MEYE: Web App for Translational and Real-Time Pupillometry

Mazziotti, Raffaele; Carrara, Fabio; Viglione, Aurelia; Lupori, Leonardo; Verde, Luca Lo; Benedetto, Alessandro; Ricci, Giulia; Sagona, Giulia; Amato, Giuseppe; Pizzorusso, Tommaso

doi:10.1523/eneuro.0122-21.2021

Cited by 14 publications

(7 citation statements)

References 53 publications

Supporting

Mentioning

Contrasting

Order By: Relevance

“…3 B). Pupillometry was performed using MEYE Deep Learning tool (24). During pupillometry the animal was exposed to the following stimuli: a mean luminance uniform gray screen, a VR isoluminant stimulus composed of a virtual reality corridor moving coherently with the animal movement to elicit an orienting response (OR, Fig.…”

Section: Resultsmentioning

confidence: 99%

“…Pupillometry is a non-invasive, quantitative and fully translational tool already used in clinical practice that requires minimal collaboration by the subject, and it has been used even in newborns and preterm infants at postpartum age of 1 day (38). Recently developed methods are opening the possibility to perform these measurements in a clinical and a domestic environment (24). Since early diagnosis is essential to evaluate treatment outcomes and pupillary measures can be performed quickly, also in preverbal subjects, we propose the monitoring of resting state and OR pupillometry as a promising and practical biomarker for CDD.…”

Section: Discussionmentioning

confidence: 99%

See 1 more Smart Citation

Behavioral impulsivity is associated with pupillary alterations and hyperactivity in CDKL5 mutant mice

Viglione

Sagona

Carrara

et al. 2022

Human Molecular Genetics

Self Cite

View full text Add to dashboard Cite

Cyclin-dependent kinase-like 5 (Cdkl5) deficiency disorder (CDD) is a severe neurodevelopmental condition caused by mutations in the X-linked Cdkl5 gene. CDD is characterized by early-onset seizures in the first month of life, intellectual disability, motor and social impairment. No effective treatment is currently available and medical management is only symptomatic and supportive. Recently, mouse models of Cdkl5 disorder have demonstrated that mice lacking Cdkl5 exhibit autism-like phenotypes, hyperactivity, and dysregulations of the arousal system, suggesting the possibility to use these features as translational biomarkers. In this study, we tested Cdkl5 male and female mutant mice in an appetitive operant conditioning chamber to assess cognitive and motor abilities, and performed pupillometry to assess the integrity of the arousal system. Then, we evaluated the performance of artificial intelligence models to classify the genotype of the animals from the behavioral and physiological phenotype. The behavioral results show that CDD mice display impulsivity, together with low levels of cognitive flexibility and perseverative behaviors. We assessed arousal levels by simultaneously recording pupil size and locomotor activity. Pupillometry reveals in CDD mice a smaller pupil size and an impaired response to unexpected stimuli associated with hyperlocomotion, demonstrating a global defect in arousal modulation. Finally, machine learning reveals that both behavioral and pupillometry parameters can be considered good predictors of CDD. Since early diagnosis is essential to evaluate treatment outcomes and pupillary measures can be performed easily, we proposed the monitoring of pupil size as a promising biomarker for CDD.

show abstract

Section: Resultsmentioning

confidence: 99%

Section: Discussionmentioning

confidence: 99%

Behavioral impulsivity is associated with pupillary alterations and hyperactivity in CDKL5 mutant mice

Viglione

Sagona

Carrara

et al. 2022

Human Molecular Genetics

Self Cite

View full text Add to dashboard Cite

show abstract

“…An example is the open source MEYE tool which uses convolutional neural networks to detect and measure real-time changes in pupil size both in humans and animals. 16 Unfortunately, we could not integrate it with our device because the MEYE tool is designed for evaluation of one pupil at a time and could not identify both pupils from our camera design. Our custom designed software allows user friendly immediate post recording measurement of the pupil diameter with excellent reproducibility and high degree of accuracy.…”

mentioning

confidence: 99%

Pilot Study of Smartphone Infrared Pupillography and Pupillometry

Solyman

Abushanab

Carey

et al. 2022

OPTH

View full text Add to dashboard Cite

To describe and validate a novel portable smartphone-based infrared pupillographer. Materials and Methods: A prototype infrared smartphone pupillographer device was custom designed for this project. Infrared video and photo pupillography were attempted on 12 patients with different clinical pupillary examination findings. Captured pupillography media files were assessed by three masked investigators, and the agreement between their qualitative clinical evaluation was tested against the evaluation of the neuro-ophthalmologist who performed the real-time examination and pupillography. Quantitative measurements of the pupillary diameter were performed by three investigators using a custom designed smartphone application on three different smartphones and on a personal computer. Measurements obtained by the three investigators using the smartphone and the desktop computer were compared. Results: Infrared video pupillography of high quality was successfully captured for light and near pupillary reflexes, and infrared still photographs were obtained in light and dark conditions in 23 eyes of the 12 patients. Examination findings included relative afferent pupillary defect (n = 5), normal pupillary examination (n = 4), anisocoria (n = 2), and relative afferent pupillary reflex by reverse (n = 1). There was 100% agreement in the qualitative pupillary evaluation of the masked investigators compared with real time clinical examination. Quantitative measurements of pupillary size obtained on the smartphone and desktop computer showed excellent agreement among the three investigators with intraclass correlation (ICC) coefficient ranging from 0.982-0.986 (P<0.001) and 0.995 (P<0.001) for the smartphone and the desktop computer groups, respectively. Level of agreement ranged between −0.27 and 0.32. Mean pupil diameter errors were 0.03 ± 0.15 mm between groups (P = 0.248). Conclusion:This pilot study demonstrates the feasibility of smartphone-based infrared pupillography for high quality photo and video documentation of pupillary examination at the bedside and in the clinic with accurate and reproducible measurements of the pupillary size in light and dark conditions.

show abstract

“…ivadomed [60] Neuroimaging Img (2D, 3D) No Class., Segm. MEYE [61] Oculography Img, Vid Yes Segm. Allen Cell Structure Segmenter [62] Microbiology, Histology Img (3D-fluor.…”

Section: Imgmentioning

confidence: 99%

An overview of open source Deep Learning-based libraries for Neuroscience

Tshimanga¹,

Atzori²,

Pup³

et al. 2023

Preprint

View full text Add to dashboard Cite

In recent years, deep learning revolutionized machine learning and its applications, producing results comparable to human experts in several domains, including neuroscience. Each year, hundreds of scientific publications present applications of deep neural networks for biomedical data analysis. Due to the fast growth of the domain, it could be a complicated and extremely time-consuming task for worldwide researchers to have a clear perspective of the most recent and advanced software libraries. This work contributes to clarify the current situation in the domain, outlining the most useful libraries that implement and facilitate deep learning application to neuroscience, allowing scientists to identify the most suitable options for their research or clinical projects. This paper summarizes the main developments in Deep Learning and their relevance to Neuroscience; it then reviews neuroinformatic toolboxes and libraries, collected from the literature and from specific hubs of software projects oriented to neuroscience research. The selected tools are presented in tables detailing key features grouped by domain of application (e.g. data type, neuroscience area, task), model engineering (e.g. programming language, model customization) and technological aspect (e.g. interface, code source). The results show that, among a high number of available software tools, several libraries are standing out in terms of functionalities for neuroscience applications. The aggregation and discussion of this information can help the neuroscience community to devolop their research projects more efficiently and quickly, both by means of readily available tools, and by knowing which modules may be improved, connected or added.

show abstract

MEYE: Web App for Translational and Real-Time Pupillometry

Cited by 14 publications

References 53 publications

Behavioral impulsivity is associated with pupillary alterations and hyperactivity in CDKL5 mutant mice

Behavioral impulsivity is associated with pupillary alterations and hyperactivity in CDKL5 mutant mice

Pilot Study of Smartphone Infrared Pupillography and Pupillometry

An overview of open source Deep Learning-based libraries for Neuroscience

Contact Info

Product

Resources

About