. Association of deficits in short-term learning and Aβ and hippocampal volume in cognitively normal adults. Neurology. 2020 Nov 3;95(18):e2577-e2585. Epub 2020 Sep 4 PubMed.

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  1. Learning, practice effects, learning to learn, statistical learning, associate learning, retest, performance gains—there are many ways to describe the underlying construct in the exciting novel task called the Online Repeatable Cognitive Assessment-Language Learning Task (ORCA-LLT) used here by Lim et al.

    The task itself has broad appeal: Participants are taught to recognize Chinese characters over several days simply by asking them to decide whether a character matches an English word. Critically, no feedback is given during the test. The participants learn to associate the correct English word simply by observing the correct matches much more often than the incorrect matches.

    This touches upon statistical learning approaches from cognitive psychology, but the appeal in this particular task is that unlike most cognitive testing done in clinical studies, the participants gain something from participation—and something that could be interesting and even useful to them in their everyday lives, such as learning a second language. As the field of Alzheimer’s disease clinical trials searches for cognitive outcome measures, we must face the reality that there are significant shortcomings with our current methods of lengthy, one-shot assessments that often repurpose conventional neuropsychological and mental status measures that were designed to measure gross deficits and were not designed to be sensitive to the earliest brain changes that occur in the asymptomatic stages before dementia onset. Current methods also suffer from extremely low reliability. Day-to-day fluctuations in fatigue, mood, attentiveness, short-term illnesses, not to mention test anxiety, can produce high variability in test performance. In clinical trials, this variability can have drastic impacts on statistical power.

    ORCA-LLT captures learning rates, which have been shown to be more indicative of the earliest AD-related changes than recall deficits, and does so with extremely high reliability due to its format of long exposures to test stimuli (experienced in the participant’s familiar environment) over several consecutive days. The results of the study suggest that this method of assessment has exceptional promise. Cognitively normal but amyloid-positive older adults demonstrated extremely large effect-size impairments in learning rates compared to amyloid-negative older adults. To contrast between long-term and short-term learning, the study compared their learning rates on ORCA-LLT to learning rates across repeated AIBL study visits at 18-month intervals and to meta-analytic studies from the extant literature on preclinical AD. The ORCA-LLT had four times the effect size observed in long-term learning. In addition to amyloid, the test was also significantly related to hippocampal volume, which is often used as an indicator of neurodegeneration in AD studies.

    There are of course challenges with this approach. Like any remote study that is unsupervised, adherence can be a significant problem. This method of assessment requires participants to independently log onto a website for up to 30 minutes a day for six consecutive days and to endure a potentially very frustrating experience since the paradigm, by design, provides no feedback. On day one, the task appears to be totally random and some participants that need a sense of mastery may react strongly to the unstructured nature of the task so day one dropout is a valid concern. Handling missing data is another challenge with this task design. If all participants are not given the same opportunity to learn the stimuli over the same period, how does one model these data to be comparable to the other participants? Although not addressed in the publication, the authors are indeed aware of these concerns.

    There are so many possibilities to use this paradigm with different stimuli (learning abstract art and artists’ names, flora and fauna identification, faces and names, etc.), different set lengths (perhaps 20 characters over three days is enough?), and over different time periods (can learning rates be produced in one day that are just as sensitive?). Although the concept of this task is not entirely new, the clever design, the clinical meaningfulness of the task, and the readily available technology in the current age opens the door for learning rates as an assessment modality that could have game-changing impacts for observational studies and clinical trials.

    View all comments by Jason Hassenstab
  2. Lim and colleagues use a language-learning test, with repeated learning sessions containing the same learning material, to investigate learning performance (instead of memory performance) in 80 older adults.

    Following a supervised first learning session, participants continued with five more online sessions in the following days, where they learned associations of Chinese and English vocabulary. In addition, the authors determined amyloid-β status using positron emission tomography and they analyzed hippocampal and ventricular volume derived from MRI scans. Their main finding shows that Aβ-positive individuals show lower learning rates across six learning sessions on consecutive days. In addition, hippocampal volume was smaller, while ventricular volume was larger, for those individuals with smaller learning effects. Lim et al. conclude from their results that Aβ is primarily associated with a learning deficit and thus with a failure to benefit from earlier learning experience.

    While we usually try to prevent or minimize learning and practice effects in repeated assessments of cognitive function by employing different sets of difficulty-matched parallel test versions, the findings from Lim et al. suggest that learning rates could instead be considered as a screen for early cognitive impairment, or even future cognitive decline, and thus add to a body of earlier papers on practice effects that have recently been reviewed (Jutten et al., 2020). 

    While these results strengthen the evidence for the usefulness of learning-related markers as measures of cognitive function in research studies and potentially in clinical trials, they also highlight our lack of understanding regarding the mnemonic and neural mechanisms. While the observed relationships with hippocampal atrophy suggest a medial temporal origin, future studies need to identify and dissect the wider functional networks involved in repeated learning and their local relationship with accumulation of Aβ and tau pathology. This is especially true for the posterior-medial recollection network, which is particularly prone to early deposition of Aβ plaques.

    References:

    . Lower practice effects as a marker of cognitive performance and dementia risk: A literature review. Alzheimers Dement (Amst). 2020;12(1):e12055. Epub 2020 Jul 9 PubMed.

    View all comments by Oskar Hansson
  3. Once again, our friends from Australia and AIBL have conducted a very interesting experiment that could have significant potential for improving the diagnosis and prognosis of Alzheimer’s Disease (defined as abnormal Aβ deposition) as well as the development a new set of tools that could be used in clinical trials.

    The gist of the experiment consisted of comparing the performance of a group of “cognitively normal” subjects who were Aβ+ with a group who were Aβ–, using a novel cognitive task (learning the association between a Chinese character and its meaning in English—the ORCA-LLT). The paper reports that Aβ+ subjects were not as efficient as Aβ– subjects when learning the new material over the six days of learning trials. In addition, the deficits seen in Aβ+ subjects correlated with increased ventricular volume and reduced hippocampal volumes, whereas performance on the task did not correlate with either measure in Aβ– subjects.

    What does this mean? For one, we need to rethink how we define cognitively normal. Models of memory all include some form of acquisition, consolidation, and retrieval functions, and some traditional tests of declarative verbal memory (e.g., CVLT) include measures of learning efficiency. However, the brunt of focus on memory in AD patients (across the spectrum of severity) has been on measures of spontaneous or cued retrieval. The novelty of this paper is that it serves to remind us that the acquisition of novel information is impaired at very early stages of AD and that there are tools we can use now to measure learning efficiency.

    Moreover, tools such as the ORCA-LLT have the advantage of being scalable and simple to administer, making them good candidates for population-level screening and longitudinal monitoring. One can only hope to see rapid independent replication of this paper in a larger cohort and data looking at the effects of APOE and tau on learning efficiency.

    View all comments by Michael Gold
  4. Lim et al. found that cognitively healthy older adults with Alzheimer’s pathology (greater amounts of amyloid) in their brains struggled to learn a series of Chinese characters, and their English-language equivalents, over six days compared to older adults without this brain pathology. This finding is consistent with our own work showing that one’s ability to learn to take memory tests during one week is related to the amount of that same Alzheimer’s pathology in the brain (Duff, 2014; Duff et al., 2017). 

    Taken together, these two sets of results indicate that more amyloid in the brain leads to a failure to benefit from experience with novel stimuli, even over days to weeks. What might be the implications of this information? Our ability to benefit from experience (whether learning Chinese/English pairs, taking memory tests, completing new tasks at work, or using a new remote control) is crucial for successful adaptation to daily life. Failure to benefit from that experience may have dire consequences.

    Ultimately, deficits in learning, especially repeated exposure to novel information, may be one of the earliest harbingers of eventual Alzheimer’s disease. However, such information might also lead to interventions that bolster learning abilities and reduce risk of developing such conditions.

    References:

    . One-week practice effects in older adults: tools for assessing cognitive change. Clin Neuropsychol. 2014;28(5):714-25. Epub 2014 Jun 2 PubMed.

    . Short-term practice effects in mild cognitive impairment: Evaluating different methods of change. J Clin Exp Neuropsychol. 2017 May;39(4):396-407. Epub 2016 Sep 20 PubMed.

    View all comments by Kevin Duff
  5. This is an elegant study that highlights the central nature of a learning deficit in preclinical Alzheimer’s disease. Although meta-analytic studies have suggested that measures of learning are as useful as measures of delayed recall for the prediction of conversion from MCI to dementia (Belleville et al., 2017) and for differentiating individuals with MCI or Alzheimer’s dementia from cognitive normal adults (Weissberger et al., 2017), there remains a predominant focus in the field on measures of delayed recall.

    The large effect size elicited over a short period of time on the novel learning measure developed by Lim and colleagues illustrates that a well-designed learning paradigm can outperform traditional measures of delayed recall and brings to light the important role that sensitive cognitive measures play in the early detection of Alzheimer’s disease.

    References:

    . Neuropsychological Measures that Predict Progression from Mild Cognitive Impairment to Alzheimer's type dementia in Older Adults: a Systematic Review and Meta-Analysis. Neuropsychol Rev. 2017 Dec;27(4):328-353. Epub 2017 Oct 10 PubMed.

    . Diagnostic Accuracy of Memory Measures in Alzheimer's Dementia and Mild Cognitive Impairment: a Systematic Review and Meta-Analysis. Neuropsychol Rev. 2017 Dec;27(4):354-388. Epub 2017 Sep 22 PubMed.

    View all comments by Nikki Stricker
  6. It is encouraging for secondary prevention trials seeking well-powered cognitive outcome measures that such a strong amyloid-related learning deficit is detectable over a short period in preclinical AD. Though not directly tested in the present study, it is particularly striking that the deficit in learning rate appears even at low-to-moderate Centiloid levels (i.e., 25-50 CL).

    Future studies expounding when this learning deficit appears and whether amyloid or tau alone, or the combined effect of both pathologies, drive this learning deficit will be critical to determine whether preclinical AD researchers ought to shift away from traditional measures of memory recall to these measures of novel short-term learning.

    View all comments by Michelle Farrell

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