Daniel Herrera-Esposito

Daniel Herrera-Esposito

Computational Neuroscientist. Interested in the brain, math, computers, and sometimes epidemiology

Posts by Collection

portfolio

publications

Tyrosine oxidation and nitration in transmembrane peptides is connected to lipid peroxidation

Published in Archives of Biochemistry and Biophysics, 2017

Tyrosine nitration is an oxidative post-translational modification that can occur in proteins associated to hydrophobic bio-structures such as membranes and lipoproteins. In this work, we studied tyrosine nitration in membranes using a model system consisting of liposomes with pre-incorporated tyrosine-containing 23 amino acid transmembrane peptides.

Recommended citation: Silvina Bartesaghi, Daniel Herrera, Debora M. Martinez, Ariel Petruk, Veronica Demicheli, Madia Trujillo, Marcelo A. Marti, Dario A. Estrín, Rafael Radi (2017). "Tyrosine oxidation and nitration in transmembrane peptides is connected to lipid peroxidation " Archives of Biochemistry and Biophysics. 622.
Download Paper

Flexible contextual modulation of naturalistic texture perception in peripheral vision

Published in Journal of Vision, 2021

In this paper we use psychophysics experiments with Portilla-Simoncelli textures to show that texture segmentation affects contextual modulation in peripheral vision. This flexible contextual modulation cannot be accounted for by popular pooling models of crowding. We probe the relevance of different texture properties to contextual modulation, providing guidance for studying the neural mechanisms of flexible contextual modulation.

Recommended citation: Herrera-Esposito, D.; Coen-Cagli, R.; Gómez-Sena, L; (2021). "Flexible contextual modulation of naturalistic texture perception in peripheral vision" Journal of Vision.
Download Paper | Data and code

Redundancy between spectral and higher-order texture statistics for natural image segmentation

Published in Vision Research, 2021

In this paper we elaborate on out previous psychophysical findings that higher-order texture statistics are a secondary segmentation cue for humans, compared to spectral statistics. We analyze the contribution of both types of statistics to a natural image segmentation task and find that higher-order statistics are redundant with spectral statistics. We argue that this might explain their secondary role in human perception.

Recommended citation: Herrera-Esposito, D.; Gómez-Sena, L; Coen-Cagli, R. (2021). "Redundancy between spectral and higher-order texture statistics for natural image segmentation." Vision Research. 187
Download Paper | Data and code

Age-specific rate of severe and critical SARS-CoV-2 infections estimated with multi-country seroprevalence studies.

Published in BMC Infectious Diseases, 2022

In this paper we report the age-stratified proportion of SARS-CoV-2 infections that result in severe and critical disease. For this we use the gold standard of serological survey meta-analysis, and collected a unique dataset on hospitalizations and ICU admissions from publich health authorities around the world. We show that the risk of severe and critical disease increases exponentially with age, but much less steeply than the risk of fatal illness. This work has been cited in media outlets and in a United States House of Representatives hearing about school policies during COVID-19.

Recommended citation: Herrera-Esposito, D.; de los Campos, Gustavo. " Age-specific rate of severe and critical SARS-CoV-2 infections estimated with multi-country seroprevalence studies. " BMC Infectious Diseases. 22,311.
Download Paper | Data and code

Assesing the burden of COVID-19 in developing countries: systematic review, meta-analysis and public policy implications

Published in BMJ Global Health, 2022

In this paper, COVID-19 fatality is assessed in developing countries using the golden standard of seroprevalence studies meta-analysis. We find that the infection fatality rate is roughly 2 times higher than in high-income countries. This paper was featured in Nature News, Forbes, Quartz, and other news media.

Recommended citation: Andrew T Levin, Nana Owusu-Boaitey, Sierra Pugh, Bailey K Fosdick, Anthony B Zwi, Anup Malani, Satej Soman, Lonni Besançon, Ilya Kashnitsky, Sachin Ganesh, Aloysius McLaughlin, Gayeong Song, Rine Uhm, Daniel Herrera-Esposito, Gustavo de Los Campos, Ana Carolina Pecanha Peçanha Antonio, Enyew Birru Tadese, Gideon Meyerowitz-Katz (2022). "Assesing the burden of COVID-19 in developing countries: systematic review, meta-analysis and public policy implications." BMJ Global Health. 7.
Download Paper | Data and code

Contact tracing-induced Allee effect in disease dynamics

Published in Journal of Theoretical Biology, 2022

In this paper we modeled the interaction between non-pharmaceutical interventions for SARS-CoV-2 (e.g. contact tracing) and the number of infected individuals in a population. We find connections between the resulting dynamics and the Allee effect from ecology, and discuss the implications for epidemic management.

Recommended citation: Arim, Matı́as; Herrera-Esposito, D.; Bermolen, Paola; Cabana, Álvaro; Fariello, Marı́a Inés; Lima, Mauricio; Romero, Héctor (2022) . " Contact tracing-induced Allee effect in disease dynamics" Journal of Theoretical Biology. 542.
Download Paper | Data and code

Dynamics of SARS-CoV-2 seroassay sensitivity: a systematic review and modeling study

Published in Eurosurveillance, 2023

In this paper we did a systematic meta-analysis of the SARS-CoV-2 serological literature to collect a dataset on how assay sensitivity changes with time after infection. We report that assay characterisics are an essential determinant of sensitivity dynamics, and discuss the potential biases that this introduces in the literature.

Recommended citation: Nana Owusu-Boaitey, Timothy W Russell, Gideon Meyerowitz-Katz, Andrew T Levin, Daniel Herrera-Esposito (2023). " Dynamics of SARS-CoV-2 seroassay sensitivity: a systematic review and modeling study ." Eurosurveillance. 28(21).
Download Paper | Data and code

Optimal motion-in-depth estimation with natural stimuli

Published in bioRxiv, 2024

In this paper we trained ideal observer models to estimate 3D motion from naturalistic binocular video clips. We show that the resulting ideal observer exhibit non-obvious behaviors that are similar to those reported in human psychophysics.

Recommended citation: Herrera-Esposito, D.; Burge, J (2024). " Optimal motion-in-depth estimation with natural stimuli." bioRxiv.
Download Paper | Data and code

talks

Crowding of naturalistic visual textures

Published:

Summary statistics representations of visual inputs are used to model visual texture perception. These type of representations are also used to model visual crowding in peripheral vision, in the so called texture-tiling model of peripheral vision. Here we probe visual crowding using naturalistic textures, to test how well the texture-tiling model can account for perceptual organization in crowding. Slides

Age-stratified severe and critical infection rates to estimate COVID-19 under-ascertainment

Published:

Underascertainment of SARS-CoV-2 infections is a common problem during the COVID-19 pandemic. Estimating the degree of underascertainment can be challenging, but it is useful for guiding public health responses. Here we estimate underascertainment across time for Uruguay during 2020, adapting a method developed by Russell et al. (2020) to incorporate age-stratified case reports, as well as for using hospitalization and ICU admission data. Video

A geometric analysis of task-specific natural image statistics

Published:

There is growing interest in the geometric analyses of representations in biological and artificial neural systems. Generally, these analyses do not consider the stochastic nature of the representations. Here, we use differential geometry to analyze the geometry of response statistics in a simple ideal observer model to naturalistic images across different visual tasks. We find that different information geometric structures are required for different analysis goals. Slides

teaching

Biochemistry for medical students

Undergraduate, Faculty of Medicine, Universidad de la Republica, 2013

2013-2016. I was a teaching assistant in 1st and 3rd year biochemistry courses for medical students (note: Medical School is 7 years long in Uruguay, with years 1 to 3 being equivalent to pre-med undergraduate studies). I taught topics in physical chemistry, biochemistry and human physiology. I also led and organized practical laboratory classes on a variety of topics. This teaching was done in the context of my teaching position at the Biochemistry Department of the Faculty of Medicine.

Molecular and cellular neuroscience

Undergraduate, Faculty of Sciences, Universidad de la Republica, 2017

2017-2022. I taught lectures, led discussion groups, and designed and led a 3-class neuron biophysics simulation lab in this course for advanced biology and biochemistry students. I taught lectures on the biophysical underpinnings of neuronal electrophysiology, and led the simulation labs using the NEURON simulator to explore these biophysical principles.

Milestones and Myths of the Brain

Undergraduate, Faculty of Sciences, Universidad de la Republica, 2017

2017-2024. I teach a lecture and a discussion class about perception science in this course for first and second year biology students. I also wrote a chapter for the book by the same name as the course, published by the course coordinators. The chapter, found here, is titled Is the world as we see it? and discusses broad concepts in perception and neuroscience, accessible to a general educated audience.

Systems and Circuit Neuroscience

Undergraduate, Faculty of Sciences, Universidad de la Republica, 2017

2017-2022. I taught several lectures and a psychophysics tutorial in this course for advanced biology and biochemistry students. I taught the course lectures on the Cerebellum, Basal Ganglia, Visceral motor control, Memory and Learning, Information Theory and Neural Coding, and a tutorial on psychophysical data analysis.

Tutorial: Advanced statistics for Systems Neuroscience

Graduate course, Faculty of Sciences, Universidad de la Republica, 2021

2021. I taught an invited lecture on data analysis in the Systems Neuroscience graduate course, where I where I introduced students to generalized linear models, and mixed models for data analysis. Slides

Tutorial: Mathematical methods for Cognitive Science

Graduate, Faculty of Sciences, Universidad de la Republica, 2021

2021. I taught an invited lecture on dynamical systems modeling for the masters course “Mathematical methods for Cognitive Science”. I used modeling of epidemic dynamics as an example, and designed and implemented a Jupyter notebook to teach the class. (Link to Jupyter notebook).

Basic Machine Learning for Scientists

Graduate, Faculty of Engineering, Universidad de la Republica, 2021

2021. I was a teaching assistant in the first edition of this 7-week graduate course. I designed and implemented, with the other TA, the notebooks for the practical classes (link to notebooks), that include the course evaluations, and we led those classes. Course website