PS-1B: Poster Session 1B |
Session Type: Poster |
Time: Thursday, September 6, 18:45 - 20:45 |
Location: Symphony/Overture |
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PS-1B.1: Decomposing spatial conflict BOLD activation using a drift-diffusion model framework |
James McIntosh; Columbia University |
Paul Sajda; Columbia University |
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PS-1B.2: A Procedural Roadblock to Mechanistic Understanding of Neural Circuits |
Venkat Ramaswamy; National Centre for Biological Sciences |
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PS-1B.3: Decision-making through evidence integration at long timescales |
Michael Waskom; New York University |
Roozbeh Kiani; New York University |
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PS-1B.4: Predicting memory performance using a joint model of brain and behavior |
David Halpern; New York University |
Shannon Tubridy; New York University |
Lila Davachi; New York University |
Todd Gureckis; New York University |
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PS-1B.5: Neural and computational dissociations between objects, scenes, and near-scale reachspaces |
Emilie Josephs; Harvard University |
Talia Konkle; Harvard University |
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PS-1B.6: Modeling the effects of temporal context on neural responses across the cortical hierarchy |
Hsiang-Yun Chien; Johns Hopkins University |
Christopher Honey; Johns Hopkins University |
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PS-1B.7: Gaussian Process Models Characterize Other-Regarding Strategies Over Multiple Timescales in a Dynamic Social Game |
Kelsey McDonald; Duke University |
William F. Broderick; New York University |
Scott Huettel; Duke University |
John Pearson; Duke University |
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PS-1B.8: Improving Corticostriatal Parcellation Through Multilevel Bagging with PyBASC |
Aki Nikolaidis; Child Mind Institute |
Joshua Vogelstein; Johns Hopkins University |
Pierre Bellec; University of Montreal |
Michael Milham; Child Mind Institute |
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PS-1B.9: Performance Optimization is Insufficient for Building Accurate Models for Neural Representation |
Jonathan Yu; Princeton University |
Qihong Lu; Princeton University |
Uri Hasson; Princeton University |
Kenneth Norman; Princeton University |
Jonathan Pillow; Princeton University |
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PS-1B.10: Deep convolutional neural networks, features, and categories perform similarly at explaining primate high-level visual representations |
Kamila Maria Jozwik; Massachusetts Institute of Technology and University of Cambridge |
Nikolaus Kriegeskorte; Columbia University |
Radoslaw Martin Cichy; Free University Berlin |
Marieke Mur; University of Cambridge |
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PS-1B.11: Brain activity recorded during free viewing of naturalistic short films simultaneously reveals the brain representations of multiple feature spaces |
Anwar Nunez-Elizalde; University of California, Berkeley |
Fatma Deniz; University of California, Berkeley |
James Gao; University of California, Berkeley |
Jack Gallant; University of California, Berkeley |
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PS-1B.12: Learning long-range spatial dependencies with horizontal gated-recurrent units |
Drew Linsley; Brown University |
Junkyung Kim; Brown University |
Vijay Veerabadran; Brown University |
Thomas Serre; Brown University |
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PS-1B.13: Temporal structure of learning to regulate ventral tegmental area using real-time fMRI neurofeedback |
Shabnam Hakimi; Duke University |
Jeffrey MacInnes; University of Washington |
Kathryn Dickerson; Duke University |
Alison Adcock; Duke University |
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PS-1B.14: Deep Learning Classification Study of First-Episode Treatment-Naïve Schizophrenia Using Brain Cortical Area and Cognitive Features |
Yinfei Li; West China Hospital |
Tao Li; West China Hospital |
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PS-1B.15: Learning to attend in a brain-inspired deep neural network |
Hossein Adeli; Stony Brook University |
Gregory Zelinsky; Stony Brook University |
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PS-1B.16: Non-Computational Functionalism: Computation and the Function of Consciousness |
Gualtiero Piccinini; University of Missouri - Saint Louis |
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PS-1B.17: Predicting Affective Cognitions in the Resting Adult Brain |
Keith Bush; University of Arkansas for Medical Sciences |
Anthony Privratsky; University of Arkansas for Medical Sciences |
Clinton Kilts; University of Arkansas for Medical Sciences |
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PS-1B.18: How does motion affect material perception of deformable objects? |
Wenyan Bi; American University |
Hendrikje Nienborg; University of Tubingen |
Bei Xiao; American University |
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PS-1B.19: The hippocampal formation facilitates social decision-making by transforming reference frames. |
Raphael Kaplan; University College London |
Karl Friston; University College London |
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PS-1B.20: Memory mechanisms predict sampling biases in sequential decision tasks |
Marcelo Mattar; Princeton University |
Deborah Talmi; University of Manchester |
Nathaniel Daw; Princeton University |
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PS-1B.21: Uncovering mental and neural structure through data-driven ontology discovery |
Ian Eisenberg; Stanford University |
Patrick Bissett; Stanford University |
A Zeynep Enkavi; Stanford University |
Jamie Li; Stanford University |
David MacKinnon; Arizona State University |
Lisa Marsch; Dartmouth College |
Russell Poldrack; Stanford University |
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PS-1B.22: A selective diffusion model of brain network activity |
Daniel Graham; Hobart & William Smith Colleges |
Yan Hao; Hobart & William Smith Colleges |
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PS-1B.23: Cortical feedback to superficial layers of V1 contains predictive scene information. |
Andrew Morgan; University of Glasgow |
Lucy Petro; University of Glasgow |
Lars Muckli; University of Glasgow |
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PS-1B.24: Using features from deep neural networks to model human categorization of natural images |
Ruairidh Battleday; University of California, Berkeley |
Joshua Peterson; University of California, Berkeley |
Thomas Griffiths; University of California, Berkeley |
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PS-1B.25: Decision-related activity & feature-selective attention: evidence for a common mechanism in macaque V2 |
Katrina R Quinn; University of Tübingen |
Stephane Clery; University of Tübingen |
Paria Pourriahi; University of Tübingen |
Hendrikje Nienborg; University of Tübingen |
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PS-1B.26: An Algorithm for Clustering Decision-Making Phenotypes from Behavioural Data |
Abraham Nunes; Dalhousie University |
Alexander Rudiuk; Dalhousie University |
Thomas Trappenberg; Dalhousie University |
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PS-1B.27: Phoneme-level processing in low-frequency cortical responses to speech explained by acoustic features |
Christoph Daube; University of Glasgow |
Robin A. A. Ince; University of Glasgow |
Joachim Gross; Westfälische Wilhelms-Universität |
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PS-1B.28: A variational image reconstruction algorithm reveals distortion and uncertainty in mental imagery |
Thomas Naselaris; Medical University of South Carolina |
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PS-1B.29: Data-driven methods reveal the generalizing mechanisms of speech processing in naturally varying soundscapes |
Moritz Boos; Applied Neurocognitive Psychology Lab |
Jörg Lücke; Machine Learning Group |
Jochem Rieger; Applied Neurocognitive Psychology Lab |
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PS-1B.30: Reevaluating revaluation: evidence for value construction during decision making |
Akram Bakkour; Columbia University |
Ariel Zylberberg; Columbia University |
Michael Shadlen; Columbia University |
Daphna Shohamy; Columbia University |
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PS-1B.31: A dynamical systems model of intrinsic and evoked activity, variability, and functional connectivity |
Takuya Ito; Rutgers University |
Brian Keane; Rutgers University |
Ravi Mill; Rutgers University |
Richard Chen; Rutgers University |
Luke Hearne; Rutgers University |
Katelyn Arnemann; Rutgers University |
Biyu He; New York University |
Horacio Rotstein; New Jersey Institute of Technology |
Michael Cole; Rutgers University |
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PS-1B.32: Modeling human visual responses with a U-shaped deep neural network for motion flow-field estimation |
Atsushi Wada; National Institute of Information and Communications Technology |
Satoshi Nishida; National Institute of Information and Communications Technology |
Hiroshi Ando; National Institute of Information and Communications Technology |
Shinji Nishimoto; National Institute of Information and Communications Technology |
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PS-1B.33: Neurons of the prefrontal cortex encode a representation of a Bayesian belief during reinforcement learning |
Ramon Bartolo; National Institutes Of Health |
Richard Saunders; National Institutes Of Health |
Andrew Mitz; National Institutes Of Health |
Bruno Averbeck; National Institutes Of Health |
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PS-1B.34: Short-term Sequence Memory: Compressive effects of Recurrent Network Dynamics |
Adam Charles; Princeton University |
Han Lun Yap; DSO National Laboratories |
Dong Yin; University of California, Berkeley |
Christopher Rozell; Georgia Institute of Technology |
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PS-1B.35: Visualizing the global geometry of population representations of multiple visual object categories with spheres |
Andrew David Zaharia; Mortimer B. Zuckerman Mind Brain Behavior Institute, Columbia University |
Alexander Walther; Realeyes |
Nikolaus Kriegeskorte; Mortimer B. Zuckerman Mind Brain Behavior Institute, Columbia University |
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PS-1B.36: Unsupervised deep neural network for fMRI feedback modelling |
Michele Svanera; University of Glasgow |
Andrew T. Morgan; University of Glasgow |
Lucy S. Petro; University of Glasgow |
Lars Muckli; University of Glasgow |
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PS-1B.37: Oscillations in Stochastic Neural Computational Systems |
Gary Engler; Stevens Institute of Technology |
Michael Zabarankin; Stevens Institute of Technology |
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PS-1B.38: Brain age prediction for post-traumatic stress disorder patients with convolutional neural networks: a multi-modal neuroimaging study |
Xin Niu; Drexel university |
Hualou Liang; Drexel university |
Fengqing Zhang; Drexel university |
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PS-1B.39: White Matter Network Architecture Guides Direct Electrical Stimulation Through Optimal State Transitions |
Jennifer Stiso; University of Pennsylvania |
Ankit Khambhati; University of Pennsylvania |
Tommaso Menara; University of California Riverside |
Ari Kahn; University of Pennsylvania |
Joel Stein; University of Pennsylvania |
Sandihitsu Das; University of Pennsylvania |
Richard Gorniak; Jefferson University |
Joseph Tracy; Jefferson University |
Brian Litt; University of Pennsylvania |
Kathryn Davis; University of Pennsylvania |
Fabio Pasqualetti; University of California Riverside |
Timothy Lucas; University of Pennsylvania |
Danielle Bassett; University of Pennsylvania |
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PS-1B.40: The impact of noise correlation on multivariate pattern classification in fMRI |
RUYUAN ZHANG; University of Minnesota |
Kendrick Kay; University of Minnesota |
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PS-1B.41: A Perceptual Confirmation Bias from Approximate Online Inference |
Richard Lange; University of Rochester |
Ankani Chattoraj; University of Rochester |
Matthew Hochberg; University of Rochester |
Jeffrey Beck; Duke University |
Jacob Yates; University of Rochester |
Ralf Haefner; University of Rochester |
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PS-1B.42: Orientation selectivity and stimulus vignetting in human visual cortex |
Zvi Roth; National Institutes of Health |
David Heeger; New York University |
Elisha Merriam; National Institutes of Health |
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PS-1B.43: Response Inhibition in Adolescents is Moderated by Brain Connectivity and Social Network Structure |
Steven Tompson; U.S. Army Research Laboratory |
Emily Falk; University of Pennsylvania |
Jean Vettel; U.S. Army Research Laboratory |
Danielle Bassett; University of Pennsylvania |
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PS-1B.44: Global-and-local attention networks for visual recognition |
Drew Linsley; Brown University |
Dan Shiebler; Twitter |
Sven Eberhardt; Amazon |
Thomas Serre; Brown University |
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PS-1B.45: Why is the fusiform face area recruited for other domains of expertise? |
Garrison Cottrell; UCSD |
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