Week in Review: Number 36

Age-Related Ophthalmic Conditions Associated with Increased Risk of Dementia Independently and Concurrently with Systemic Conditions
It is thought that reduced stimulation of the visual sensory pathways can accelerate cognitive decline, and a few small studies have suggested a link between ophthalmic conditions such as age-related macular degeneration, cataract, diabetes-related eye disease and glaucoma with cognitive impairment. Other studies have noted that systemic risk factors, such as as diabetes, high blood pressure, heart disease, depression and stroke also increase in incidence with increasing age. Researchers sought to investigate whether these ophthalmic conditions are associated with a higher incidence of dementia independently of these systematic conditions. They analysed data on 12,364 adults aged 55-73 years from the UK Biobank study; these individuals were initially assessed between 2006 and 2010 at baseline and followed up until early 2021. In the 1,263,513 data points collected, 2,304 cases of dementia were recorded. The data showed that age-related macular degeneration, cataract and diabetes-related eye disease, but not glaucoma, were independently associated with increased risk of dementia from any cause. In particular, compared with people who did not have ophthalmic conditions at the start of the study, the risk of dementia was 26% higher in those with age-related macular degeneration, 11% higher in those with cataract, and 61% higher in those with diabetes-related eye disease. They add that while glaucoma was not associated with increased risk of Alzheimer’s disease, it was associated with a higher risk of vascular dementia. Having both an ophthalmic condition and a system condition increased the risk of dementia further compared to having only an ophthalmic condition, with the greatest risk being concurrent diabetes-related eye disease and a systemic condition. Newly developed hypertension, diabetes, stroke, heart disease and depression mediated the association between cataract/diabetes-related eye disease and dementia. Finally, having more ophthalmic conditions showed a larger relative risk for dementia. The authors caution that this is an observational study based on self-reported and inpatient record data. Nonetheless, they conclude, "AMD, cataract and DRED but not glaucoma are associated with an increased risk of dementia. Individuals with both ophthalmic and systemic conditions are at higher risk of dementia compared with those with an ophthalmic or systemic condition only."

Aerosol Fluid Dynamics in Non-Contact Tonometry
Scientists in India were interested in studying the aerosol transmission of pathogens, especially in the context of SARS-CoV-2, and non-contact tonometers used to measure intraocular pressures as a screening for glaucoma. Based on tracking the speed of tear droplets ejected from the eye during "the air puff test," they predicted that tear droplets could travel up to a meter away from the patient, potentially presenting a pathway for spreading viral particles and transmitting the disease. The authors write, "The interaction finally leads to the rupture and breakup of the tear film culminating into sub-millimeter sized droplet projectiles traveling at speeds of 0.2 m/s. The calculated droplet spread radius (∼0.5 m) confirms the likelihood of the procedure to generate droplets that may disperse in air as well as splash on instruments, raising the potential of infection." The distance also depended on factors such as air flow in the room. Eyes with more tears created more droplets than dry eyes, leading them to recommend against the use of eye drops prior to the test. Although most pertinent in the context of the COVID-19 pandemic, these fluid dynamics are applicable to the spread of aerosol pathogens in general. The researchers conclude that although non-contact tonometry is considered a relatively safe test, caution should be considered in improving room ventilation and cleaning nearby instruments and surfaces that had not been thought of previously.

GLP-1R Agonists as Glaucoma Treatment in Diabetics
A retrospective study examining a class of diabetes medications called glucagon-like peptide-1 receptor (GLP-1R) agonists (Trulicity and Rybelsus) shows a possible protective effect against glaucoma in patients with diabetes. GLP-1R agonists are normally used to regulate blood glucose in type 2 diabetes mellitus. However, evidence in animal models shows that this class of drugs provides some neuroprotection against Alzheimer's and Parkinson's diseases, with clinical trials underway to test the drug against neurodegenerative diseases in humans. An earlier study from 2020 similarly found that the GLP-1R agonist NLY01 reduced retinal neuroinflammation and glial activation to rescue retinal ganglion cells in a mouse model of glaucoma, spurring the researchers to investigate whether exposure to GLP-1R agonists influences glaucoma risk. The investigators looked at an insurance claims database (Clinformatics Data Mart), with cohorts comprised of 1961 new users of GLP-1R agonists matched to 4371 unexposed controls. They found that after 150 days on average, 10 patients (0.51%) in the medicated group were newly diagnosed with glaucoma compared to 58 patients (1.3%) in the control group. After adjustment, the data shows a reduced hazard ratio of 0.56, suggesting that exposure to GLP-1 receptor agonists may decrease a diabetic patient’s risk of developing glaucoma by half. The researchers remark that the encouraging findings from their study warrant further investigation into the potential of GLP-1R agonists in glaucoma prevention.

Varying Eye Contact Enhances Conversation
Eye contact can be immersive and powerful. However, a new study suggests that varying eye contact, repeatedly making and breaking eye contact, enhances the dynamics of a conversation. As graduate student and lead author of the study explains, “When two people are having a conversation, eye contact signals that shared attention is high—that they are in peak synchrony with one another. As eye contact persists, that synchrony then decreases.” In particular, she and her research advisor examined pupillary synchrony, when two speakers' pupils dilate in sync, during moments of shared attention. The principle investigator of the study further comments, “We make eye contact when we are already in sync, and, if anything, eye contact seems to then help break that synchrony. Eye contact may usefully disrupt synchrony momentarily in order to allow for a new thought or idea.” The study involved 47 pairs of students having 10-minute recorded conversations about whatever they wanted while wearing eye-tracking glasses. The participants were asked to watch the recordings and rate how engaged they were. The data showed that people make eye contact as pupillary synchrony is at its peak, immediately decreases, only to sync again once eye contact is broken. They also found that instances of eye contact correlated with moments with higher levels of engagement during a conversation. The findings highlight that conversation is a shared creative process, with the rise and fall in pupillary synchrony and eye contact allowing for both moments of shared attention and moments of independent novelty. Moving into and out of alignment enhances connection. The authors conclude that "[E]ye contact may be a key mechanism for enabling the coordination of shared and independent modes of thought, allowing conversation to both cohere and evolve."

Pupil Shape Reveals GAN-Generated Faces
Computer scientists interested in studying differences between real photos and computer-generated photos developed a detection software to analyze differences in human faces generated by deep learning artificial intelligence systems called generative adversarial networks (GAN). Images of real faces are fed into the deep learning system, which then generates synthetic faces. These faces are then tested against another neural network that attempts to spot the fake images, so that the first network can learn from its mistakes; the back and forth between the “adversarial networks” quickly improves the output, to the point where the synthetic faces are difficult to distinguish from real ones. The results are, for example, "deep fake" photos for fake social media accounts. However, these systems are not perfect. While the faces themselves are realistic enough, details such as earrings and glasses contain artifacts that give them away. The present research found another tell-tale sign, namely, in the shape of pupils. Whereas real pupils are round or slightly elliptical, the pupils in computer-generated models are irregular, which the researchers speculate is due to the GAN models' "lack of physiological constraints," or lacking an understanding of eye anatomy. They then applied a detection tool to extract and analyze the regularity of pupil shape from a database of 2000 images (1000 real faces and 1000 synthetically generated faces), reporting that the software could reliably distinguish between the two based on pupil shape. They conclude that evaluation of pupil shape can be used as a simple, yet effective, method to detect GAN-generated faces, and thereby help to counter the malicious use of "deep fake" photos to deceive people on social media and other platforms.

In Other News
(1) FDA approves Lucentis biosimilar to treat wet AMD
(2) People tend to conceptualize vision of 2D objects in 3D
(3) Abstract learning begins in the primary visual cortex