`

Timezone: »

 
Poster
Neurons as Monte Carlo Samplers: Bayesian Inference and Learning in Spiking Networks
Yanping Huang · Rajesh PN Rao

Mon Dec 08 04:00 PM -- 08:59 PM (PST) @ Level 2, room 210D #None

We propose a two-layer spiking network capable of performing approximate inference and learning for a hidden Markov model. The lower layer sensory neurons detect noisy measurements of hidden world states. The higher layer neurons with recurrent connections infer a posterior distribution over world states from spike trains generated by sensory neurons. We show how such a neuronal network with synaptic plasticity can implement a form of Bayesian inference similar to Monte Carlo methods such as particle filtering. Each spike in the population of inference neurons represents a sample of a particular hidden world state. The spiking activity across the neural population approximates the posterior distribution of hidden state. The model provides a functional explanation for the Poisson-like noise commonly observed in cortical responses. Uncertainties in spike times provide the necessary variability for sampling during inference. Unlike previous models, the hidden world state is not observed by the sensory neurons, and the temporal dynamics of the hidden state is unknown. We demonstrate how this network can sequentially learn the hidden Markov model using a spike-timing dependent Hebbian learning rule and achieve power-law convergence rates.

Author Information

Yanping Huang (University of Washington)
Rajesh PN Rao (University of Washington)

More from the Same Authors

  • 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
  • 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
  • 2012 Poster: How Prior Probability Influences Decision Making: A Unifying Probabilistic Model »
    Yanping Huang · Abram Friesen · Timothy Hanks · Michael N Shadlen · Rajesh PN Rao
  • 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
  • 2006 Poster: Learning Nonparametric Models for Probabilistic Imitation »
    David Grimes · Daniel Rashid · Rajesh PN Rao