Timezone: »
How does the brain combine prior knowledge with sensory evidence when making decisions under uncertainty? Two competing descriptive models have been proposed based on experimental data. The first posits an additive offset to a decision variable, implying a static effect of the prior. However, this model is inconsistent with recent data from a motion discrimination task involving temporal integration of uncertain sensory evidence. To explain this data, a second model has been proposed which assumes a time-varying influence of the prior. Here we present a normative model of decision making that incorporates prior knowledge in a principled way. We show that the additive offset model and the time-varying prior model emerge naturally when decision making is viewed within the framework of partially observable Markov decision processes (POMDPs). Decision making in the model reduces to (1) computing beliefs given observations and prior information in a Bayesian manner, and (2) selecting actions based on these beliefs to maximize the expected sum of future rewards. We show that the model can explain both data previously explained using the additive offset model as well as more recent data on the time-varying influence of prior knowledge on decision making.
Author Information
Yanping Huang (University of Washington)
Abram Friesen (DeepMind)
Timothy Hanks (Princeton University)
Michael N Shadlen (Columbia University and Howard Hughes Medical Institute)
Michael Shadlen MD, PhD is an Investigator of the Howard Hughes Medical Institute and Professor of Physiology & Biophysics at the University of Washington, where is also an adjunct Professor of Neurology. He performed undergraduate and medical studies at Brown University and obtained a PhD from UC Berkeley in visual neuroscience under the guidance of Ralph D. Freeman. He received postgraduate clinical training in Neurology at Stanford Medical Center. He then returned to basic neuroscience as a fellow in the laboratory of William T. Newsome, where he began to work on the neurobiology of decision-making. Shadlen studies neurons in the association cortex that process information from the visual cortex to give rise to interpretations, decisions, and plans for behavior. His experiments combine electrophysiology and behavioral and computational methods to advance our knowledge of higher brain function.
Rajesh PN Rao (University of Washington)
More from the Same Authors
-
2022 : Multi-step Planning for Automated Hyperparameter Optimization with OptFormer »
Lucio M Dery · Abram Friesen · Nando de Freitas · Marc'Aurelio Ranzato · Yutian Chen -
2019 : Poster Session »
Pravish Sainath · Mohamed Akrout · Charles Delahunt · Nathan Kutz · Guangyu Robert Yang · Joseph Marino · L F Abbott · Nicolas Vecoven · Damien Ernst · andrew warrington · Michael Kagan · Kyunghyun Cho · Kameron Harris · Leopold Grinberg · John J. Hopfield · Dmitry Krotov · Taliah Muhammad · Erick Cobos · Edgar Walker · Jacob Reimer · Andreas Tolias · Alexander Ecker · Janaki Sheth · Yu Zhang · Maciej Wołczyk · Jacek Tabor · Szymon Maszke · Roman Pogodin · Dane Corneil · Wulfram Gerstner · Baihan Lin · Guillermo Cecchi · Jenna M Reinen · Irina Rish · Guillaume Bellec · Darjan Salaj · Anand Subramoney · Wolfgang Maass · Yueqi Wang · Ari Pakman · Jin Hyung Lee · Liam Paninski · Bryan Tripp · Colin Graber · Alex Schwing · Luke Prince · Gabriel Ocker · Michael Buice · Benjamin Lansdell · Konrad Kording · Jack Lindsey · Terrence Sejnowski · Matthew Farrell · Eric Shea-Brown · Nicolas Farrugia · Victor Nepveu · Jiwoong Im · Kristin Branson · Brian Hu · Ramakrishnan Iyer · Stefan Mihalas · Sneha Aenugu · Hananel Hazan · Sihui Dai · Tan Nguyen · Doris Tsao · Richard Baraniuk · Anima Anandkumar · Hidenori Tanaka · Aran Nayebi · Stephen Baccus · Surya Ganguli · Dean Pospisil · Eilif Muller · Jeffrey S Cheng · Gaël Varoquaux · Kamalaker Dadi · Dimitrios C Gklezakos · Rajesh PN Rao · Anand Louis · Christos Papadimitriou · Santosh Vempala · Naganand Yadati · Daniel Zdeblick · Daniela M Witten · Nicholas Roberts · Vinay Prabhu · Pierre Bellec · Poornima Ramesh · Jakob H Macke · Santiago Cadena · Guillaume Bellec · Franz Scherr · Owen Marschall · Robert Kim · Hannes Rapp · Marcio Fonseca · Oliver Armitage · Jiwoong Im · Thomas Hardcastle · Abhishek Sharma · Wyeth Bair · Adrian Valente · Shane Shang · Merav Stern · Rutuja Patil · Peter Wang · Sruthi Gorantla · Peter Stratton · Tristan Edwards · Jialin Lu · Martin Ester · Yurii Vlasov · Siavash Golkar -
2019 Poster: A Bayesian Theory of Conformity in Collective Decision Making »
Koosha Khalvati · Saghar Mirbagheri · Seongmin A. Park · Jean-Claude Dreher · Rajesh PN Rao -
2018 Poster: Submodular Field Grammars: Representation, Inference, and Application to Image Parsing »
Abram Friesen · Pedro Domingos -
2016 : Rajesh Rao - Modeling human decision making using POMDPs »
Rajesh PN Rao -
2016 Poster: A Probabilistic Model of Social Decision Making based on Reward Maximization »
Koosha Khalvati · Seongmin A. Park · Jean-Claude Dreher · Rajesh PN Rao -
2015 Poster: A Bayesian Framework for Modeling Confidence in Perceptual Decision Making »
Koosha Khalvati · Rajesh PN Rao -
2014 Poster: Neurons as Monte Carlo Samplers: Bayesian Inference and Learning in Spiking Networks »
Yanping Huang · Rajesh PN Rao -
2011 Poster: An ideal observer model for identifying the reference frame of objects »
Joseph L Austerweil · Abram Friesen · Tom Griffiths -
2010 Oral: A rational decision making framework for inhibitory control »
Pradeep Shenoy · Rajesh PN Rao · Angela Yu -
2010 Poster: A rational decision making framework for inhibitory control »
Pradeep Shenoy · Rajesh PN Rao · Angela Yu -
2008 Tutorial: The Neurobiology of Decision Making »
Michael N Shadlen -
2006 Poster: Learning Nonparametric Models for Probabilistic Imitation »
David Grimes · Daniel Rashid · Rajesh PN Rao