From Neuroscience to Artificially Intelligent Systems
November 9 - 12, 2020

You must register for the meeting in order to submit abstracts.
After registering you will be sent a web link for abstract submission by email.
You may copy and paste your abstract from Word, Google Docs, or Notepad; abstracts are limited to ~2900 characters.

Virtual Meeting program informationAn preliminary PDF of the program abstract book will be sent approximately 5 days prior to the first day of the meeting.  The final, hyperlinked abstract book will be available for download on the first morning of the meeting.

**Please check your email for the length of your talk, poster instructions, links to the webinar, and how to prepare and submit your poster PDF for the virtual poster session. 


Abstract Status


        

Presenting Author

Title

Talk/Poster

Abbasi-Asl, Reza

The DeepTune framework for modeling and characterizing neurons in visual cortex

poster

Aenugu, Sneha

A neural reinterpretation of long short-term memory

poster

Aghamohammadi, Cina

Unbiased partitioning of spiking variability to reveal decision computations

poster

Ahmad, Subutai

Sparsity in the neocortex, and its implications for machine learning

poster

Akaishi, Rei

Multiscale neural computations and exploitation/exploration behavior

poster

Aldarondo, Diego E

Analyzing the neural dynamics underlying hierarchical motor control in a virtual rodent

poster

Almanza, Mark

A comparison of neural network and penalized regression approaches for fast neurochemical detection in humans and rodents

poster

Amsalem, Oren

Analytical reduction of detailed nonlinear neuron models for biologically-inspired machine learning

poster

Anokhin, Konstantin

Towards principles of neuromorphic memory—Selective allocation of associative memory in the mouse brain circuits

poster

Artoni, Pietro

Deep learning of spontaneous arousal fluctuations detects early cholinergic defects across neurodevelopmental mouse models and patients

poster

Arun, SP

Towards a dialogue between machine vision and biological vision

poster

Bae, Hyojin

Lessons from artificial neural network for studying coding principles of biological neural network

poster

Barabasi, Daniel L

A genetically-encoded connectome model for neural network evolution

talk

Bengio, Yoshua

Towards bridging the gap between backprop and neuroscience

talk

Beniaguev, David

Single cortical neurons as deep artificial neural networks

poster

Benjamin, Asaf

Neural representations of social information in the mouse prefrontal cortex

poster

Beuth, Frederik

Predicting how the brain solves different visual task classes

poster

Blakeman, Sam

A complementary learning systems approach to temporal difference learning

poster

Bohm, Clifford

Can evolution help us discover artificial intelligence?

poster

Bordelon, Blake A

Optimal spectral properties of population codes for noise robust readout

poster

Borgohain, Satya

Self-organising neural network hierarchy

poster

Borthakur, Ayon

Lifelong learning in the wild using Intel Loihi

talk

Braun, Lukas

Online learning of neural computations from sparse temporal feedback

poster

Cadena, Santiago A

How well do deep neural networks trained on object recognition characterize the mouse visual system?

poster

Chapman, William G

Trajectory prediction in a biologically inspired network

poster

Chapochnikov, Nikolai

Mechanistic model of a neural circuit implementing whitening in olfaction

poster

Chartier, Thomas F

Symmetry inference, an important feature for AI systems

poster

Chen, Jiang-fan

Calcium signal from M1 neural populations support the cross-day neuroprosthetic learning with stable neuroplasticity mapping

poster

Chklovskii, Dmitri

A visual motion detector—From the connectome to a theory of transformation learning

talk

Churchland, Anne

Movements, decisions, and wholistic behavior

talk

Collman, Forrest C

Complexity of cortical cell types signaling pathways

poster

Conwell, Colin

Mouse brain in the modeling zoo—Neural architecture search and taskonomy for unveiling the representational structure of rodent visual cortex

poster

Cornille, Nathan

Improving representation learning with pervasive internal regression (PIR)

poster

Cowley, Benjamin R

From vision to decision—Deep neural network modeling of visuomotor transformations during social interaction

poster

Cueva, Christopher

Emergence of functional and structural properties of the head direction system by optimization of recurrent neural networks

poster

Czegel, Daniel

Emergent evolutionary dynamics over recurrent neural computations

poster

Davidson, Guy

Investigating simple object representations in model-free deep reinforcement learning

poster

Deny, Stéphane

An empirical study of inductive biases in deep neural networks

poster

Diao, Huitian

Predicting single cell-fate decisions in CD8 T cells responding to viral infection

poster

Dorkenwald, Sven M

Binary and analog variation of synapses between cortical pyramidal neurons

poster

Doron, Michael

Using prior knowledge to automatically discover interesting phenomena in computational models

poster

Dyballa, Luciano

Deep artificial neural networks—Little brains or big retinas?

talk

Finn, Chelsea

How not to create a robot's mind

talk

Fomins, Aleksejs

Information-theoretic pipeline for uncovering whole-brain spatio-temporal patterns from mesoscopic calcium recordings

poster

Fraser, Maia

Temporo-spatial hierarchy and reinforcement learning - enabling richer alignment with the environment for more general AI

talk

Gardner, Daniel

Are neural circuits and computations evolutionarily conserved? New potential designs for AI systems

poster

Gazula, Harshvardhan

Attention-coupled saliency enhances the interpretability of recurrent models

poster

Geadah, Victor

Single-neuron nonlinearities and their impact on learning dynamics of recurrent networks

talk

Genkin, Mikhail

Discovering interpretable models of population dynamics from neural activity recordings

poster

George, Dileep

Recursive cortical network—A generative vision model with deep grounding in neuroscience

talk

Ghazizadeh, Elham

Learned attractor dynamics for sequential working memory

poster

Goeltz, Julian

Fast and deep neuromorphic learning with time-to-first-spike coding

poster

Gold, Carl

Shallow learning in spiking neural networks using dendritic connection rules based on topography

poster

Golden, Ryan

Hippocampal indexing at the onset of cortical up states promotes consolidation and prevents retroactive interference

poster

Gordon, Jeremy R

Long distance relationships without time travel—Boosting the performance of a sparse predictive autoencoder in sequence modeling

poster

Goudar, Vishwa

Elucidating the neural mechanisms of learning-to-learn

talk

Han, Yena

Unsupervised learning of latent variables from continuously changing data

poster

Hawkins, Jeff

How the brain uses references frames to learn a model of the world, and why AI needs to do the same

talk

Heiney, Kristine A

Computational behavior of biological neural networks through the lens of criticality

poster

Huang, Ben S

OpenCortex—An integrated platform for deconstructing cortex-wide cognitive networks in behaving mice

poster

Huse Ramstad, Ola

Neural network models informed by network electrophysiology

poster

Jacob, Georgin

Do deep neural networks see the way we do?

poster

Jain, Shailee

Natural language encoding models for fMRI reveal distinct patterns of semantic integration across cortex

poster

Jang, Jaeson

Emergence of face-selective neurons in untrained deep neural networks

poster

Jang, Jaeson

Emergence of number selectivity in untrained deep neural networks

poster

Janik, Romuald A

Entropy from machine learning―Defining entropic characteristics of deep neural networks and complexity of datasets

poster

Jensen, Kristopher T

Self-supervised learning for multisensory integration in biologically inspired networks

poster

Ji, Ni

A biological neural network balancing exploration versus exploitation during foraging

talk

Jordan, Jakob

Conductance-based dendrites perform reliability-weighted opinion pooling

poster

Kadkhodaie, Zahra

Learning and utilizing a prior for natural images with deep neural networks

poster

Kalidindi, Hari T

Quasi-oscillatory dynamics in motor cortex are consistent with a feedback-driven system

poster

Katti, Harish

Cracking CAPTCHAs using a separable neural code

poster

Kenyon, Garrett

Using models of cortical development based on sparse coding to discriminate between real and synthetically generated faces

poster

Kim, Edward

Inhibitory and excitatory top-down feedback for visual perception

poster

Kim, Jineun

Rapid, biphasic CRF neuronal responses encode positive and negative valence

poster

Klindt, David A

Unsupervised learning of image manifolds with mutual information

poster

Klukas, Mirko

Representing non-Euclidean spaces and abstract data structures with grid cells and place cells

poster

Konkle, Talia

Emergence of multiple visual areas without a feature hierarchy

talk

Koo, Peter

Neural networks that learn robust features are more robust and interpretable

poster

Kording, Konrad

Geometrical ways of thinking about deep learning and brain activities

talk

Kornfeld, Joergen M

A connectomic substrate of credit assignment in basal ganglia reinforcement learning

poster

Kosoy, Eliza

Children’s intrinsic exploration of mazes compared to exploration algorithms

poster

Koulakov, Alex

Genomic bottleneck approach to faster learning

poster

Koulakov, Alex

Reinforcement learning basis of social conflict

poster

Kowadlo, Gideon

Use of an artificial hippocampal algorithm for one-shot and continual learning

poster

Krotov, Dmitry

Bio-inspired hashing for unsupervised similarity search

poster

Kudithipudi, Dhireesha

Brain-inspired local metaplasticity for lifelong learning

talk

Kumar, M Ganesh

Learning multiple cue-reward location associations with a reservoir computing model and temporal difference error-modulated Hebbian plasticity

poster

Kvitsiani, Duda

Normative account for choice history bias in mice and humans

poster

Kwapich, Robert S

Unsupervised identification of brain-state dynamics in mice from multi-channel LFP recordings

poster

Lacefield, Clay

A proposed neural network architecture for autonomous control based on the mammalian cortico-striatal system

poster

Lai Lucy

A computational division of labor for motor skill learning

talk

Landau, Andrew T

Learning rules mediating complex computation in biological neurons

poster

Langdon, Christopher M

Multi-area recurrent neural network model of decision-making

poster

Launay, Julien

Computer vision and feedback alignment methods

poster

Lavin, Alexander

Integration of human-like covert-overt attention with probabilistic convolutional neural nets

poster

Leadholm, Niels

Hierarchical feature binding in convolutional neural networks confers resistance to adversarial attacks

poster

Li, Ye

Orientation and color tuning of gamma range activity in human visual cortex

poster

Lim, Woochang

Influence of various temporal recoding on Pavlovian eyeblink conditioning in the cerebellum

poster

Lin, Yen-Chu

Cognitive influences on fixational eye movements (FEM) during visual discrimination

poster

Linsley, Drew A

The function of contextual illusions

poster

Lipshutz, David

A biologically plausible neural circuit for slow feature analysis

poster

Lipshutz, David

A canonical correlation analysis model of the cortical microcircuit

poster

Liu, Yanhe Y

A prefrontal top-down circuit underlying inference-based flexible decision-making

poster

Liu, Yue

Unifying spectral models of reinforcement learning in the Laplace domain

poster

Logiaco, Laureline

A thalamocortical model solves sequencing tasks more robustly than backpropagation-trained RNNs

talk

Lowe, Scott C

Higher-order activation functions

poster

Lu, Jinghao

Cortical representations of painful facial stimuli and vibrotactile touch-mediated-analgesia

poster

Luther, Kyle

A label-based measure of invariance in neural networks

poster

Madireddy, Sandeep

Metalearning for spiking neurons

poster

Makino, Hiroshi

Cortical representations of theoretical variables in reinforcement learning

poster

Man, Kingson

Truth or consequences—Homeostatic self-regulation in artificial neural networks

poster

Marino, Joseph L

Predictive coding, variational autoencoders, and biological connections

poster

Martin, Erwann

Spiking equilibrium propagation for intrinsic learning hardware

talk

Masset, Paul

A computational architecture for early olfactory processing

poster

Meadows, Austin

Sniffing out immune cell infiltration in solid tumors

poster

Mitchell, Kevin

The evolution of agency—Or how to give a robot a soul

talk

Moldwin, Toviah

The Gradient Clusteron—A gradient-based method for supervised learning via local dendritic nonlinearities and structural plasticity

poster

Moya-Sanchez, Eduardo Ulises

Deterministic CNN layer inspired on V1-cortex cells with illumination invariance and rotation equivariance response

poster

Nejatbakhsh, Amin

Correlating non-simultaneous neural data

poster

Nejatbakhsh, Amin

Joint segmentation and labeling of C. elegans neurons

poster

Niv, Yael

Hippocampus-orbitofrontal interactions in building a cognitive map of task space

talk

Olshausen, Bruno

Sparse coding, manifold flattening and persistence as organizing principles of visual representation

talk

Paiton, Dylan M

Response surfaces reveal invariances and selectivity in V1 neurons

poster

Panda, Priyadarshini

Towards scalable spike-based learning with backward residual connections

talk

Pandey, Biraj

Random feature networks with neuronal tuning

poster

Pao, Gerald

Manifold networks of brain activity embeddings that generate naturalistic behaviors

poster

Parde, Connor J

Concurrent representational codes in DCNNs trained for face identification

poster

Parthasarathy, Nikhil

Self-supervised learning of a visual texture representation for cortical area V2

poster

Pearlmutter, Barak

Learning to learn compositionally without gradient descent by gradient descent

talk

Pedigo, Benjamin D

A quantitative comparison of a complete connectome to artificial intelligence architectures

poster

Pereira, Talmo D

Deep generative modeling of biological sensorimotor transformations via imitation learning

poster

Philippides, Andrew

Insect-inspired autonomous visual navigation—Smart tricks from small brains

talk

Pitkow, Xaq

Rational thoughts in neural codes

talk

Pontes-Filho, Sidney

Towards the evolution of spiking neural networks for self-supervision with neuroplasticity

poster

Puelma Touzel, Maximilian

Neuro-inspired reinforcement learning for episodic tasks

poster

Qin, Shanshan

Contrastive similarity matching for supervised learning

poster

Rahimi Moghaddam, Shima

Learning from temporally smooth information

poster

Rawat, Shivang

Generalized ORGaNICs―Towards a unifying framework for neural dynamics

poster

Reimers, Mark

The modular mind gives way to the dynamic brain

poster

Ricci, Matthew

"Kura-Net"—An end-to-end differentiable featuring binding algorithm using the Kuramoto model

poster

Rinkus, Gerard J

A combinatorial population code can simultaneously transmit the full similarity (likelihood) distribution via an atemporal first-spike code

poster

Roach, James P

Inhibitory circuit structure and the temporal dynamics of decision-making.

poster

Robinson, Brian S

A cortical spiking network model for semantic representation and replay-based association acquisition

poster

Ryu, Jungwon

Brain-like autoencoder that learns latent covariance structure

poster

Safron, Adam

Brains as Kalman variational autoencoding heterarchies―The conscious turbo-code

poster

Sarkar, Aakash

Scale-dependent relationships in natural language

poster

Savin, Cristina

Computing and learning in the presence of neural noise

talk

Saxena, Shreya

The hypothesis of low trajectory tangling predicts motor cortex population activity across movement speeds

poster

Schossau, Jory

Evolution of curiosity

poster

Segert, Simon

Relaxed graph matching for analogy and reasoning

poster

Sejnowski, Terrence

Strong inhibitory signaling underlies stable temporal dynamics and working memory in spiking neural networks

talk

Sekhar, Sudarshan

A hybrid neural network / Kalman filter decoder improves brain-computer interface performance

poster

Shen, Yang

A correspondence between normalization strategies in artificial and real neural networks

talk

Shi, Jianghong

CNN MouseNet―Biologically constrained convolutional neural network model
for mouse visual cortex

poster

Shi, Yanliang

Spatiotemporal neural correlations and dynamics in neural networks with spatial network architectures

poster

Shin, Jae Hoon

Deep interaction between reinforcement learning algorithms and human reinforcement learning

poster

Shuvaev, Sergey

Neural networks with motivation

talk

Singh, Satpreet Harcharan

Understanding biological plume tracking behavior using deep reinforcement-learning

poster

Sizikova, Elena

Word recognition in humans and deep neural networks

poster

Sokol, Piotr A

Unexpected benefits of learning with neural oscillations—Stable backpropagation with limit cycles

poster

Solla, Sara A

A Bayesian theory of supervised learning

talk

Srinivasan, Shyam

A winner-take-all mechanism balances the trade-off between neuronal variability and discrimination

poster

Sussillo, David

Universality and individuality in neural dynamics across large populations of recurrent networks

talk

Tamari, Ronen

Language (re)modelling—Towards embodied inductive biases for language understanding

poster

Tanaka, Hidenori

From deep learning to mechanistic understanding in neuroscience—Tthe structure of retinal prediction

poster

Tapson, Jonathan

Brain-inspired computing and the algorithm problem

poster

Tepper, Mariano H

Learning neural Nyström representations

poster

Teti, Michael

Can sparse coding account for non-classical receptive field effects in V1 simple cells?

poster

Tolias, Andreas

A less artificial intelligence

talk

Toosi, Tahereh

Symbiotic learning of feedforward and feedback networks

talk

Topalovic, Uros

Deep learning methods for exploring human cognition

poster

Tran, Ngoc

DeepNose—Using artificial neural networks to represent the space of odorants

talk

Tresp, Volker

The tensor brain

talk

Tripp, Bryan P

Simulated environment for naturalistic mouse models

poster

Turcu, Denis

Using a Sparse RNN for dynamic binary classification

poster

Versace, Elisabetta

Priors for generalization—Insights from newborn chicks

poster

Vogelstein, Joshua

A biological implementation of lifelong learning in the pursuit of artificial general intelligence

poster

Wanner, Adrian A

How recurrent is the network of strong connections in the neocortex?

poster

Xie, Marjorie

The significance of sparse representations in cerebellum-like networks

poster

Yamakawa, Hiroshi

Understanding the computational meaning of the neocortical interrarea signals

poster

Yamashiro, Kotaro

Decoding complex sensory stimuli from neuronal activity of rat somatosensory cortex

poster

Yang, Guangyu Robert

Evolving the olfactory system

poster

Yang, Runzhe

Unsupervised feature discovery by neural networks with disynaptic recurrent inhibition

talk

Yilmaz, Hakan

Inverse graphics explains population responses in body-selective regions of the primate inferotemporal cortex

poster

Zapp, Soren J

Inference of functional network structure using matrix factorization

poster

Zhu, Hanlin

Acquiring long-term, large-scale neural data to accelerate discoveries at the intersection of Neuroscience and AI

poster

Zhu, Yuqing

Addition of neocortical features permits successful training of spiking neuronal network models

poster