Factors Affecting Long-Term Memory Success/Failure

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Long-term memory (LTM) can be broadly defined as a store of information that is held indefinitely, with a near-limitless capacity (Cowan, 2008); this is estimated to be around 2.5 petabytes on average (Reber, 2010). LTM can be sub-divided into two main systems (Curran, 2014), one being declarative memory which stores information that requires conscious recollection, including episodic memories (EM), enabling us to remember events and experiences, and semantic memories (SM), which store our knowledge about the world (Tulving, 1993). In contrast, nondeclarative memory stores information that can be recalled unconsciously, including procedural memories which store information on how to perform certain tasks, such as riding a bike (Johnson, 2012). This essay will explore and critically evaluate some important factors that may contribute to determining the success or failure of encoding, maintenance, and retrieval in LTM. Declarative LTM will be the primary focus as evidence suggests that knowledge in this store is more accessible than nondeclarative LTM (Squire & Zola, 1996), which could be vastly improved through utilising specific learning and maintenance strategies. This store is also profoundly affected by amnesia, particularly retrograde amnesia and anterograde amnesia (Squire & Zola, 1998), both of which are potential consequences of brain damage This highlights the importance of studying declarative LTM, as a greater theoretical understanding could lead to the development of beneficial real-life interventions to improve the success of these memories.

One factor that may determine the success or failure of encoding in declarative LTM is whether a massing or spacing learning technique is adopted when learning information. Massed learning involves long, intense periods of study, however these sessions occur infrequently and temporally close together (VandenBos, 2007). A common massing technique is ‘cramming’, which involves studying intensely in the days or hours preceding the necessary retrieval of this information, such as in an examination (Kornell, 2009); evidence suggests that between 23.5% (Vacha & McBride, 1993) and 51% (Michaels & Miethe, 1989) of university students use this method, often following procrastination (Brinthaupt & Shin, 2001). Substantial evidence suggests that massing impairs learning and contributes to the failure of effectively encoding LTMs; this may occur because massing attenuates the degree of attention paid to information, as items become highly familiar when learning in this manner (Hintzman, 1974), which requires less processing but leads to more forgetting in the long-term (Magliero, 1983). In contrast, spaced learning is characterised by shorter, more frequent periods of study, with sufficient time left between learning sessions (VandenBos, 2007). Robust evidence suggests that this learning method is greatly beneficial and contributes to the successful encoding of LTMs. The reactivation theory of spacing effects (Mizuno, 2003) suggests this occurs because, in spacing, memory reactivation during subsequent learning sessions is greater than in massing. Research also indicates that spacing between sessions provides temporal distinctiveness, which appears to make memories more resistant to interference and thus improve long-term storage of material (Kelley & Whatson, 2013).

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There is substantial evidence demonstrating the superiority of spaced learning in encoding LTMs compared to massed learning. In Bloom & Schuell’s (1981) research, students studied words for a vocabulary test either distributed across three days, or all on the third day. Immediate testing did not produce a huge amount of difference in recall between the two groups, however, in a retest 4 days later, the massed learning groups recall was significantly poorer than the distributed group, reflecting the short-lived nature of massed information. This experiment has been widely replicated (e.g. McDaniel et al., 2013) and has valuable real-life application as it demonstrates the benefits of spaced learning in classroom activities, compared to previous studies which were predominantly artificial, laboratory experiments, and so lack generalisability to everyday settings. Furthermore, Foot-Seymour et al. (2019) found that spacing helped students to remember more facts, as well as develop their critical thinking skills. However, a notable limitation of this study is that it failed to find a benefit of spacing in one of the two fact learning measures, which was most likely due to fatigue as the 9-12 year old students were presented with a large number of questions following a ninety-minute lesson. Conflicting evidence from Brinthaupt & Shin (2001) found massing to be beneficial for learning as it increases individuals ‘flow’ state (Csikszentmihalyi, 1990), which is characterised by enhanced concentration and goals, and a loss self-consciousness. However, in terms of long-term storage, evidence clearly indicates that massing is far superior in successfully encoding LTMs, despite the benefits that massing may present at the time of learning.

Another factor that may determine the success or failure of storing declarative LTMs is whether information is effectively consolidated or not. Memory consolidation refers to the process by which an unstable, newly encoded memory is converted into a stable LTM (Squire et al., 2015). It is distinguished by two distinct processes; firstly, synaptic consolidation occurs, a comparatively quick process in which synaptic transmission is strengthened, enabling memories to be retained over a longer time (Clopath, 2012). This is followed by systemic consolidation, a considerably longer process in which memories that were originally hippocampal-dependent are reorganised to become hippocampal-independent (Dudai, 2004). These consolidation processes are augmented by various influences, one being sleep; research has found that rapid eye movement (REM) sleep supports synaptic consolidation through upregulating plasticity-related immediate-early genes, whilst the oscillations, spindles, and ripples occurring during slow-wave sleep (SWS) support systemic consolidation (Diekelmann & Born, 2010). The impact of this was demonstrated in Jenkins and Dallenbach’s (1924) classic research, which found greater retention of nonsense syllables following sleep compared to periods of waking activity; studies have since replicated this finding that increased sleep improves successful declarative LTM consolidation (e.g. Fowler et al., 1973; Plihal & Born, 1997). However, several reviews have critiqued these early studies as being confounded by circadian influences, which are also suggested to affect successful maintenance of declarative LTMs (Tilley & Warren, 1983), as subjects in sleep and wake conditions recalled information at different times of day, undermining these studies’ internal validity. Despite this, more recent and controlled research has indeed verified the relationship between sleep and enhanced declarative LTM, for instance Wagner et al. (2006) found that even a brief sleep following learning keeps memories, particularly emotional ones, alive for years. This highlightings the importance of consolidation in maintaining declarative LTMs, as well as the beneficial impact that sleep has on enhancing this process.

Reconsolidation also contributes to the success or failure of maintaining declarative LTMs; this is the process by which previously stored memories are reactivated, causing them to become unstable, and so these memories are consolidated once again to restore their stability (Alberini & LeDoux, 2013). Memory reconsolidation could facilitate LTM storage as evidence suggests that it strengthens memories; for instance, Lee (2008) found that memory reconsolidation in rats strengthened their contextual-fear memory, giving them an adaptive advantage as they learned to avoid an unpleasant stimulus. This adaptive strengthening advantage has been generalised to humans. For instance, Exton-McGuinness et al. (2015) interpreted it as being an adaptive updating mechanism for guiding future behaviour, however this is a theoretical assumption and lacks empirical evidence. Despite this, theoretical understanding of reconsolidation has led to the development of potentially beneficial interventions, one being for post-traumatic stress disorder (PTSD), particularly when used in conjunction with drug treatment. This was demonstrated by Brunet et al. (2008) who reminded participants of the event associated with their PTSD, and then administered some with propranolol, a beta blocker intended to reduce anxiety; when asked to imagine the event one week later, those in the propranolol group showed reduced emotional and physiological responses. On the contrary, memory reconsolidation has also been recognised as contributing to the failure of storing some declarative LTMs, as it makes memories more susceptible to distortion through misinformation. For example, Chan and LaPaglia (2013) showed participants a film clip, after which half of the participants were given a memory test to reactive their memory representation of this. Subsequently, all participants went through a ‘relearning’ phase where they were told facts about the film, some of which were incorrect; the group that had their memory reactivated suffered greater disruption to their memory. This draws attention to the profound impact of reconsolidation in storing accurate LTM representations, and this could have detrimental real-world implications, such as if individuals are subjected to leading questions during eyewitness testimony (Loftus, 1975).

A third factor that undoubtedly determines the failure of encoding and retrieving declarative LTMs is amnesia. Anterograde amnesia and retrograde amnesia both typically result from traumatic brain injury or damage (Martin & Slevc, 2012), and often occur concurrently (Smith et al., 2013). Anterograde amnesia is characterised by an inability to form new declarative LTMs; research has shown that anterograde amnesia primarily affects EMs following hippocampal damage, however it may also impair SMs if there is damage to the wider medial temporal lobe (MTL) (Spiers et al., 2001). For instance, patient ‘PS’ had impaired EM but relatively intact SM resulting from hippocampal-selective brain damage, whereas patient ‘SS’ had both impaired SM and EM, and was found to have wider MTL damage in addition to hippocampal damage (Verfaellie et al., 2000). Although this study is limited in the sense that it is idiographic and based on unique case studies, these findings have been widely replicated (e.g. Bayley et al., 2006). Retrograde amnesia also affects SM and EM, however it is characterised by an inability to recall these previously stored declarative LTMs and typically causes a selective deficit in either SM or EM. For instance, patient ‘KC’ suffered from severely impaired EM retrograde amnesia (Tulving, 2002); when tested using family photographs, he was able to recognise the people as his SM was comparatively intact, but he could not recall the event (Westmacott et al., 2001). The opposite effect was observed when patient ‘EL’, who had severely impaired SM but relatively intact EM, was tested, as he could recall the events but not the people or any other facts about the photograph. Retrograde amnesia seems to be caused by a widely distributed network of brain regions (Bright, et al., 2006), hence onset can be caused by various different types of brain damage. Furthermore, both anterograde amnesia and retrograde amnesia can be, and often are, extremely handicapping. Everyday challenges facing individuals suffering from both amnestic conditions might include the inability to fulfil social or occupational commitments due to the failure of retaining information (Svoboda & Richards, 2009), as well as being unable to recall important details that have happened in their lives. At present, there are no direct treatments to enable amnesic patients to successfully encode and/or retrieve declarative LTMs which is a significant limitation. However, interventions have been developed to assist in managing the handicapping effects of amnesia in order to improve individuals’ quality of life, including technology assistance such as reminder apps (Svoboda & Richards, 2009), which is indeed a significant advantage of research.

In conclusion, whilst anterograde and retrograde amnesia solely contribute to the failure of encoding and retreiving declarative LTMs, consolidation and learning techniques can cause either the success or failure of encoding and maintaining declarative LTMs. When encoding new material, there is strong evidence favouring the utilisation of a spaced learning technique, rather than a massed learning technique, as this makes information more temporally distinct, thus subsequently less susceptible to interference. This research has valuable real-world application to contexts such as educational institutions, as it could enable learners to more effectively retain new information. In addition, memory consolidation processes support the successful storage and maintenance of declarative LTMs, and can be enhanced by influences such as sleep. Although research has shown the therapeutic benefit of reconsolidation in disoders like that of PTSD, it also makes memory more susceptible to distortion when reactivated, which could have a negative effect in some contexts, such as eyewitness testimony. Furthermore, although anterograde and retrograde amnesia undoubtedly contribute to the failure of LTMs, research has led to significant advancements in theoretical understanding, as well as to the development of interventions to help individuals cope with everyday challenges, both of which are invaluable advancements.

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Factors Affecting Long-Term Memory Success/Failure. (2022, August 25). Edubirdie. Retrieved December 27, 2024, from https://edubirdie.com/examples/critical-analysis-of-the-factors-that-determine-the-success-and-failure-of-long-term-memory/
“Factors Affecting Long-Term Memory Success/Failure.” Edubirdie, 25 Aug. 2022, edubirdie.com/examples/critical-analysis-of-the-factors-that-determine-the-success-and-failure-of-long-term-memory/
Factors Affecting Long-Term Memory Success/Failure. [online]. Available at: <https://edubirdie.com/examples/critical-analysis-of-the-factors-that-determine-the-success-and-failure-of-long-term-memory/> [Accessed 27 Dec. 2024].
Factors Affecting Long-Term Memory Success/Failure [Internet]. Edubirdie. 2022 Aug 25 [cited 2024 Dec 27]. Available from: https://edubirdie.com/examples/critical-analysis-of-the-factors-that-determine-the-success-and-failure-of-long-term-memory/
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