Measures of Retinal Structure and Function as Biomarkers in Neurology and Psychiatry

Silverstein, Steven M.; Demmin, Docia; Schallek, Jesse; Fradkin, Samantha I.

doi:10.1016/j.bionps.2020.100018

Cited by 41 publications

(37 citation statements)

References 392 publications

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“…The anti-dopaminergic medication, however, may influence precision weighting and retinal functioning. 44 , 58 A strength of our study is the inclusion of 3 clearly distinct groups allowing us to draw conclusions across a variety of perceptual experiences. Schizophrenia patients as well as synesthetes were carefully characterized with regard to their specific conditions to ensure samples were as homogeneous as possible.…”

Section: Discussionmentioning

confidence: 99%

Perceptual Gains and Losses in Synesthesia and Schizophrenia

Leeuwen

Sauer

Jurjut

et al. 2020

Schizophrenia Bulletin

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Individual differences in perception are widespread. Considering inter-individual variability, synesthetes experience stable additional sensations; schizophrenia patients suffer perceptual deficits in, eg, perceptual organization (alongside hallucinations and delusions). Is there a unifying principle explaining inter-individual variability in perception? There is good reason to believe perceptual experience results from inferential processes whereby sensory evidence is weighted by prior knowledge about the world. Perceptual variability may result from different precision weighting of sensory evidence and prior knowledge. We tested this hypothesis by comparing visibility thresholds in a perceptual hysteresis task across medicated schizophrenia patients (N = 20), synesthetes (N = 20), and controls (N = 26). Participants rated the subjective visibility of stimuli embedded in noise while we parametrically manipulated the availability of sensory evidence. Additionally, precise long-term priors in synesthetes were leveraged by presenting either synesthesia-inducing or neutral stimuli. Schizophrenia patients showed increased visibility thresholds, consistent with overreliance on sensory evidence. In contrast, synesthetes exhibited lowered thresholds exclusively for synesthesia-inducing stimuli suggesting high-precision long-term priors. Additionally, in both synesthetes and schizophrenia patients explicit, short-term priors—introduced during the hysteresis experiment—lowered thresholds but did not normalize perception. Our results imply that perceptual variability might result from differences in the precision afforded to prior beliefs and sensory evidence, respectively.

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Section: Discussionmentioning

confidence: 99%

Perceptual Gains and Losses in Synesthesia and Schizophrenia

Leeuwen

Sauer

Jurjut

et al. 2020

Schizophrenia Bulletin

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“…Functional ability of RGC was assessed by pattern electroretinogram amplitude (PERGA), a useful tool to estimate the risk of glaucoma progression 49‐51 . PERG was assessed before and after melatonin treatment.…”

Section: Methodsmentioning

confidence: 99%

Melatonin mitigates disrupted circadian rhythms, lowers intraocular pressure, and improves retinal ganglion cells function in glaucoma

Gubin

Нероев

Малишевская

et al. 2021

Journal of Pineal Research

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Glaucoma is a progressive optic neuropathy associated with damage to retinal ganglion cells (RGCs) and disrupted circadian rhythms. Melatonin is a promising substance to ameliorate glaucoma‐associated compromised circadian rhythms, sleep, mood, and retinal cells function. However, studies estimating melatonin effects in glaucoma are currently lacking. Therefore, In this study, we investigated the effect of long‐term (daily at 10:30 pm for 90 days) oral melatonin administration on systemic (Tb) and local to the organ of vision (IOP) circadian rhythms, pattern electroretinogram (PERG), sleep, and mood, depending on glaucoma stage in patients diagnosed with stable or advanced primary open‐angle glaucoma. In a laboratory study in 15 of them, 24‐hour records of salivary melatonin were obtained and MTNR1B receptor gene polymorphism was assessed. Melatonin increased the stability of the Tb circadian rhythm by improving its phase alignment and alignment with IOP. Melatonin time‐dependently decreased IOP and IOP standard deviation (SD). IOP 24‐hour mean and IOP SD decreases were more pronounced in individuals with the higher initial 24‐hour IOP mean. Melatonin improved RGCs function in advanced glaucoma; N95 amplitude increase correlated positively with RGCs loss. The beneficial effects of melatonin on sleep and mood were greater in advanced glaucoma. Finally, delayed salivary melatonin and Tb phases were observed in MTNR1B G‐allele carriers with advanced glaucoma. Combined, these results provide evidence for melatonin efficiency in restoring disrupted circadian rhythms in glaucoma with different effects of melatonin on systemic vs. local circadian rhythms, indicating that a personalized strategy of melatonin administration may further refine its treatment benefits.

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“…In this study, we sought to demonstrate the potential effectiveness of an ML-based approach to investigating changes in retinal structure, as observed using optical coherence tomography (OCT; a form of retinal imaging) in people with schizophrenia. We undertook these analyses based on multiple considerations, including: 1) the retina is part of the CNS that develops out of the same tissue as the brain and shares many features (e.g., neurons and neurotransmitters, a layered architecture); 2) thinning of retinal neural and vascular layers has been identified in a range of neuropsychiatric disorders (e.g., Alzheimer’s disease, Parkinson’s disease, multiple sclerosis, traumatic brain injury) where it is correlated with, and often precedes, features such as brain volume loss, cognitive decline, and overall illness progression (reviewed in Silverstein et al, 2020a); 3) retinal thinning has been consistently observed in schizophrenia (reviewed in Silverstein et al, 2020b); but 4) findings regarding which layers demonstrate thinning have been inconsistent; and 5) partly as a result of this inconsistency, the overall effect sizes from between-group comparisons (e.g., schizophrenia vs. healthy control) are small or very small for all variables that have been measured to date (Kazakos & Karageorgiou, 2020; Silverstein et al, 2020b). This situation suggests two potential hypotheses and directions.…”

Section: Introductionmentioning

confidence: 99%

“…This situation suggests two potential hypotheses and directions. One is that while thinning of retinal layers is reliably observed in schizophrenia, the specific layer(s) that are affected may be significantly determined by stochastic factors that are independent of the illness itself, as is thought to occur regarding the specific site of epileptic foci (Silverstein et al, 2020a). A second is that abnormalities in retinal structure in schizophrenia may be better characterized by variables other than overall thickness or volume.…”

Section: Introductionmentioning

confidence: 99%

Using Machine Learning to Classify Schizophrenia Based on Retinal Images

Joseph

Lai

Silverstein

et al. 2021

Preprint

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Objectives: Thinning of retinal layers has been documented in patients with chronic schizophrenia using standard metrics of optical coherence tomography (OCT) devices. We demonstrate the effectiveness of machine learning (ML) techniques to differentiate between schizophrenia patients and healthy controls using OCT images. Methods: Features extracted from a convolutional neural network (CNN) designed to segment retinal layers from OCT images represented abstracted data from the OCT images of 14 first episode (FEP) and 18 chronic schizophrenia patients, and their respective 20 and 18 age-matched controls. The abstracted data and OCT machine metrics were used separately to train support vector classification (SVC) models to differentiate between control and schizophrenia samples and test them. Results: SVCs operating on OCT machine metrics did not classify unseen samples of FEP schizophrenia patients and controls with performance better than chance, while those looking at chronic schizophrenia did, paralleling results obtained using parametric statistics. In contrast, SVCs operating on OCT image data extracted from the CNN classified unseen samples from both populations with performance greater than chance. Conclusion: These results suggest that ML techniques can detect patterns in patients with FEP schizophrenia with greater performance using features extracted from OCT images than metrics provided by OCT machines.

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Measures of Retinal Structure and Function as Biomarkers in Neurology and Psychiatry

Cited by 41 publications

References 392 publications

Perceptual Gains and Losses in Synesthesia and Schizophrenia

Perceptual Gains and Losses in Synesthesia and Schizophrenia

Melatonin mitigates disrupted circadian rhythms, lowers intraocular pressure, and improves retinal ganglion cells function in glaucoma

Using Machine Learning to Classify Schizophrenia Based on Retinal Images

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