Publications

Book Chapters and Volumes

M.D. Schirmer, A. Venkataraman, I. Rekik, M. Kim and A. Wern Chung (Eds.). Connectomics in NeuroImaging: MICCAI Workshops, ShenZhen, China, October 2019.

A. Venkataraman. Autism Spectrum Disorders: Unbiased Functional Connectomics Provide New Insights into a Multifaceted Neurodevelopmental Disorder. Connectomics: Methods, Mathematical Models and Applications, Eds. B. Munsel, G. Wu, and P. Laurienti, 2018.

T. Schultz, G. Nedjati-Gilani, A. Venkataraman, L. O’Donnell and E. Panagiotaki (Eds.). Computational Diffusion MRI and Brain Connectivity: MICCAI Workshops, Nagoya, Japan, January 2014.

 

Journal Articles

N.S. D’Souza, N. Wymbs, M.B. Nebel, S. Mostofsky and A. Venkataraman. A Joint Network Optimization Framework to Predict Clinical Severity from Resting State fMRI Data. Under Revision for NeuroImage, 2019.

J. Craley, E. Johnson, A. Venkataraman. A Spatio-Temporal Model of Seizure Propagation in Focal Epilepsy. Under Revision for IEEE Transactions on Medical Imaging, 2019.

D. Rangaprakash, M.N. Dretsch, A. Venkatraman, J.S. Katz, T.S. Denney Jr. and G. Deshpande. Identifying Disease Foci from Static and Dynamic Effective Connectivity Networks: Illustration in Soldiers with Trauma. Hum Brain Map, 39(1): 264-287, 2018.

S. Zhao, D. Rangaprakash, A. Venkataraman, P. Liang and G. Deshpande. Investigating Focal Connectivity Decits in Alzheimer’s Disease using Directional Brain Networks Derived from Resting-State fMRI. Frontiers on Aging Neurosci, 9: 1-12, 2017.

S. van Noordt, J. Wu, A. Venkataraman, M.J. Larson, M. South and M.J. Crowley. Inter-trial Coherence of Medial Frontal Theta Oscillations Linked to Differential Feedback Processing in High-Functioning Autism. Res in Autism Spect Disorders, 33:1-10 2017.

A. Venkataraman, D. Yang, N. Dvornek, L.H. Staib, J.S. Duncan, K.A. Pelphrey and P. Ventola. Pivotal Response Treatment Prompts a Functional Rewiring of the Brain Among Individuals with Autism Spectrum Disorder. NeuroReport, 27:1081-1085, 2016.

D. Yang, K.A. Pelphrey, D.G. Sukhodolsky, M.J. Crowley, E. Dayan, N. Dvornek, A. Venkataraman , J.S Duncan, L.H. Staib and P. Ventola. Brain Responses to Biological Motion Predict Treatment Outcome in Young Children with Autism. Translational Psychiatry, 6(11):e948 2016.

A. Venkataraman, D. Yang, K.A. Pelphrey and J.S. Duncan. Bayesian Community Detection in the Space of Group-Level Functional Differences. IEEE Transactions on Medical Imaging, 35(8):1866-1882, 2016..

A. Venkataraman, J.S. Duncan, D. Yang and K.A. Pelphrey. An Unbiased Bayesian Approach to Functional Connectomics Implicates Social-Communication Networks in Autism. NeuroImage Clinical, 8:356-366, 2015.

A. Venkataraman, M. Kubicki and P. Golland. From Brain Connectivity Models to Region Labels: Identifying Foci of a Neurological Disorder. IEEE Transactions on Medical Imaging, 32(11):2078-2098, 2013.

A. Venkataraman, T.J. Whitford, C-F. Westin, P. Golland and M. Kubicki Whole Brain Resting State Functional Connectivity Abnormalities in Schizophrenia. Schizophrenia Research, 139(1-3):7-12, 2012.

A. Venkataraman, Y. Rathi, M. Kubicki, C-F. Westin and P. Golland. Joint Modeling of Anatomical and Functional Connectivity for Population Studies. IEEE Transactions on Medical Imaging, 31(2):191-199, 2012.

K.R.A. Van Dijk, T.Hedden, A. Venkataraman, K.C. Evans, S.W. Lazar and R.L. Buckner. Intrinsic Functional Connectivity As a Tool For Human Connectomics: Theory, Properties, and Optimization. Journal of Neurophysiology, 103(1):297-321, 2010.

 

Peer-Reviewed Conference Papers

N. Nandakumar, K. Manzoor, J. Pillai, S. Gujar, H. Sair, and A. Venkataraman. A Novel Graph Neural Network to Localize Eloquent Cortex in Brain Tumor Patients from Resting-State fMRI Connectivity. In Proc. CNI: Connectomics in Neuroimaging, LNCS 11848:10-20, 2019. Selected for an Oral Presentation; Best Paper Award

N.S. D’Souza, N. Wymbs, M.B. Nebel, S. Mostofsky and A. Venkataraman. Integrating Neural Networks and Dictionary Learning for Multidimensional Clinical Characterizations from Functional Connectomics Data. In Proc. MICCAI: Medical Imaging Computing and Computer Assisted Intervention, LNCS 11766:709-717, 2019.

J. Craley, C. Jouny, E. Johnson and A. Venkataraman. Automated Noninvasive Seizure Detection and Localization Using Switching Markov Models and Convolutional Neural Networks. In Proc. MICCAI: International Conference on Medical Image Computing and Computer Assisted Intervention, LNCS 11767:253-262, 2019. Selected for Early Acceptance

S. Ghosal, Q. Chen, A.L. Goldman, W. Ulrich, K.F. Berman, D.R. Weinberger, V.S. Mattay and A. Venkataraman. Bridging Imaging, Genetics, and Diagnosis in a Coupled Low-Dimensional Framework. In Proc. MICCAI: International Conference on Medical Image Computing and Computer Assisted Intervention, LNCS 11767:647-655, 2019. Selected for Early Acceptance

R. Shankar, J. Sager and A. Venkataraman. A Multi-Speaker Emotion Morphing Model Using Highway Networks and Maximum Likelihood Objective. In Proc. Interspeech: Conference of the International Speech Communication Association, 2848-2852, 2019. Selected for an Oral Presentation

J. Sager, R. Shankar, J. Reinhold, and A. Venkataraman. VESUS: A Crowd-Annotated Database to Study Emotion Production and Perception in Spoken English. In Proc. Interspeech: Conference of the International Speech Communication Association, 316-320, 2019. Selected for an Oral Presentation

R. Shankar, J. Sager, H.-W. Hsieh, N. Charon and A. Venkataraman. Automated Emotion Morphing in Speech Based on Diffeomorphic Curve Registration and Highway Networks. In Proc. Interspeech: Conference of the International Speech Communication Association, 4499-4503, 2019.

R. Shankar and A. Venkataraman. Weakly Supervised Syllable Segmentation by Vowel-Consonant Peak Classification. In Proc. Interspeech: Conference of the International Speech Communication Association, 644-648, 2019.

N.S. D’Souza, N. Wymbs, M.B. Nebel, S. Mostofsky and A. Venkataraman. A Coupled Manifold Optimization Framework to Jointly Model the Functional Connectomics and Behavioral Data Spaces. In Proc. IPMI: Information Processing in Medical Imaging, LNCS 11492:605–616, 2019.

J. Craley, E. Johnson, A. Venkataraman. Integrating Convolutional Neural Networks and Probabilistic Graphical Modeling for Epileptic Seizure Detection in Multichannel EEG. In Proc. IPMI: Information Processing in Medical Imaging, LNCS 11492:291–303, 2019.  Selected for Oral Presentation

S. Ghosal, Q. Chen, A.L. Goldman, W. Ulrich, D.R. Weinberger, V.S. Mattay and A. Venkataraman. A Generative-Predictive Framework to Capture Altered Brain Activity in fMRI and its Association with Genetic Risk: Application to Schizophrenia. In Proc. SPIE Medical Imaging, col. 10949, 2019.

N. Nandakumar, N.S. D’Souza, J. Craley, K. Manzoor, J. Pillai, S. Gujar, H. Sair, A. Venkataraman. Defining Patient Specific Functional Parcellations in Lesional Cohorts via Markov Random Fields. In Proc. CNI: Connectomics in Neuroimaging, LNCS 11083:88-98, 2018. Selected for Oral Presentation

N.S. D’Souza, N. Wymbs, M.B. Nebel, S. Mostofsky and A. Venkataraman. A Generative-Discriminative Basis Learning Framework to Predict Clinical Severity from Resting State Functional MRI Data. In Proc. MICCAI: International Conference on Medical Image Computing and Computer Assisted Intervention, LNCS 11072:163-
171, 2018. Selected for Early Acceptance

J. Craley, E. Johnson, A. Venkataraman. A Novel Method for Epileptic Seizure Detection Using Coupled Hidden Markov Models. In Proc. MICCAI: International Conference on Medical Image Computing and Computer Assisted Intervention, LNCS 11072:482-489, 2018. Selected for Early Acceptance

A. Venkataraman, N. Wymbs, M.B. Nebel and S. Mostofsky. A Unified Bayesian Approach to Extract Network-Based Functional Differences from a Heterogeneous Patient Cohort. In Proc. CNI: International Workshop on Connectomics in Neuroimaging, pp. 1-10, 2017. Selected for Oral Presentation

N.C. Dvornek, D. Yang, A. Venkataraman, P. Ventola, L.H. Staib, K.A. Pelphrey and J.S. Duncan. Prediction of Autism Treatment Response from Baseline fMRI using Random Forests and Tree Bagging. In Proc. Multimodal Learning for Clinical Decision Support, pp. 1-8, 2016. Selected for Oral Presentation

A. Venkataraman, D. Yang, K.A. Pelphrey and J.S. Duncan. Community Detection in
the Space of Functional Abnormalities Reveals both Heightened and Reduced Brain Synchrony in Autism
. In Proc. BAMBI: Bayesian and Graphical Models for Biomedical Imaging, 1-12, 2015. Selected for Oral Presentation

A. Sweet*, A. Venkataraman*, S.M. Stufflebeam, H. Liu, N. Tanaka and P. Golland. Detecting Epileptic Regions Based on Global Brain Connectivity Patterns. In Proc. MICCAI: International Conference on Medical Image Computing and Computer Assisted Intervention, LNCS 8149:98-105, 2013. Selected for Oral Presentation *equal contribution by first two authors

A. Venkataraman, M. Kubicki and P. Golland. From Brain Connectivity Models to Identifying Foci of a Neurological Disorder. In Proc. MICCAI: International Conference on Medical Image Computing and Computer Assisted Intervention, LNCS 7510:697-704, 2012. Selected for Oral Presentation

A. Venkataraman, Y. Rathi, M. Kubicki, C-F. Westin and P. Golland. Joint Generative Model for fMRI/DWI and its Application to Population Studies. In Proc. MICCAI: International Conference on Medical Image Computing and Computer Assisted Intervention, LNCS 6361:191-199, 2010. Selected for Oral Presentation

A. Venkataraman, M. Kubicki, C-F. Westin and P. Golland. Robust Feature Selection in Resting-State fMRI Connectivity Based on Population Studies. In Proc. MMBIA: IEEE CS Workshop on Mathematical Methods in Biomedical Image Analysis, 2010.

A. Venkataraman, K.R.A Van Dijk, R.L. Buckner and P. Golland. Exploring Functional Connectivity in fMRI via Clustering. In Proc. ICASSP: IEEE International Conference on Acoustics, Speech and Signal Processing, pp.441-444, 2009.

P. Golland, D. Lashkari and A. Venkataraman. Spatial Patterns and Functional Profiles for Discovering Structure in fMRI Data. Invited paper. In Proc. Asilomar Conference on Signals, Systems and Computers, pp.1402-1409, 2008.

A. Venkataraman and A.V. Oppenheim, Signal Approximation using the Bilinear Transform, In Proc. ICASSP: IEEE International Conference on Acoustics, Speech and Signal Processing, pp.3729-3732, 2008.

 

Conference Abstracts

N.S. D’Souza, M.B. Nebel, N. Wymbs, S. Mostofsky, A. Venkataraman. A Joint Network Optimization Framework to Predict Clinical Severity from Resting-State Functional MRI Data. In Proc. Conference on Medical Imaging and Case Reports, 2019. Invited Talk

N.S. D’Souza, M.B. Nebel, N. Wymbs, S. Mostofsky, A. Venkataraman. A Joint Network Optimization Framework to Predict Clinical Severity from Resting-State Functional Connectomics. In Proc. Flux Congress, 2019.

A. Venkataraman, N.S. D’Souza, M.B. Nebel, N. Wymbs, S. Mostofsky. Predicting Behavior from Resting-State fMRI. In Proc. SAND9: Statistical Analysis of Neuronal Data, 2019. Young Investigator Spotlight Presentation

N.S. D’Souza, M.B. Nebel, N. Wymbs, S. Mostofsky, A. Venkataraman. A Generative-Discriminative Basis Learning Framework to Predict Autism Spectrum Disorder Severity. In Proc. ISBI: Intl Symposium on Biomedical Imaging, 2018.

N. Nandakumar, N.S. D’Souza, H. Sair, A. Venkataraman. A Modified K-Means Algorithm for Resting State FMRI Analysis of Brain Tumor Patients, As Validated by Language Localization. In Proc. ISBI: Intl Symposium on Biomedical Imaging, 2018.

J. Craley, E. Johnson, A. Venkataraman. Robust Seizure Detection Using Coupled Hidden Markov Models. In Proc. ISBI: Intl Symposium on Biomedical Imaging, 2018.

A. Venkataraman, J.S. Duncan, D. Yang and K.A. Pelphrey. Abnormal Functional Communities in Autism. In Proc: IMFAR: Intl Meeting For Autism Research, 2016.         Selected for Oral Presentation

D. Rangaprakash, G. Deshpande, A. Venkataraman, J.S. Katz, T.S. Denney and M.N. Dretsch. Identifying Foci of Brain Disorders from Effective Connectivity Networks. In Proc: ISMRM, 2016. Awarded an Honorable Mention

A. Venkataraman, J.S. Duncan, D. Yang and K.A. Pelphrey. An Unbiased Bayesian Approach to Functional Connectomics Implicates Social-Communication Networks in Autism. In Proc. ISBI: International Symposium on Biomedical Imaging, 2015.       Invited Abstract and Talk

S. Zhao, A. Venkataraman, P. Liang and G. Deshpande. Investigating the Role of Brain Stem in Alzheimer’s Disease using Directional Brain Networks derived from Resting State fMRI. In Proc: ISMRM, 2015.

A. Venkataraman, M. Kubicki and P. Golland. From Brain Connectivity Models to Identifying Foci of a Neurological Disorder. In Proc: 3rd Biennial Conference on Resting State Brain Connectivity, 2012.

A. Venkataraman, K.R.A Van Dijk, R.L. Buckner and P. Golland. Exploring Functional Connectivity in fMRI via Clustering. In Proc: Annual Meeting of the Organization of Human Brain Mapping, 2009.

 

Dissertations

R. Nandkarni. Examination of the Association Between Arterial Blood Pressure Below the Lower Limit of Autoregulation and Acute Kidney Injury After Cardiac Surgery. MS Thesis. Johns Hopkins University, Baltimore MD, 2019.

A. Venkataraman. Generative Models of Brain Connectivity for Population Studies. PhD Thesis. Massachusetts Institute of Technology, Cambridge MA, 2012.

A. Venkataraman. Signal Approximation Using the Bilinear Transform. MEng Thesis. Massachusetts Institute of Technology, Cambridge MA, 2007.