Timezone: »
Neuroscientists classify neurons into different types that perform similar computations at different locations in the visual field. Traditional methods for neural system identification do not capitalize on this separation of “what” and “where”. Learning deep convolutional feature spaces that are shared among many neurons provides an exciting path forward, but the architectural design needs to account for data limitations: While new experimental techniques enable recordings from thousands of neurons, experimental time is limited so that one can sample only a small fraction of each neuron's response space. Here, we show that a major bottleneck for fitting convolutional neural networks (CNNs) to neural data is the estimation of the individual receptive field locations – a problem that has been scratched only at the surface thus far. We propose a CNN architecture with a sparse readout layer factorizing the spatial (where) and feature (what) dimensions. Our network scales well to thousands of neurons and short recordings and can be trained end-to-end. We evaluate this architecture on ground-truth data to explore the challenges and limitations of CNN-based system identification. Moreover, we show that our network model outperforms current state-of-the art system identification models of mouse primary visual cortex.
Author Information
David Klindt (University of Tübingen)
Alexander Ecker (University of Tuebingen)
Thomas Euler (University of Tübingen)
Matthias Bethge (University Tübingen)
More from the Same Authors
-
2021 Spotlight: Removing Inter-Experimental Variability from Functional Data in Systems Neuroscience »
Dominic Gonschorek · Larissa Höfling · Klaudia P. Szatko · Katrin Franke · Timm Schubert · Benjamin Dunn · Philipp Berens · David Klindt · Thomas Euler -
2021 : Score-Based Generative Classifiers »
Roland S. Zimmermann · Lukas Schott · Yang Song · Benjamin Dunn · David Klindt -
2021 : Score-Based Generative Classifiers »
Roland S. Zimmermann · Lukas Schott · Yang Song · Benjamin Dunn · David Klindt -
2022 : Topological Ensemble Detection with Differentiable Yoking »
David Klindt · Sigurd Gaukstad · Erik Hermansen · Melvin Vaupel · Benjamin Dunn -
2021 Poster: Removing Inter-Experimental Variability from Functional Data in Systems Neuroscience »
Dominic Gonschorek · Larissa Höfling · Klaudia P. Szatko · Katrin Franke · Timm Schubert · Benjamin Dunn · Philipp Berens · David Klindt · Thomas Euler -
2020 Poster: System Identification with Biophysical Constraints: A Circuit Model of the Inner Retina »
Cornelius Schröder · David Klindt · Sarah Strauss · Katrin Franke · Matthias Bethge · Thomas Euler · Philipp Berens -
2020 Spotlight: System Identification with Biophysical Constraints: A Circuit Model of the Inner Retina »
Cornelius Schröder · David Klindt · Sarah Strauss · Katrin Franke · Matthias Bethge · Thomas Euler · Philipp Berens -
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 -
2018 : Adversarial Vision Challenge: Results of the Adversarial Vision Challenge »
Wieland Brendel · Jonas Rauber · Marcel Salathé · Alexey Kurakin · Nicolas Papernot · Sharada Mohanty · Matthias Bethge -
2018 Poster: Stimulus domain transfer in recurrent models for large scale cortical population prediction on video »
Fabian Sinz · Alexander Ecker · Paul Fahey · Edgar Walker · Erick M Cobos · Emmanouil Froudarakis · Dimitri Yatsenko · Xaq Pitkow · Jacob Reimer · Andreas Tolias -
2017 : DeepArt competition »
Alexander Ecker · Leon A Gatys · Matthias Bethge -
2016 : Matthias Bethge - Texture perception in humans and machines »
Matthias Bethge -
2015 Poster: Texture Synthesis Using Convolutional Neural Networks »
Leon A Gatys · Alexander Ecker · Matthias Bethge -
2015 Poster: Generative Image Modeling Using Spatial LSTMs »
Lucas Theis · Matthias Bethge -
2012 Poster: Training sparse natural image models with a fast Gibbs sampler of an extended state space »
Lucas Theis · Jascha Sohl-Dickstein · Matthias Bethge -
2010 Poster: Evaluating neuronal codes for inference using Fisher information »
Ralf Haefner · Matthias Bethge -
2009 Poster: Hierarchical Modeling of Local Image Features through $L_p$-Nested Symmetric Distributions »
Fabian H Sinz · Eero Simoncelli · Matthias Bethge -
2009 Poster: Neurometric function analysis of population codes »
Philipp Berens · Sebastian Gerwinn · Alexander S Ecker · Matthias Bethge -
2009 Poster: A joint maximum-entropy model for binary neural population patterns and continuous signals »
Sebastian Gerwinn · Philipp Berens · Matthias Bethge -
2009 Spotlight: A joint maximum-entropy model for binary neural population patterns and continuous signals »
Sebastian Gerwinn · Philipp Berens · Matthias Bethge -
2009 Poster: Bayesian estimation of orientation preference maps »
Jakob H Macke · Sebastian Gerwinn · Leonard White · Matthias Kaschube · Matthias Bethge -
2008 Poster: The Conjoint Effect of Divisive Normalization and Orientation Selectivity on Redundancy Reduction »
Fabian H Sinz · Matthias Bethge -
2008 Spotlight: The Conjoint Effect of Divisive Normalization and Orientation Selectivity on Redundancy Reduction »
Fabian H Sinz · Matthias Bethge -
2007 Oral: Bayesian Inference for Spiking Neuron Models with a Sparsity Prior »
Sebastian Gerwinn · Jakob H Macke · Matthias Seeger · Matthias Bethge -
2007 Spotlight: Near-Maximum Entropy Models for Binary Neural Representations of Natural Images »
Matthias Bethge · Philipp Berens -
2007 Poster: Near-Maximum Entropy Models for Binary Neural Representations of Natural Images »
Matthias Bethge · Philipp Berens -
2007 Poster: Bayesian Inference for Spiking Neuron Models with a Sparsity Prior »
Sebastian Gerwinn · Jakob H Macke · Matthias Seeger · Matthias Bethge -
2007 Poster: Receptive Fields without Spike-Triggering »
Jakob H Macke · Günther Zeck · Matthias Bethge