gathered data, observations, and measurement models. Relying on a singular approach, such as the data collected, limits the validity of study results due to the likelihood of bias from uncontrolled events during the research. Theory moderates the effects of such events on the results, improving the findings’ validity and reliability. Therefore, TMR is a theory-based approach that produces high-quality scientific evidence.
Despite these strengths, various limitations undermine the contributions of the TMR design to investigating sleep and psychology. One major limitation is that TMR as a methodological design does not control baseline cognitive ability. Controlling cognitive processes when conducting studies that involve competing cognitive functions is critical in enhancing validity of results (Krause et al., 2017). Naturally, mental processes are allocated and prioritized through attentional functions before being processed in the brain. However, when competition for a limited mental resource is needed to provide commands to ensure that the cognitive processes are redirected to the processes under investigation. For example, when testing if sleep is essential in learning a new language, the process arouses competition between mental functions such as alertness and orientation. Asserting cognitive regulation averts the risk of uncertainty during the decision-making process (Krause et al., 2017). TMR does not allow for cognitive control, increasing the risk of delay, a significant limitation.
Another major limitation is that the design does not provide information regarding changes to the memory accuracy, depending on the experimental task that a researcher adopts. A study conducted by Cairney et al. (2014) did not indicate memory accuracy alterations related to TMR, which the researcher attributed to differences in experimental tasks. These differences complicate interpreting the results and generalizing them to the population. Lack of uniformity in the results of the TMR unless the functions are similar also reduces the scope of applicability of the study findings, which is a significant limitation of the design.
Contributions and Limitations of Naturalistic Longitudinal Observation Design
One of the significant contributions of the naturalistic longitudinal observation studies is that they provide critical baseline data regarding real-world contexts compared to empirical data. NLO design enables practitioners to measure the effectiveness of empirically-proven interventions against no intervention (Wallace, 2019). Fundamentally, conducting a research study that excludes a section of the participants from treatment is controversially unethical and can arouse questions regarding the validity of such study results. Therefore, most studies involve comparing one intervention against the other, which complicates measuring the effectiveness of an intervention. However, NGOs allow researchers to observe participants in their natural settings without implementing an intervention. The approach does not involve uprooting the participants from their natural environment or controlling for any confounding variables, and it is not considered unethical. If the respondents do not receive an intervention, it does not amount to unethical behavior. The observations provide vital baseline data for comparing the performance of an intervention.
Another significant contribution is that NLO provides feedback regarding the flexibility v. fidelity relating to clients with different characteristics. The approach creates a feedback loop that empirical researchers can utilize to measure how flexibility v. fidelity plays out with other respondents (Wallace, 2019). As a result, the NLO enables the investigators to determine the effectiveness of interventions based on characteristics like demography. Consequently, researchers who use NLO can provide vital insights regarding the interacting factors that can enhance the therapeutic efficacy of an intervention (Wallace, 2019). Therefore, giving feedback about the flexibility v. fidelity of an intervention based on respondents’ characteristics is another significant contribution of the approach.
However, the approach is marred by limitations that undermine the above strengths. NLO methodology is limited to observing social behaviors that occur naturally and frequently within the range of the observer (Erdley & Jankowski, 2020). Assessing social behaviors that do not often occur within the observer’s scrutiny requires adjusting the environment to make it more structured. Therefore, the NLO approach is limited to social behaviors that meet these qualifications. Another limitation is that behavior is largely subjective, which makes the study results prone to different interpretations based on the observer’s experience. Reporting the findings of a naturalistic longitudinal observation study requires the use of highly qualified observers and interpreters who can remain objective.
The current study investigates whether sleep is vital for learning a new language. I would recommend using the targeted memory reactivation process as the methodology for this project because it would allow the researcher to combine external cues with performance tasks to measure outcomes. TMR has been proven effective in consolidating memory after initial skill acquisition, making it suitable for testing whether sleep can consolidate external cues related to a new language, facilitating learning (Johnson et al., 2019). This approach is more scientific than naturalistic longitudinal observation, which implies that it can produce high-quality empirical evidence if the researcher adheres to the study’s rigor.
Cairney, S. A., Durrant, S. J., Hulleman, J., & Lewis, P. A. (2014). Targeted memory reactivation during slow wave sleep facilitates emotional memory consolidation. Sleep, 37(4), 701-707.
Cherry, K. (2019). Naturalistic observation in psychology. Very well mind. Web.
Erdley, C. A., & Jankowski, M. S. (2020). Assessing youth. In Social skills across the life span (pp. 69-90). Academic Press.
Hu, X., Cheng, L. Y., Chiu, M. H., & Paller, K. A. (2020). Promoting memory consolidation during sleep: A meta-analysis of targeted memory reactivation. Psychological Bulletin, 146(3), 218.
Johnson, B. P., Scharf, S. M., Verceles, A. C., & Westlake, K. P. (2019). Use of targeted memory reactivation enhances skill performance during a nap and enhances declarative memory during wake in healthy young adults. Journal of Sleep Research, 28(5), e12832.
Krause, A. J., Simon, E. B., Mander, B. A., Greer, S. M., Saletin, J. M., Goldstein-Piekarski, A. N., & Walker, M. P. (2017). The sleep-deprived human brain. Nature Reviews Neuroscience, 18(7), 404-418.
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Rasch, B., Büchel, C., Gais, S., & Born, J. (2007). Odor cues during slow-wave sleep prompt declarative memory consolidation. Science, 315(5817), 1426-1429.
Sanders, K. E., Osburn, S., Paller, K. A., & Beeman, M. (2019). Targeted memory reactivation during sleep improves next-day problem solving. Psychological science, 30(11), 1616-1624.
Wallace, B. C. (2019). Making mandated addiction treatment work. Rowman & Littlefield.