Pablo Polosecki  Pablo Polosecki photo         

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Research Staff Member
Thomas J. Watson Research Center, Yorktown Heights, NY USA


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Learning Brain Dynamics with Coupled Low-Dimensional Nonlinear Oscillators and Deep Recurrent Networks
Germ\'an Abrevaya, Guillaume Dumas, Aleksandr Y Aravkin, Peng Zheng, Jean-Christophe Gagnon-Audet, James Kozloski, Pablo Polosecki, Guillaume Lajoie, David Cox, Silvina Ponce Dawson, others
Neural Computation, 1--40, 2021


Loss of nucleus accumbens low-frequency fluctuations is a signature of chronic pain
Meena M Makary, Pablo Polosecki, Guillermo A Cecchi, Ivan E DeAraujo, Daniel S Barron, Todd R Constable, Peter G Whang, Donna A Thomas, Hani Mowafi, Dana M Small, Paul Geha
Proceedings of the National Academy of Sciences, 2020

Resting-state connectivity stratifies premanifest Huntington's disease by longitudinal cognitive decline rate
Pablo Polosecki, Eduardo Castro, Irina Rish, Dorian Pustina, John H. Warner, Andrew Wood, Cristina Sampaio, and Guillermo Cecchi
Scientific Reports 10, 1252 (2020)


Unsupervised Morphological Segmentation for Detecting Parkinsons Disease
Elif Eyigoz, Pablo Polosecki, Adolfo M. Garcia, Katharina Rogg, Juan Rafael Orozco-Arroyave, Sabine Skodda, Eugenia Hesse, Agustin Ibanez, Guillermo A. Cecchi
AAAI Workshops, pp. 126-131, 2018
segmentation, parkinson s disease, machine learning, computer science, artificial intelligence

Learning Nonlinear Brain Dynamics: van der Pol Meets LSTM
German Abrevaya, Aleksandr Aravkin, Guillermo Cecchi, Irina Rish, Pablo Polosecki, Peng Zheng, Silvina Dawson
arXiv:1805.09874 [stat.ML], 2018

Baseline multimodal information predicts future motor impairment in premanifest Huntington's disease
Eduardo Castro, Pablo Polosecki, Irina Rish, Dorian Pustina, John H Warner, Andrew Wood, Cristina Sampaio, Guillermo A Cecchi
NeuroImage: Clinical19, 443--453, Elsevier, 2018

Unsupervised Morphological Segmentation for Detecting Parkinson’s Disease
Elif Eyigoz, Pablo Polosecki, Adolfo M Garcia, Katharina Rogg, Juan Orozco-Arroyave, Sabine Skodda, Eugenia Hesse, Agustin Ibanez, Guillermo Cecchi
Workshops at the Thirty-Second AAAI Conference on Artificial Intelligence, 2018


Learning discriminative functional network features of schizophrenia
Mina Gheiratmand, Irina Rish, Guillermo Cecchi, Matthew Brown, Russell Greiner, Pouya Bashivan, Pablo Polosecki, Serdar Dursun
Medical Imaging 2017: Biomedical Applications in Molecular, Structural, and Functional Imaging, pp. 101371A

Computational psychiatry: Advancing predictive modeling of neurodegeneration with neuroimaging of Huntington's disease
Pablo Polosecki, Eduardo Castro, Andrew Wood, John H Warner, Irina Rish, Guillermo A Cecchi
IBM Journal of Research and Development 61(2/3), 4--1, IBM, 2017

Learning stable and predictive network-based patterns of schizophrenia and its clinical symptoms
Mina Gheiratmand, Irina Rish, Guillermo A Cecchi, Matthew RG Brown, Russell Greiner, Pablo I Polosecki, Pouya Bashivan, Andrew J Greenshaw, Rajamannar Ramasubbu, Serdar M Dursun
NPJ schizophrenia 3(1), 22, Nature Publishing Group, 2017



Faces in motion: selectivity of macaque and human face processing areas for dynamic stimuli
Pablo Polosecki, Sebastian Moeller, Nicole Schweers, Lizabeth M Romanski, Doris Y Tsao, Winrich A Freiwald
Journal of Neuroscience 33(29), 11768--11773, Soc Neuroscience, 2013


Parsing a perceptual decision into a sequence of moments of thought
Martin Graziano, Pablo Polosecki, Diego Edgar Shalom, Mariano Sigman
Frontiers in integrative neuroscience5, 45, Frontiers, 2011


Synthesis of carbon nanotubes by CVD: Effect of acetylene pressure on nanotubes characteristics
Mariano Escobar, M Sergio Moreno, Roberto J Candal, M Claudia Marchi, Alvaro Caso, Pablo Polosecki, Gerardo H Rubiolo, Silvia Goyanes
Applied Surface Science 254(1), 251--256, Elsevier, 2007

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