Review 39: Inferring Latent Dynamics Underlying Neural Population Activity via Neural Differential Equations
Inferring Latent Dynamics Underlying Neural Population Activity via Neural Differential Equations by Timothy Doyeon Kim and Carlos D. Brody
Here I review some papers I read. I want to emphasize that I aim to keep reviews respectful of the authors work. I understand how hard it is to put research together and the last thing I want to do is have authors feeling like I put their work on blast. Especially, because I do not claim to be an expert in the exact domains of the papers I am reading. I am an early career researcher, a beginner whose goal is to learn. I’d like to use this to celebrate / share work I think is awesome!. And also to agglomerate notes on cool things. If you have concerns about a post, please email me at zladd@berkeley.edu.
Or leave a comment or give feedback – I’d love to engage :)
Thanks and hope you all enjoy,
Xander
Inferring Latent Dynamics Underlying Neural Population Activity via Neural Differential Equations by Timothy Doyeon Kim and Carlos D. Brody
LFADS - Latent Factor Analysis via Dynamical Systems by David Sussillo and Chethan Pandarinath
Auto-Encoding Variational Bayes by Diederik P. Kingma and Max Welling
Opening the Black Box: Low-Dimensional Dynamics in High-Dimensional Recurrent Neural Networks by David Sussillo and Omri Barak
Cortical activity during motor execution, motor imagery, and imagery-based online feedback by Kai Miller and Rajesh P.N. Rao
The Role of Population Structure in Computations Through Neural Dynamics by Alexis Dubreuil Adrian Valente and Srdjan Ostojic
High-density Single-unit Human Cortical Recordings Using the Neuropixels Probe by Jason Chung and Edward F. Chang
Living Science: Maintaining the Joy of Discovery by Eve Marder
Noninvasive Brain–Machine Interfaces for Robotic Devices by Luca Toning and José del R. Millán
Eavesdropping on the Brain With 10,000 Electrodes by Barun Dutta
Emergence of Coordinated Neural Dynamics Underlies Neuroprosthetic Learning and Skillful Control by Vivek Athalye and Jose Carmena
Four ethical priorities for neurotechnologies and AI by Rafael Yuste and Sara Goering
Parsing learning in networks using brain-machine interfaces by Amy Orsborn and Bijan Pesaran
A control-theoretic approach to brain-computer interface design by Yin Zhang and Steven Chase
Plug-and-play control of a brain-computer interface through neural map stabilization by Daniel Silversmith.
The brain-reading devices helping paralysed people to move, talk and touch by Liam Drew.
Neuropixels 2.0: A miniaturized high-density probe for stable, long-term brain recordings by Nick Steinmetz.
Cracking the Neural Code in Humans by Emily Singer at the Simons Foundation.
Trends in Computational Neuroscience: Cosyne 2022 by Sabera Talukder
Let us never speak of these values again. by Ben Recht
Deep Learning is Hitting a Wall by Gary Marcus
Predictive Coding, Variational Autoencoders, and Biological Connections by Joseph Marino
Predictive Coding, Variational Autoencoders, and Biological Connections by Joseph Marino
Predictive Coding, Variational Autoencoders, and Biological Connections by Joseph Marino
Computation Through Neural Population Dynamics by Saurabh Vyas
Computation Through Neural Population Dynamics by Saurabh Vyas
Just Ask for Generalization by Eric Jang
The Bandwagon by Claude E. Shannon
Beyond advertising: New infrastructures for publishing integrated research objects by Elizabeth DuPre et al.
The Sensory Neuron as a Transformer: Permutation-Invariant Neural Networks for Reinforcement Learning by Dr. Ha and Yujin Tang
The Future of Artificial Intelligence is Self-Organizing and Self-Assembling by Prof. Sebastian Risi
Visualizing synaptic plasticity in vivo by large-scale imaging of endogenous AMPA receptors by Dr. Austin Graves Dr. Richard Huganir.
Spiking Neural Networks by Anil Ananthaswamy.
Making RL Tractable by Learning More Informative Reward Functions: Example-Based Control, Meta-Learning, and Normalized Maximum Likelihood.
Wow, I just found out what it means to be “Not even wrong”. The phase, coined by Wolfgang Pauli has just given me a huge slice of humble pie. Basically not e...
If we already understood the brain, would we even know it? by Tal Yarkoni.
From synapse to network: models of information storage and retrieval in neural circuits by Johnatan (Yonatan) Aljadeff et al.
Sparse balance: excitatory-inhibitory networks with small bias currents and broadly distributed synaptic weights by Ramin Khajeh, Francesco Fumarola, Lar...
Review 1 : In Silico by Dr. Fairhall Citation: Fairhall, Adrienne L. “In silico: where next?.” Eneuro 8.2 (2021). Intro ...
Well I am very busy so I’ll keep this short and sweet but I was listening to Alan Watts and ever since I’ve turned it off this one thought has stuck with me....