Pablo Polosecki photo Jenna M Reinen photoIrina Rish photo

Neuroimaging Publications


Learning Representations from EEG with Deep Recurrent-Convolutional Neural Networks
Pouya Bashivan, Irina Rish, Mohammed Yeasin, Noel Codella
ICLR 2016 : International Conference on Learning Representations 2016

Evaluating Effects of Methylphenidate on Brain Activity in Cocaine Addiction: A Machine-Learning Approach
Irina Rish, Pouya Bashivan, Guillermo A. Cecchi, Rita Z. Goldstein
SPIE Medical Imaging, 2016


Turing a la Freud: Test for an Automated Psychiatrist
G.A. Cecchi and I. Rish
Beyond the Turing Test - AAAI 2015 Workshop

Mental State Recognition via Wearable EEG
Pouya Bashivan, Irina Rish, Steve Heisig
NIPS Workshop on Machine Learning and Interpretation in Neuroimaging (MLINI2015)


Reliability Estimation and Enhancement via Spatial Smoothing in Sparse fMRI Modeling
Carroll, Melissa K., Guillermo A. Cecchi, Irina Rish, Rahul Garg, Marwan Baliki, and A. Vania Apkarian
Practical Applications of Sparse Modeling, pp. 123-150, MIT Press, 2014


Schizophrenia as a network disease: disruption of emergent brain function in patients with auditory hallucinations
I. Rish, G. Cecchi, B. Thyreau, B. Thirion, M. Plaze, M. L. Paillere-Martinot, C. Martelli, J. L. Martinot, J. B. Poline
PLoS ONE 8(1), e50625, 2013

Functional MRI Analysis with Sparse Models
I. Rish
Invited paper at NECTAR track of the European Conference on Machine Learning (ECML-2013)

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


Variable Selection for Gaussian Graphical Models
Jean Honorio, Dimitris Samaras, Irina Rish, Guillermo Cecchi

Schizophrenia classification using functional network features
Irina Rish, Guillermo A Cecchi, Kyle Heuton
SPIE Medical Imaging, pp. 83170W--83170W, 2012

Predictive dynamics of human pain perception
G. A. Cecchi, L. Huang, J. A. Hashmi, M. Baliki, M. V. Centeno, I. Rish, A. V. Apkarian
PLoS Comput. Biol. 8(10), e1002719, 2012

Sparse regression analysis of task-relevant information distribution in the brain
Irina Rish, Guillermo A Cecchi, Kyle Heuton, Marwan N Baliki, A Vania Apkarian
SPIE Medical Imaging, 2012


Adult neurogenesis as efficient sparsification
I. Rish, G. Cecchi, A. Lozano, R. Rao
Neuroscience 2011 (SfN meeting), November 12-16

Parsing a perceptual decision into a sequence of moments of thought
Graziano, Mart{'i}n and Polosecki, Pablo and Shalom, Diego Edgar and Sigman, Mariano
Frontiers in integrative neuroscience5, 45, Frontiers, 2011


Learning sparse Gaussian Markov networks using a greedy coordinate ascent approach
Katya Scheinberg, Irina Rish
European Conference on Machine Learning and Knowledge Discovery in Databases (ECML-PKDD), pp. 196--212, Springer, 2010

Sparse regression models of pain perception
Irina Rish, Guillermo A Cecchi, Marwan N Baliki, A Vania Apkarian
Brain Informatics, pp. 212--223, Springer, 2010

Sparse Markov Net Learning with Priors on Regularization Parameters
Katya Scheinberg, Irina Rish, Narges Bani Asadi
in Proceedings of The Eleventh International Symposium on Artificial Intelligence and Mathematics (ISAIM 2010), pp. 112--122


Prediction and interpretation of distributed neural activity with sparse models
Melissa K Carroll, Guillermo A Cecchi, Irina Rish, Rahul Garg, A Ravishankar Rao
NeuroImage 44(1), 112--122, Elsevier, 2009


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