The US Food and Drug Administration Approves Use of Aducanumab for Alzheimer’s Disease Treatment

Post by Shireen Parimoo

Treatments for Alzheimer’s disease

Alzheimer’s disease (AD) is a neurodegenerative illness characterized by the deposition of amyloid-β (Aβ) plaques and neurofibrillary tangles in the brain that lead to widespread neurodegeneration, resulting in dementia and eventual death. AD affects more than 20 million people in the world, and with a growing global aging population, it has become increasingly crucial to develop treatments that can stop or delay the progression of AD symptoms.

Over the decades, several drugs have been developed and tested in randomized clinical trials. The drugs that have previously been approved for treating symptoms of AD help regulate the level of neurotransmitters in the brain. For example, the drug Donepezil helps temporarily mitigate memory-related symptoms by preventing the breakdown of acetylcholine. So far, however, none of these drugs have been effective in preventing the progression of AD or treating the underlying neuropathology. In fact, no new drug has been approved by the United States Food and Drugs Administration (FDA) for AD treatment since 2003.

In The Lancet Neurology, Lon Schneider provides an overview of a novel AD drug – aducanumab – created by the company Biogen. Schneider outlines the mechanism by which the drug targets AD pathology along with the history of its development. Aducanumab is a monoclonal antibody that is markedly different from other AD drug candidates because it directly binds to and clears out Aβ deposits in the brain, thereby targeting the hypothesized neuropathological mechanism underlying AD progression.

Is aducanumab effective?

Early randomized clinical trials showed that aducanumab injections over a year reduced Aβ levels in patients with prodromal or mild AD, though the clinical effects were less conclusive. Following up on these promising results, 1650 patients were enrolled in two separate multi-year phase 3 trials in 2015 to determine the efficacy of aducanumab in reducing the clinical symptoms of AD.

Despite initially promising results, several factors halted further testing of the drug. Firstly, there were issues with uneven participant dropout, missed doses, and poor compliance with the treatment protocol between the placebo and drug groups. Secondly, futility analyses conducted to monitor the interim efficacy of the drug showed mixed results and undesirable side effects like brain swelling. Specifically, differences in clinical symptoms between patients taking aducanumab and placebo only emerged in one of the trials. Moreover, it is unclear whether the differences were due to the drug’s efficacy in improving symptoms or because of worsening symptoms in the placebo group.

Finally, some of the positive results were observed in patients who received high doses of aducanumab, were genetically less at risk for experiencing side effects, and were highly compliant with the treatment protocol. In contrast, the placebo group consisted of more patients who were genetically predisposed to developing side effects and experienced greater clinical decline. Together, these factors posed a challenge to the validity of the findings from the clinical trials.

What’s happening now?

In June 2021, the FDA approved aducanumab under its accelerated approval pathway. This decision came after the FDA advisory committee had initially voted against approving the drug in November 2020. The accelerated approval approach is typically taken when the benefits provided by a drug under consideration outweigh those of existing treatments and are likely to have desirable long-term effects as well.

According to the FDA, their primary reason for approving aducanumab was the reliable dose- and time-dependent reduction in Aβ plaques. It is hoped that in turn, a lower Aβ burden will reduce further clinical decline, even though the evidence for this effect is currently uncertain. The next steps include conducting phase 4 clinical trials to confirm the clinical benefits of aducanumab in AD patients.

Schneider, L. A resurrection of aducanumab for Alzheimer’s disease. Neurology (2020). Access the original scientific publication here.

https://www.fda.gov/drugs/news-events-human-drugs/fdas-decision-approve-new-treatment-alzheimers-disease

How Much Effort Does it Take to Just Listen?

Post by Anastasia Sares

What is listening effort?

We don’t often think about how much of our mental space we reserve for listening to speech—for many people, it feels effortless. However, there are often obstacles: background noises, distracting conversations, or age-related hearing loss, to name a few. According to some models, we have a limited amount of mental resources, and the more we spend trying to decipher speech, the less we have left over for critical thinking, memory, and other high-level processing. However, a nebulous concept such as “effort” isn’t easy to quantify, and scientists have tried a number of approaches, from self-report questionnaires to full-sized brain scanners. Here’s a run-down of all the techniques used to measure listening effort.

Using self-report measures

One way to measure effort on a task is to ask people about it directly. This is the simplest method, but it can get tricky because people may have different interpretations of what “effort” means. To be more precise, some recommend breaking down effort into sub-components, like mental effort, physical effort, time pressure, or frustration. The NASA task load index is one such breakdown. However, a recent study suggests that we should ask about tiredness, a question that is not present in the NASA task load index. In that study, people’s tiredness ratings during speech listening were shown to correlate with the next method of measuring effort: pupil size.

Using the size of the pupil (pupillometry)

Our pupils dilate under states of mental arousal or effort, and specifically when listening conditions are worsened. Using video recordings of the eye or special glasses with infra-red cameras, we can measure the size of a person’s pupil as they hear and respond to sounds—this is called pupillometry. It is less subjective than self-report, and we can evaluate the effort someone expends on a task without forcing them to stop and reflect. However, pupillometry currently needs specific lighting conditions, and sometimes the pupil response can plateau in complex tasks. So, there are still some challenges to using this method.

Using brain activity (EEG, fMRI, fNIRS)

Electroencephalography, or EEG, measures electrical activity in the brain and can be used as another way to tap into listening effort. Among other EEG measures, the N100 response to sound is one index of this effort. This automatic response happens 100 milliseconds after the onset of a sound, and it becomes bigger when the speech is made less intelligible. Another EEG measure of effort is alpha power. If we take the activity in the alpha range and sum up its power over the course of an experiment, we can see when more effort is being expended.

Blood flow to different brain areas has long been used as a proxy for brain activity in those areas. In particular, blood flow to the left inferior frontal region of the brain (close to the temples) and the superior temporal gyrus (just above the ears) can give us a hint about how much effort is being exerted. This can be done in a magnetic scanner that detects the magnetic properties of blood (fMRI) or using a cap with small infra-red lights pointed at the scalp (fNIRS). These blood flow methods are a little slower than EEG, but fMRI, in particular, can pinpoint the location of activity in the brain with better accuracy, and fNIRS is advantageous because it doesn’t interfere with hearing aids or other devices.

What’s the bottom line?

Hearing is a crucial aspect of health: hearing loss has a large societal burden and may contribute to the risk of dementia later in life. Armed with multiple tools to measure listening effort, we can study how it varies in different conditions and populations, and better understand the link between hearing and cognition.

References

Pichora-Fuller, M. K. et al. Hearing Impairment and Cognitive Energy. Ear Hear. 37, 5S-27S (2016).

Hart, S. G. & Staveland, L. E. Development of NASA-TLX (Task Load Index): Results of Empirical and Theoretical Research. Adv. Psychol. 52, 139–183 (1988).

McGarrigle, R., Rakusen, L. & Mattys, S. Effortful listening under the microscope: Examining relations between pupillometric and subjective markers of effort and tiredness from listening. Psychophysiology 58, 1–22 (2021).

Zekveld, A. A., Kramer, S. E. & Festen, J. M. Pupil response as an indication of effortful listening: The influence of sentence intelligibility. Ear Hear. 31, 480–490 (2010).

Koo, M. et al. Effects of noise and serial position on free recall of spoken words and pupil dilation during encoding in normal-hearing adults. Brain Sci. 11, 1–14 (2021).

Zhang, Y., Lehmann, A. & Deroche, M. Disentangling listening effort and memory load beyond behavioural evidence: Pupillary response to listening effort during a concurrent memory task. (2020). doi:10.1101/2020.05.04.076588

Obleser, J. & Kotz, S. A. Multiple brain signatures of integration in the comprehension of degraded speech. Neuroimage 55, 713–723 (2011).

Obleser, J., Wöstmann, M., Hellbernd, N., Wilsch, A. & Maess, B. Adverse listening conditions and memory load drive a common alpha oscillatory network. J. Neurosci. 32, 12376–12383 (2012).

Wild, C. J. et al. Effortful listening: The processing of degraded speech depends critically on attention. J. Neurosci. 32, 14010–14021 (2012).

Kousaie, S. et al. Language learning experience and mastering the challenges of perceiving speech in noise. Brain Lang. 196, 104645 (2019).

Zekveld, A. A., Heslenfeld, D. J., Johnsrude, I. S., Versfeld, N. J. & Kramer, S. E. The eye as a window to the listening brain: Neural correlates of pupil size as a measure of cognitive listening load. Neuroimage 101, 76–86 (2014).

Rovetti, J., Goy, H., Pichora-Fuller, M. K. & Russo, F. A. Functional Near-Infrared Spectroscopy as a Measure of Listening Effort in Older Adults Who Use Hearing Aids. Trends Hear. 23, 233121651988672 (2019).

Ford, A. H. et al. Hearing loss and the risk of dementia in later life. Maturitas. 112, 1–11 (2018).

Attention in the Age of Social Media

Post by Elisa Guma

The advent of the internet

The Internet is the most widespread and rapidly adopted technology in the history of humankind. With the advent of broadband Wi-Fi and smartphone technologies, we have constant access to the internet. This has rapidly changed the way we work, search for and access information, consume media and entertainment, and engage socially. Indeed, we currently live in a media-saturated world, using it not only for entertainment purposes such as listening to music or watching movies but also for communicating with peers. Connecting with family and friends across the globe can help people feel more connected in times of isolation, such as in the current global pandemic. However, access to this endless stream of communication and connection may be changing the way we think and absorb information and may also impact our mental health.

Attention and the brain

Attention is the behavioural and cognitive process by which we selectively concentrate on a discrete aspect of information while ignoring other information. Focusing our attention recruits brain regions such as the prefrontal and visual cortices, thalamic and midbrain nuclei. It can alternatively be thought of as an allocation of limited cognitive processing resources to a particular topic or task. The ability to achieve selective and sustained attention, free from distractions, is critical to our ability to complete tasks, learn new information, and engage socially with others. Once attention is engaged, we remain focused until some external environmental or internal state change occurs that triggers a shift. The constant flow of information and notifications the internet brings may interfere with our ability to maintain sustained concentration on other tasks. Social media is designed to be highly engaging in an attempt to keep us browsing for as long as possible. Furthermore, content that fails to gain our attention is quickly drowned out in a sea of incoming information, while information that does capture our attention is amplified or proliferated.

How does social media impact our attention?

One of the first studies investigating the effect of social media on attention found that heavy social media use may increase people’s susceptibility to distraction from irrelevant stimuli. Neuroimaging studies have shown that those who engage in heavy media multitasking perform poorer in distracted attention tasks while exhibiting greater activity in prefrontal regions during those tasks. These findings suggest that these individuals may require higher cognitive effort to maintain concentration when faced with distractor stimuli. Similarly, heavy internet usage and multitasking have been associated with decreased grey matter volume in brain regions involved in decision-making. Comorbidities between internet use disorders and attention deficit hyperactivity disorders have also been reported, suggesting that there may be strong links between excessive media usage and disorders of inattention.

Although research in this area is growing, the findings are still mixed. Some studies have confirmed these negative effects on attention, whereas others report that increased media multitasking may even be linked to increased performance in some aspects of cognition. It is possible that the internet allows for “cognitive off-loading” of certain cognitively demanding tasks, such as semantic memory retrieval, which may free up our cognitive resources for use in other tasks. It is difficult to disentangle whether heavy social media use leads to higher distractibility, or whether pre-existing differences in neural activity make some individuals more susceptible to distraction. What we do know, is that social media and technology offer easy-to-reach distractions, which may interfere with our ability to focus.

Social media use and mental health

Engaging with social media apps taps into more than just our brain’s attention network. It requires social reward processing, emotion-based processing, regulation, and thinking about the thoughts and feelings of others. Numerous studies have reported that positive attention on social media in the form of likes on Instagram, Twitter, and Facebook may cause our brains to release dopamine and activate reward circuits in the brain. Furthermore, reduced grey matter volume in regions involved in emotional regulation and social cognition, such as the amygdala and ventral striatum have also been associated with excessive social media use. Given the tight link between social media use and the brain’s reward system, there is potential for abuse or dependence.

Heavy social media use may also have important implications for psychological well-being. While social media use may provide an opportunity for social integration with similar interest groups, access to support groups, and motivation for a healthy lifestyle, it may also have more toxic effects on users’ mental health. Increased feelings of depression, anxiety, poor body image, and loneliness have all been reported following social media use.

Why are adolescents more susceptible?

Adolescence is a developmental stage in which the brain is undergoing extensive structural and functional remodeling. Impulse and cognitive control, as well as social reward and emotional processing, are not yet developed. This can lead adolescents to engage in more reward-seeking or risk-taking behaviours, and be more susceptible to distracting highly engaging social media content. As discussed above though, it is unclear whether social media use may influence our long-term ability to sustain attention, or whether it is merely a source of temporary distraction. Of greater importance for this age group may be the effects of social media on mental health. Adolescence is a sensitive developmental window in which neuropsychiatric disorders are most likely to emerge. Parental influence decreases, while the influence of peers and the need for peer acceptance increases. Managing social media use may be one helpful way to avoid overuse and some potential negative outcomes. Setting boundaries with social media use, such as reducing time spent on social networks, and establishing some no-phone zones in the home, or no-phone times (e.g. before bed) can be an effective way to prevent overuse. Gaining a better understanding of how adolescents process media content and peers’ feedback will be of critical importance for understanding how best to avoid negative impacts on mental health. 

What’s the takeaway?

With social media becoming a more and more prominent part of our everyday lives, there are many risks to be aware of, including social media overuse. Furthermore, heavy social media use may have an impact on how our brain functions. Although the extent to which social media use impacts our cognition and attention is still unclear, it certainly provides an additional source of distraction. Of greater concern, however, are the effects it may have on our mental health, particularly in more vulnerable age groups, such as adolescents. More research will be needed to better understand the impact that social media has in our lives, and how we can navigate its use in the future. 

References

Crone EA, Konijn EA. Media use and brain development during adolescence. Nature Communications (2018) 9(588). https://doi.org/10.1038/s41467-018-03126-x

Frith JA, Torous J, Frith J. Exploring the impact of internet use on memory and attention processes. International Journal of Environmental Research and Public Health (2020). 17 (9481); doi:10.3390/ijerph17249481

Baumgartner SE, van der Schuur WE, Lemmens JS, & Poel F.  The Relationship Between Media Multitasking and Attention Problems in Adolescents: Results of Two Longitudinal Studies. Human Communication Research (2017). 44 (1), 3-30. https://academic.oup.com/hcr/article-abstract/44/1/3/4760433

Ra CK, Cho J, Stone MD, De La Cedra J, Goldenson NI, Moroney E, Tung I, Lee SS, Leventhal AM. Association of Digital Media Use With Subsequent Symptoms of Attention-Deficit/Hyperactivity Disorder Among Adolescents. JAMA (2018). 320(3):255-263. doi:10.1001/jama.2018.8931

Cohen R.A. (2014) Neural Mechanisms of Attention. In: The Neuropsychology of Attention. Springer, Boston, MA. https://doi.org/10.1007/978-0-387-72639-7_10