View Posters

Select posters below to view. Clicking on the poster title displays a preview of the poster.

Classification and Predictive Modeling
Preview	Poster No	Title	Authors
	M002	Machine Learning Guided Neurofunctional Markers for High-Functioning Autism Spectrum Disorder	Sheeba Arnold Anteraper¹^,2, Kaustubh Patil³^,4, Xavier Guell²^,5, Gagan Joshi²^,6
	M071	Using ROI functional connectivity during attention to classify schizophrenia and its familial risk	Linda Antonucci¹, Nora Penzel¹, Giulio Pergola², Lana Kambeitz-Ilankovic¹, Shalaila Haas¹, Joseph Kambeitz¹, Leonardo Fazio², Grazia Caforio³, Giuseppe Blasi², Alessandro Bertolino², Nikolaos Koutsouleris¹
	M081	Comparison of two brain parcellations in functional-connectivity-based classification of psychosis	Johanna Weiske¹, Shalaila Haas¹^,2, Anne Ruef¹, Linda Betz¹, Giulio Pergola³, Nikolaos Koutsouleris¹, Lana Kambeitz-Ilankovic¹, Linda Antonucci¹^,3
	M158	Patterns of cortical thickness in prodromal stage of synucleinopathies: a cluster analysis study	Malo Gaubert¹, Shady Rahayel¹, Ron Postuma¹, Jacques Montplaisir¹, Pierre-Alexandre Bourgouin¹, David Rémillard-Pelchat¹, Carrier Julie¹, Oury Monchi², Jean-François Gagnon¹
	M162	Machine-learning predictions of stroke recovery using quantitative tractography-based connectivity	Chun-Hung Yeh¹, Xiaoyun Liang¹, Chia-Lin Koh¹, Leeanne Carey¹^,2^,3, Alan Connelly¹^,2
	M176	Resting state effective connectivity extracts clinically relevant prognostic information in Stroke	MOHIT ADHIKARI¹, Joseph Griffis², Joshua Siegel², Gustavo Deco¹, Andrea Insabato¹, Matthieu Gilson¹, Maurizio Corbetta³
	M202	Deep Learning-based Detection of DSC-Defined Penumbral Tissue on pCASL in Acute Ischemic Stroke	Kai Wang¹, Qinyang Shou², Samantha Ma¹, David Liebeskind³, Xin Qiao⁴, Fabien Scalzo³, Jeffrey Saver³, Noriko Salamon⁴, Danny Wang⁵
	M230	Random Forest Regression to find White Matter Pathways Implicating Working Memory Scores in mTBI	Jhimli Mitra¹, Chitresh Bhushan¹, Soumya Ghose¹, Radhika Madhavan², Ek Tsoon Tan¹, Luca Marinelli¹, Joseph Masdeu³, Pratik Mukherjee⁴, Roland Lee⁵, Michael McCrea⁶, Gillian Hotz⁷, Michael Collins⁸, Anthony Kontos⁸, Teena Shetty⁹
	M233	Longitudinal changes in apparent diffusion coefficient value predicts prognosis for mTBI patients	Soumya Ghose¹, Radhika Madhavan², Chitresh Bhushan¹, Jhimli Mitra¹, Ek Tsoon Tan¹, Luca Marinelli¹, Joseph Masdeu³, Pratik Mukherjee⁴, Roland Lee⁵, Michael McCrea⁶, Gillian Hotz⁷, Michael Collins⁸, Anthony Kontos⁸, Teena Shetty⁹
	M294	Representations of emotion from the face, body and voice in the brain, an fMRI decoding study	Maarten Vaessen¹, Kiki Van der Heijden¹, Rebecca Watson¹, Beatrice de Gelder¹^,2
	M416	Predicting response to motor therapy in chronic stroke patients using Machine Learning	ceren tozlu¹, Dylan Edwards², Aaron Boes³, Douglas Labar⁴, K. Zoe Tsagaris⁵, Joshua Silverstein⁵, Heather Lane⁵, Mert Sabuncu⁶, Charles Liu⁷, Amy Kuceyeski⁸
	M419	High-order Laplacian Regularized Low-rank Representation for Brain Disease Diagnosis	Aimei Dong¹^,2, Mingliang Wang²^,3, Mingxia Liu², Dinggang Shen²
	M422	Intuitive visualization for convolutional neural networks detecting brain diseases in MRI scans	Eman Marzban¹^,2, Stefan Teipel²^,3, Martin Dyrba²
	M429	Discriminating neurofibromatosis and healthy children with multimodal MRI and machine learning	Federico Nemmi¹, Fabien Cignetti², Christine Assaiante³, Stéphanie Maziero¹, Frederique Audic⁴, Patrice Péran¹, Yves Chaix⁵
	M430	A whole-brain multimodal discrimination of Parkinson’s Disease, Multiple System Atrophy and Controls	Federico Nemmi¹, Anne Pavy-Le Traon², Phillips Owen³, Monique Galitzky³, Wassilios Meissner⁴, Olivier Rascol³, Patrice Péran¹
	M431	Trans-diagnostic/cross-stage neuroimaging markers for risk of schizophrenia and bipolar disorder	Hugo Schnack¹, Julia Binnewies¹, Nikita Setiaman¹, Neeltje van Haren², Rene Kahn², Manon Hillegers³
	M432	Can (un)supervised feature extraction classify Alzheimer patients better than whole-brain analysis?	Tom Wilderjans¹, Jeffrey Durieux¹, Marisa Koini², Frank de Vos¹, Tijn Schouten¹, Reinhold Schmidt², Mark de Rooij¹, Serge Rombouts¹
	M434	Early personalized treatment prediction model derived from subgroups in depression	Xinyi Wang¹^,2, Yurong Sun¹^,2, Huan Wang¹^,2, Rui Yan³, Shui Tian¹^,2, Hao Tang³, Zhijian Yao³^,4, Qing Lu¹^,2
	M438	Quantitative radiomic features in multisite AD: classification, longitude progress, biological basis	Kun Zhao¹^,2, Yanhui Ding¹, Ying Han³, Yong Fan², Tong Han⁴, Dan Jin²^,5, Bing Liu²^,5^,6, Jie Lu⁷, Chengyuan Song⁸, Pan Wang⁹^,10, Dawei Wang¹¹, Qin Wang¹¹, Kaibin Xu², Hongwei Yang⁷, Hongxiang Yao¹², Yuanjie Zheng¹, Chunshui Yu¹³, Bo Zhou¹⁰, Xinqing Zhang³, Yuying Zhou⁹, Tianzi Jiang²^,5^,6, Xi Zhang¹⁰, Yong Liu²^,5^,6
	M442	Classification of Multiple Sclerosis patients using a histogram-based K-Nearest Neighbors algorithm	Sana REBBAH¹^,2, Daniel Delahaye², Stéphane Puechmorel², Pierre Maréchal³, Florence Nicol², Isabelle Berry¹^,4
	M449	Longitudinal prediction of cognitive decline using multimodal MRI	Tijn Schouten¹^,2, Frank de Vos¹^,2, Sanneke van Rooden², Mark Bouts¹^,2, Rogier Feis¹^,2, Jessica Foster-Dingley², Justine Moonen², Roos van der Mast², Mark de Rooij¹, Jeroen van der Grond², Serge Rombouts¹^,2
	M451	Using Machine Learning to Predict Age and Dementia from Neural Frequency and Complexity Measures	Aleksi Ikkala¹, Tristan Bekinschtein², Richard Henson¹, Daniel Bor²
	M455	Altered structure of cerebellum in autism spectrum disorder: a new evidence from deep neural network	Chin-Hsuan Huang¹, Tien-Ruey Hsiang¹, Yi-Ping Chao²
	M475	Deep Chronnectome Learning Via Full Bidirectional Long Short-Term Memory for Schizophrenia Diagnosis	Weizheng Yan¹^,2, Vince Calhoun³, Tianzi Jiang¹^,2, Jing Sui¹^,2
	M476	Brain Age, A New Biomarker	Feng Sang¹, Yaojing Chen¹, Jianan Xia¹, Zhanjun Zhang¹
	M483	Classifying Major Depression Using GAN Based on Dynamic Functional Network Connectivity	Jianlong Zhao¹^,2, Dongmei Zhi¹^,2, Weizheng Yan¹^,2, Xiaohong Ma³^,4, Luxian Lv⁵^,6, Qing Ke⁷, Yongfeng Yang⁵^,6, Miao Pan³^,4, Xiao Yang³^,4, Vince Calhoun⁸, Jing Sui¹^,2^,9
	M486	Detecting Abnormal Functional Connectivity Patterns Using Stacked Autoencoders	Miguel Fernandes¹, Lília Jorge², Nádia Canário², Catarina Duarte², Miguel Castelo-Branco², Susana Novais-Santos¹, Pedro Almeida¹, Alexandre Andrade¹
	M488	Prediction of depression using multiple volumetric measures, subcortical regions and subfields	Thomas Vanicek¹, Alexander Kautzky¹, Gregor Gryglewski¹, Rene Seiger¹, Manfred Klöbl¹, Mathis Godbersen¹, Jakob Unterholzner¹, Murray Reed², Paul Michenthaler¹, Andreas Hahn¹, Siegfried Kasper¹, Rupert Lanzenberger¹
	M491	Multimodal integration of brain images for MRI based prediction of schizophrenia diagnosis	Raymond Salvador¹, Amalia Guerrero-Pedraza², Salvador Sarró³, Peter McKenna³, Edith Pomarol-Clotet⁴
	M504	Response To Treatment In Depression: Multi-class Predictive Utility Of Morphometric Features	Pradeep Reddy Raamana¹, Jee-su Suh², Stephen Arnott³, Benicio Frey², Stefanie Hassel⁴, Jacqueline Harris⁴, Mojdeh Zamyadi⁵, Raymond Lam⁶, Roumen Milev⁷, Daniel Mueller⁸, Susan Rotzinger⁹, Sidney Kennedy⁹, Glenda McQueen⁴, CAN-BIND Investigator Team¹⁰, Stephen Strother¹¹
	M511	Severity of Symptoms Is Associated with Accelerated Brain Aging in Depressive Patients	Nils Winter¹, Marie Beisemann², Ramona Leenings³, Daniel Emden³, Claas Kaehler³, Nils Opel³, Ronny Redlich², Janik Goltermann², Jonathan Repple², Dominik Grotegerd², Katharina Dohm², Katharina Förster², Dario Zaremba², Elisabeth Leehr², Joscha Böhnlein², Susanne Meinert², Verena Enneking², Fanni Dzvonyar⁴, Hannah Lemke⁴, Lisa Sindermann⁴, Walter Heindel², Harald Kugel², Volker Arolt⁵, Tilo Kircher⁶, Igor Nenadić⁶, Jens Sommer⁷, Olaf Steinsträter⁷, Andreas Jansen⁷, Christian Gaser⁸, Marco Hermesdorf², Klaus Berger², Udo Dannlowski², Tim Hahn⁹
	M521	Simulated TMS-EEG Biofeedback Using Automated Neural Architecture Search and Transfer Learning	Scott Heston¹, Michael Borich²
	M522	Patient-tailored prediction of neuropathology in cognitive impairment using neuroimaging biomarkers	EunChong Lee¹, Han Soo Yoo², Byoung Seok Ye², Joon-Kyung Seong¹
	M687	EEG microstate features predict BOLD-fMRI dynamic functional connectivity states	Rodolfo Abreu¹, João Jorge², Alberto Leal³, Patrícia Figueiredo¹
	M689	Classification of epileptic states from fMRI dynamic functional connectivity using machine learning	Joana Carmona¹, Rodolfo Abreu¹, Carlos Santiago², Alberto Leal³, Jacinto C. Nascimento², Patricia Figueiredo¹
	M741	Predicting task activation from resting connectivity in Schizophrenia patients	Niv Tik¹, Abigail Livny², Mark Weiser², Karny Gigi², Galia Tzarfaty², Ido Tavor¹
	M877	Multiblock Components Analysis for Brain Imaging Data	Atsushi Kawaguchi¹
	T368	QMRI grey matter microstructural changes predict healthy aging and identify Multiple Sclerosis	Asier Erramuzpe¹, Roey Schurr¹, Aviv Mezer¹
	T675	Concurrent TMS-fMRI and MVPA reveals a causal role of right dlPFC in driving selective attention	Jade Jackson¹, Eva Feredoes², Anina Rich³, Michael Linder², Alexandra Woolgar⁴^,5
	Th141	The Impacts of Anti-depressants on the Depression Functional Network: Improve or Worsen?	Qunjie Zhou¹, Dan Dai¹^,2, Ningning Ma², Jianfeng Feng¹^,2
	Th167	Classification of mood disorders using multiple kernel learning on multimodal neuroimaging data	Benedetta Vai¹, Sara Poletti¹, Carlotta Bertocchi¹, Irene Bollettini¹, Cristina Colombo¹, Francesco Benedetti²
	Th178	Clustering of depression subtypes – Linking symptoms and morphology	Lee Jollans¹, Philipp Sämann¹, Tanja Brückl¹, Elisabeth Binder²
	Th186	Covariates for the prediction of antidepressant treatment response from functional connectivity	Manfred Klöbl¹, Gregor Gryglewski¹, Lucas Rischka¹, Mathis Godbersen¹, Jakob Unterholzner¹, Murray Reed¹, Paul Michenthaler¹, Thomas Vanicek¹, Edda Winkler-Pjrek¹, Andreas Hahn¹, Siegfried Kasper¹, Rupert Lanzenberger¹
	Th218	Exploring multivariate functional signature of migraine and comorbid insomnia: An fMRI study	Chen-Yuan Kuo¹, Fu-Chi Yang², Shuu-Jiun Wang³, Ching-Po Lin¹^,4^,5, Kun-Hsien Chou⁴^,5
	Th366	Basal Ganglia-Cerebellar Impact on Performance After Motor Imagery With Real-time fMRI Neurofeedback	Owen Morgan¹, Jonathan Lisinski², Stephen LaConte², Cherie Marvel¹
	Th367	Attentuating Neural Threat Expression with Imagination	Marianne Reddan¹, Tor Wager², Daniela Schiller¹
	W026	Identification of imaging biomarkers in Internet Gaming Disorder using random forest classifier	Min Seob Kim¹, Do hyun Kim¹, Bumseok Jeong¹
	W056	Detection of Alzheimer's disease using paragraph vectors of spoken samples	Gang Lyu¹, Kim-Han Thung², Dinggang Shen²
	W079	Predicting conversion to Alzheimer’s with MRI Asymmetry Indices of Hippocampus subfields	Alessia Sarica¹, Aldo Quattrone¹
	W090	MRI-based frontotemporal dementia probability scores: a longitudinal presymptomatic biomarker study	Rogier Feis¹, Mark Bouts², Frank de Vos², Tijn Schouten², Jessica Panman³, Lize Jiskoot³, Elise Dopper³, Jeroen van der Grond¹, John van Swieten³, Serge Rombouts¹
	W093	A data-driven staging of in-vivo tau deposition is consistent with Braak’s post-mortem staging	Leon Aksman¹, Daniel Alexander¹, Frederik Barkhof², Andre Altmann¹
	W095	Symptom-onset prediction in genetic frontotemporal dementia with multimodal MRI-based classification	Rogier Feis¹, Mark Bouts², Frank de Vos², Tijn Schouten², Jessica Panman³, Lize Jiskoot³, Elise Dopper³, Jeroen van der Grond¹, John van Swieten³, Serge Rombouts¹
	W113	Predicting future cognitive decline of memory clinic patients using multimodal MRI	Frank de Vos¹^,2^,3, Tijn Schouten¹^,4^,3, Mark Bouts¹^,2^,3, Rogier Feis⁵^,3, Mark de Rooij¹^,3, Jeroen van der Grond⁵, Serge Rombouts¹^,2^,3
	W115	Characterization of a « Temporoparietal Junction » Subtype of Alzheimer’s Disease	François Meyer¹, Marie Wehenkel², Christophe Phillips³, Pierre Geurts⁴, Christine Bastin³, Eric Salmon³
	W132	Machine Learning Based Automated Staging of 18F-Florbetaben PET images Background	Jun Pyo Kim¹, Jeonghun Kim², Yeshin Kim³, Seung Whan Moon¹, Yu Hyun Park¹, Sole Yoo⁴, Hee Jin Kim¹, Duk L. Na¹, Sang Won Seo¹
	W154	Prediction of 7-year progression from subjective cognitive decline to MCI	Ling Yue¹, Dan Hu², Han Zhang², Junhao Wen³, Ye Wu², Tao Wang¹, Dinggang Shen*², Shifu Xiao¹
	W199	Study of brain connectivity changes to characterize epileptic seizures after traumatic brain injury	Marianna La Rocca¹, Giuseppe Barisano¹, Rachael Garner¹, Paul Vespa², Arthur Toga¹, Dominique Duncan¹
	W205	Conditional generative adversarial networks support the detection of focal cortical dysplasias	Bastian David¹, Sailesh Conjeti², Fabiane Schuch¹, Bernd Weber¹, Elke Hattingen³, Christian Elger¹, Martin Reuter²^,4, Theodor Rüber¹^,5^,6
	W213	Robust detection of longitudinal white matter trajectories in premanifest Huntington's Disease	Pablo Polosecki¹, Eduardo Castro¹, Dorian Pustina², John Warner², Andrew Wood², Cristina Sampaio², Guillermo Cecchi¹
	W225	Brain Abnormalities Detection in de novo Parkinsonian Patients	Verónica Muñoz Ramírez¹, Florence Forbes², Alexis Arnaud², Michel Dojat¹
	W228	Voice Analysis in Early Parkinson's Disease and Correlation with Neuroimaging	Laetitia Jeancolas¹, Nicolas Villain²^,3^,4, Rahul Gaurav⁴, Dijana Petrovska-Delacrétaz¹, Badr-Eddine Benkelfat¹, Graziella Mangone⁵^,3^,4, Marie Odile Habert⁶^,7, Jean-Christophe Corvol³^,5^,4, Marie Vidailhet³^,5^,4, Stephane Lehéricy⁴^,5, Habib Benali⁸
	W243	Resting-state connectivity stratifies premanifest Huntington’s disease by cognitive decline rate	Pablo Polosecki¹, Eduardo Castro¹, Dorian Pustina², John Warner², Andrew Wood², Cristina Sampaio², Guillermo Cecchi¹
	W275	Robust multivariate models of longitudinal subcortical change in premanifest Huntington’s disease	Eduardo Castro¹, Pablo Polosecki¹, Dorian Pustina², John Warner², Andrew Wood², Cristina Sampaio², Guillermo Cecchi¹
	W277	Automatic Diagnosis of Spasmodic Dysphonia with Structural MRI and Machine Learning	Davide Valeriani¹, Kristina Simonyan¹
	W447	Disrupted resting-state effective connectivity of the thalamus in schizophrenic patients	Minghui Hua¹, Meng Liang¹
	W510	Multimodal Neuroimaging Biosignatures of Perinatally Acquired HIV/early ART in 7-year-old Children	Isaac Khobo¹, Frances Robertson¹^,2, Marcin Jankiewicz¹^,2, Martha Holmes¹, Francesca Little¹, Mark Cotton³, Andre van der Kouwe⁴^,5, Barbara Laughton³, Emmanuel Nwosu¹, Ernesta Meintjes¹^,2, Allison Moreau⁶
	W843	Does change of frontal theta cordance predict depression treatment outcome?	Barbora Bučková¹^,2, Jaroslav Hlinka¹, Martin Brunovský³, Michal Vavrečka¹, Vlastimil Koudelka³
Back To Top