Understanding long-term forgetting in the healthy and clinical population: evidence from different research paradigms and methods

Abstract

Memory and forgetting are closely related, yet cognitive research has neglected the topic of long-term forgetting, leaving several questions unanswered. From a theoretical point of view, understanding the dynamics of normal forgetting would clarify whether forgetting depends on how much information is initially encoded, on the passage of time or on the type of material tested. From a clinical point of view, knowing how people normally forget information would inform our understanding on pathological forgetting in people with neurological conditions, and would aid the development of reliable clinical assessments.

This PhD thesis sought to expand our current knowledge on long-term forgetting through various stimulus material and research paradigms, which were:

1. Behavioural paradigms of Prose recall memory to assess how qualitatively distinct episodic details (gist and peripheral) are forgotten and how repeated retrieval and initial degree of post-encoding performance affect their retention (Experiment 1, 2 and 3; Chapter 2). Previous research (Sekeres et al., 2016) demonstrated that forgetting of peripheral details occurs at a faster rate, as compared to memory for gist up to a week. In my experiments, I assessed forgetting of episodic details up to a month by adapting the research design from Slamecka and McElree (1983), who observed parallel forgetting with verbal material up to 5-days. I found that peripheral details were forgotten at a faster rate than gist events when memory was tested after a month, whilst forgetting was countered by repeated testing. With shorter intervals (Experiment 5 and Experiment 6; Chapter 4) I could not observe this differential effect, independently of age that did not modulate the observed effects (Experiment 4; Chapter 3)

2. Neuropsychological research methods to assess whether people in early stages of Alzheimer’s Disease present with Accelerated Long-term Forgetting or not. Some researchers argued that faster forgetting occurs in early Alzheimer’s Disease (Weston et al., 2018), while others did not (Stamate et al., 2020). Experiment 7 (Chapter 5) employed the same prose recall paradigm of previous experiments on a group of people with amnesia (Mild Cognitive Impairment due to Alzheimer’s Disease) and a group of age-matched healthy controls. In this experiment, people with amnesia presented with impaired encoding and faster forgetting of gist events of a story, while memory for peripheral information pervasively remained at floor. I reconciled previous discordant literature by concluding that people with Alzheimer’s Disease show Fast Forgetting when the material to be recalled grossly benefits from repeated testing.

3. Psychophysical methods to investigate perceptual memory and forgetting of sinusoidal gratings up to 24-hr. Experiment 8 (Chapter 6) attempted to replicate a study from Magnussen et al. (2003), who claimed the existence of a high-fidelity perceptual long-term storage of spatial frequency. I failed to replicate these findings, so the existence of a long-term perceptual memory for spatial frequency could not be demonstrated and it would not represent a promising ground for further investigations in healthy aging and people with amnesia.

4. Working memory research methods to study long-term learning and forgetting of feature bindings (colours-shapes combinations). The aim of Experiment 9 (Chapter 7) was to assess whether learning took place after repeated verbal recall by assessing memory retention for a visual array at time intervals of 1-day or 1-week or 1-month, and by also considering the role of awareness of repetition on long-term learning and forgetting of feature binding. I demonstrated that long-term learning and retention of feature bindings is enhanced by repeated recall of the visual array, and this is faster in participants who became aware of repetition. Learning of feature binding remained stable up to a day, and I also found evidence of residual learning after a month, even among those participants who did not learn after repeated array presentations. I therefore concluded that long-term learning and retention of feature binding is supported by two different cognitive mechanisms: visual short-term memory and episodic long-term memory.