Check the Meetings table below for the topics of future meetings.
Below are the upcoming journal clubs, as well as summaries of previous meetings.
| Date | Presenter | Reading |
|---|---|---|
|
2020/12/09 |
Kai Chen |
Generating Coherent Patterns of Activity from Chaotic Neural Networks. |
|
2021/04/21 |
Kai Chen |
Universality and individuality in neural dynamics across large populations of recurrent networks. |
|
2021/05/20 |
Kai Chen |
One Step Back, Two Steps Forward: Interference and Learning in Recurrent Neural Networks. |
|
2021/08/18 |
Boran Yang |
Graph neural fields: A framework for spatiotemporal dynamical models on the human connectome. |
|
2021/09/08 |
Kai Chen |
Learning function from structure in neuromorphic networks. |
|
2021/11/29 |
Boran Yang |
Biophysical Modeling of Large-Scale Brain Dynamics and Applications for Computational Psychiatry. |
|
2021/12/13 |
Kai Chen |
Context-dependent computation by recurrent dynamics in prefrontal cortex. |
|
2021/12/27 |
Jingcheng Shi |
Task representations in neural networks trained to perform many cognitive tasks. |
|
2022/02/09 |
Boran Yang |
ReduNet: A White-box Deep Network from the Principle of Maximizing Rate Reduction. |
|
2022/02/16 |
Bo Wang |
Self-backpropagation of synaptic modifications elevates the efficiency of spiking and artificial neural networks. |
|
2022/02/21 |
Xuexing Du |
Analysis and applications of the Locally Competitive Algorithm. |
|
2022/02/23 |
Kai Chen |
The role of population structure in computations through neural dynamics. |
|
2022/02/28 |
Mingzhang Wang |
Larger GPU-accelerated brain simulations with procedural connectivity. |
|
2022/03/02 |
Ziling Wang |
The striatum organizes 3D behavior via moment-to-moment action selection. |
|
2022/03/07 |
Licheng Zou |
Linking Connectivity, Dynamics, and Computations in Low-Rank Recurrent Neural Networks (1). |
|
2022/03/09 |
Licheng Zou |
Linking Connectivity, Dynamics, and Computations in Low-Rank Recurrent Neural Networks (2). |
|
2022/03/14 |
Zheng Wang |
Random Matrix Methods for Machine Learning: When Theory meets Applications. |
|
2022/03/16 |
Chongming Liu |
Transmission trend of the COVID-19 pandemic predicted by dendritic neural regression. |
|
2022/03/21 |
Jingyang Ma |
Avoiding catastrophe: active dendrites enable multi-task learning in dynamic environments. |
|
2022/03/23 |
Rong Chen |
The node-similarity distribution of complex networks and it's application in link prediction. |
|
2022/03/28 |
Jingcheng Shi |
Circuit mechanisms for the maintenance and manipulation of information in working memory. |
|
2022/03/30 |
Chongming Liu |
Towards Provable Learning of Polynomial Neural Networks Using Low-Rank Matrix Estimation. |
|
2022/04/06 |
Boran Yang |
Sensory-Motor Cortices Shape Functional Connectivity Dynamics in the Human Brain. |
|
2022/04/11 |
Muhan Ma |
Macroscopic gradients of synaptic excitation and inhibition in the neocortex. |
|
2022/04/13 |
Zheng Wang |
A random matrix approach to neural networks. |
|
2022/04/18 |
Kai Chen |
Organizing recurrent network dynamics by task-computation to enable continual learning. |
|
2022/04/20 |
Licheng Zou |
Mechanisms of distributed working memory in a large-scale network of macaque neocortex. |
|
2022/04/25 |
Ziling Wang |
Untangling stability and gain modulation in cortical circuits with multiple interneuron classes. |
|
2022/04/27 |
Rong Chen |
Multi-level Graph Convolutional Networks for Cross-platform Anchor Link Prediction. |
|
2022/05/02 |
Jingyang Ma |
Ultrafast Simulation of Large-Scale Neocortical Microcircuitry with Biophysically Realistic Neurons. |
|
2022/05/04 |
Mingzhang Wang |
Training dynamically balanced excitatory-inhibitory networks. |
|
2022/05/13 |
Xuexing Du |
[Project report] Introduction to the neural circuit for locomotion in C.elegans. |
|
2022/05/16 |
Bo Wang |
Learning to live with Dale's principle: ANNs with separate excitatory and inhibitory units. |
|
2022/05/20 |
Zhenyuan Jin |
Dynamic models of large-scale brain activity. |
|
2022/05/23 |
Kai Chen |
Parametric Control of Flexible Timing Through Low-Dimensional Neural Manifolds (1). |
|
2022/05/27 |
Kai Chen |
Parametric Control of Flexible Timing Through Low-Dimensional Neural Manifolds (2). |
|
2022/06/03 |
Ziling Wang |
Deep brain stimulation in the subthalamic nucleus for Parkinson’s disease can restore dynamics of striatal networks. |
|
2022/06/06 |
Rong Chen |
Spiking Graph Convolutional Networks. |
|
2022/06/10 |
Mingzhang Wang |
Nonlinear stimulus representations in neural circuits with approximate excitatory-inhibitory balance. |
|
2022/06/13 |
Jingcheng Shi |
[Project report] The study of working memory mechanisms based on recurrent neural networks. |
|
2022/06/17 |
Chongming Liu |
Review of deep learning: concepts, CNN architectures, challenges, applications, future directions. |
|
2022/06/20 |
Bo Wang |
A Long Short-Term Memory for AI Applications in Spike-based Neuromorphic Hardware. |
|
2022/07/08 |
Xuexing Du |
Can we reverse-engineer the simple brain of a tiny worm?. |
|
2022/07/11 |
Licheng Zou |
A dopamine gradient controls access to distributed working memory in the large-scale monkey cortex. |
|
2022/07/15 |
Zheng Wang |
Reservoirs Learn to Learn. |
|
2022/07/19 |
Kai Chen |
Tensor Analysis Reveals Distinct Population Structure that Parallels the Different Computational Roles of Areas M1 and V1. |
|
2022/07/22 |
Chongming Liu |
Backpropagation Neural Tree. |
|
2022/08/02 |
Jingcheng Shi |
'Activity-silent' working memory in prefrontal cortex: a dynamic coding framework. |
|
2022/08/09 |
Muhan Ma |
[Project report] The large scale dynamical model of the macaque cortex. |
|
2022/08/12 |
Ziling Wang |
Learning prediction error neurons in a canonical interneuron circuit. |
|
2022/08/19 |
Bo Wang |
Coding schemes and training methods of SNNs. |
|
2022/08/23 |
Jingyang Ma |
Dendritic Computing: Branching Deeper into Machine Learning. |
|
2022/08/26 |
Xuexing Du |
OpenWorm: overview and recent advances in integrative biological simulation of Caenorhabditis elegans. |
|
2022/08/30 |
Mingzhang Wang |
Excitatory-inhibitory balance modulates the formation and dynamics of neuronal assemblies in cortical networks. |
|
2022/09/09 |
Zhenyuan Jin |
Microscopic theory of intrinsic timescales in spiking neural networks. |
|
2022/09/14 |
Kai Chen |
Emergent reliability in sensory cortical coding and inter-area communication. |
|
2022/09/16 |
Chongming Liu |
Neural network models of decision making. |
|
2022/09/21 |
Boran Yang |
Computational Modeling of EEG and fMRI Paradigms Indicates a Consistent Loss of Pyramidal Cell Synaptic Gain in Schizophrenia. |
|
2022/09/23 |
Zheng Wang |
Backpropagation algorithms and Reservoir Computing in Recurrent Neural Networks for the forecasting of complex spatiotemporal dynamics. |
|
2022/09/28 |
Jingcheng Shi |
Meta-learning synaptic plasticity and memory addressing for continual familiarity detection. |
|
2022/10/04 |
Zhenyuan Jin |
Phase Diagram for Two-layer ReLU Neural Networks at Infinite-width Limit. |
|
2022/10/07 |
Bo Wang |
The techniques of Noise Injection for neural network training. |
|
2022/10/12 |
Ziling Wang |
Sequential and efficient neural-population coding of complex task information. |
|
2022/10/14 |
Xuexing Du |
How do neurons increase their robustness to noise perturbations. |
|
2022/10/19 |
Mingzhang Wang |
Effects of Altered Excitation-Inhibition Balance on Decision Making in a Cortical Circuit Model. |
|
2022/10/21 |
Kai Chen |
Gradient-based learning drives robust representations in recurrent neural networks by balancing compression and expansion. |
|
2022/10/26 |
Chongming Liu |
Learning Overparameterized Neural Networks via Stochastic Gradient Descent on Structured Data. |
|
2022/11/02 |
Jingyang Ma |
A synaptic learning rule for exploiting nonlinear dendritic computation. |
|
2022/11/04 |
Boran Yang |
Functional network organization of the human brain. |
|
2022/11/09 |
Zheng Wang |
Task representations in neural networks trained to perform many cognitive tasks. |
|
2022/11/11 |
Jingcheng Shi |
Flexible multitask computation in recurrent networks utilizes shared dynamical motifs. |
|
2022/11/16 |
Zhenyuan Jin |
Spatialtemporal patterns of adaptation-induced slow oscillations in a whole brain model of slow-wave sleep. |
|
2022/11/18 |
Bo Wang |
Predictive learning as a network mechanism for extracting low-dimensional latent space representations. |
|
2022/11/23 |
Ziling Wang |
Cell-type-specific population dynamics of diverse reward computations. |
|
2022/11/25 |
Xuexing Du |
Rapid detection and recognition of whole brain activity in a freely behaving Caenorhabditis elegans. |
|
2022/11/30 |
Mingzhang Wang |
Closed-form continuous-time neural networks. |
|
2022/12/03 |
Kai Chen |
Extracting computational mechanisms from neural data using low-rank RNNs. |
|
2022/12/07 |
Chongming Liu |
Gradient Descent Maximizes the Margin of Homogeneous Neural Networks. |
|
2022/12/09 |
Jingyang Ma |
The Forward-Forward Algorithm: Some Preliminary Investigations. |
|
2022/12/14 |
Yeqiang Liao |
|
|
2022/12/16 |
Licheng Zou |
Several papers in decision-making. |
|
2022/12/30 |
Xuexing Du |
Energy-efficient network activity from disparate circuit parameters. |
|
2023/01/06 |
Kai Chen |
Flexible selection of task-relevant features through population gating. |
|
2023/01/31 |
Shouwei Luo |
|
|
2023/02/03 |
Zhenyuan Jin |
Multimodal analysis demonstrating the shaping of functional gradients in the marmoset brain. |
|
2023/02/09 |
Chongming Liu |
Brain-Score: Which Artificial Neural Network for Object Recognition is most Brain-Like?. |
|
2023/02/13 |
Zheng Wang |
Implicit Self-Regularization in Deep Neural Networks: Evidence from Random Matrix Theory and Implications for Learning. |
|
2023/02/16 |
Jingyang Ma |
Using single neuron model to predict the spike time and its applications. |
|
2023/02/20 |
Bo Wang |
Brain-inspired chaotic backpropagation for MLP. |
|
2023/02/23 |
Maokai Zhan |
Redefining the connectome: A multi-modal, asymmetric, weighted,and signed description of anatomical connectivity. |
|
2023/02/27 |
Ziling Wang |
Prediction-error neurons in circuits with multiple neuron types: Formation, refinement, and functional implications. |
|
2023/03/02 |
Yixiao Feng |
Scaling of sensory information in large neural populations shows signatures of information-limiting correlations. |
|
2023/03/06 |
Rong Chen |
A Large-Scale High-Density Weighted Structural Connectome of the Macaque Brain Acquired by Predicting Missing Links. |
|
2023/03/09 |
Licheng Zou |
Flexible categorization in perceptual decision making. |
|
2023/03/16 |
Yeqiang Liao |
Fast algorithms for simulation of dynamics based on the bilinear dendritic integration rule. |
|
2023/03/20 |
Mingzhang Wang |
Functional Implications of Dale's Law in Balanced Network Dynamics and Decision Making. |
|
2023/03/23 |
Xuexing Du |
CRBA: A Competitive Rate-Based Algorithm Based on Competitive Spiking Neural Networks. |
|
2023/03/29 |
Kai Chen |
A new theoretical framework jointly explains behavioral and neural variability across subjects performing flexible decision-making. |
|
2023/04/03 |
Boran Yang |
Multitask representations in the human cortex transform along a sensory-to-motor hierarchy. |
|
2023/04/06 |
Yixiao Feng |
Scaling of sensory information in large neural populations shows signatures of information-limiting correlations. |
|
2023/04/10 |
Shouwei Luo |
Dendritic Self-Organizing Maps for Continual Learning. |
|
2023/04/13 |
Zhenyuan Jin |
Specificity and robustness of long-distance connections in weighted, interareal connectomes. |
|
2023/04/17 |
Chongming Liu |
Quadratic neural network: a brain-inspired artificial intelligence model. |
|
2023/04/20 |
Zheng Wang |
Reservoir Computing Beyond Memory-Nonlinearity Trade off. |
|
2023/04/24 |
Xiaoyu Chen |
Modelling and prediction of the dynamic responses of large-scale brain networks during direct electrical stimulation. |
|
2023/05/04 |
Ziling Wang |
Representational geometry of perceptual decisions in the monkey parietal cortex. |
|
2023/05/08 |
Licheng Zou |
Network mechanisms underlying representational drift in area CA1 of hippocampus. |
|
2023/05/18 |
Jiayue Yu |
Undergraduate Project : Using recurrent neural network to train the delay match sample task. |
|
2023/06/05 |
Jingyang Ma |
A brain-inspired computational model for spatio-temporal information processing. |
|
2023/06/15 |
Mingzhang Wang |
Rich-club connectivity, diverse population coupling, and dynamical activity patterns emerging from local cortical circuits. |
|
2023/06/26 |
Xiu Xin |
A model-free approach which was developed to detect temporal change-point in time series. |
|
2023/07/05 |
Yixiao Feng |
Mapping functional brain networks from the structural connectome: Relating the series expansion and rife mode approaches. |
|
2023/07/10 |
Xuexing Du |
Flexible and efficient simulation-based inference for models of decision-making. |
|
2023/07/13 |
Zhankai Mao |
Noise improves the association between effects of local stimulation and structural degree of brain networks. |
|
2023/07/17 |
Zhenyuan Jin |
A Tweaking Principle for Executive Control: Circuit Mechanism for Rule-Based Task Switching and Conflict Resolution. |
|
2023/08/14 |
Chongming Liu |
Low-dimensional models of neural population activity in sensory cortical circuits. |
|
2023/08/17 |
Xiaoyu Chen |
Virtual deep brain stimulation: Multiscale co-simulation of a spiking basal ganglia model and a whole-brain mean-field model with The Virtual Brain. |
|
2023/09/04 |
Zheng Wang |
[project report] The role of recurrent matrix in reservoir computing. |
|
2023/09/07 |
Ziling Wang |
Learnable latent embeddings for joint behavioral and neural analysis. |
|
2023/09/12 |
Boran Yang |
Geometric constraints on human brain function. |
|
2023/09/13 |
Shouwei Luo |
Structured cerebellar connectivity supports resilient pattern separation. |
|
2023/09/25 |
Chongming Liu |
Some papers about the training algorithm of spiking neural networks. |
|
2023/09/27 |
Jiayue Yu |
Neuronal wiring diagram of an adult brain. |
|
2023/10/10 |
Jingyao Zhang |
Bifurcation in space: Emergence of function modularity in the neocortex. |
|
2023/10/30 |
Lishuo Zhang |
Harvesting random embedding for high-frequency change-point detection in temporal complex systems. |
|
2023/11/01 |
Jialin Duan |
|
|
2023/11/06 |
Mingzhang Wang |
Learning better with Dale's Law: A Spectral Perspective. |
|
2023/11/15 |
JiaHua Xiang |
Reconstructing the Mind's Eye:fMRI-to-Image with Contrastive Learning and Diffusion Priors. |
|
2023/11/27 |
Jingyang Ma |
Spiking neurons can discover predictive features by aggregate-label learning. |
|
2023/11/29 |
Jiahan Zhang |
Sensory-motor cortices shape functional connectivity dynamics in the human brain. |
|
2023/12/04 |
Siyuan Shen |
A simple reservoir model of working memory with real values. |
|
2023/12/11 |
Kai Chen |
Theory of coupled neuronal-synaptic dynamics. |
|
2023/12/20 |
Xuexing Du |
Incorporating neuro-inspired adaptability for continual learning in artificial intelligence. |
|
2023/12/25 |
Zhenyuan Jin |
Local and long-distance organization of prefrontal cortex circuits in the marmoset brain. |
|
2024/04/18 |
Lishuo Zhang |
Higher-order Granger reservoir computing: simultaneously achieving scalable complex structures inference and accurate dynamics prediction. |
It has been widely recorded that the population neuronal activities pocess the low dimensional manifold in multiple brain regions, especially PFC. The origin of low dimensional dynamics and the relation between the dynamical properties and the network structures remain open questions. One of the potential solutions is that low dimensional dynamics is generated by low-rank network architectures. This work trained low-rank recurrent neural networks to perform 5 distinct cognitive tasks respectively, and theoretically analyzed the network dynamics performing computation for each task. Their work showed that very few ranks (1-2) of network structure are actually required to well perform those cognitive tasks. For those tasks with flexible input-target mapping, multiple cell-types (sub-populations) are necessary to perform tasks. Overall, their theory of low-rank RNN can extract the effective latent dynamics for computation, and furthermore provide a framework to networks with multitasking ability.
Mante et. al. showed how neurons with complex response coordinate together to do computations of selective integrations in monkey PFC. They trained an siRNN to model the psychophysical behavior of monkeys. By analyzing the modeled siRNN using theory of linear dynamical system, the response of siRNN fits almost perfectly with monkey data in the population level. Furthermore, siRNN produced a novel mechanism to unify selection and integration in a single circuit in terms of line attractor and selection vector.
Human brain can perform various of cognitive tasks and is able to flexibly learn new tasks without interfering other tasks. Whether and how the learning and computing capability is inherited from the brain connectomes remains unknown. This work tried to link the learning function and brain connectome in the framework of reservoir computing. They showed that the brain connectome outperform random network at crtical dynamical regime. Futhermore, they found that functional parcellation helps regulate the information flow which might facilitate the cognitive computation in brain
Catastrophic forgetting is a key issue in continual learning paradigm. Training algorithms, like FORCE, seem to be able to bypass this to some extent. Chen and Barak applied fixed point analysis to explicitly show the change of fixed point structure of networks during training in continual learning scenario. Their work provide intuitions about how learning algorithm and the order of task sequence affect the training in continual learning.
Multi-solution is a prominant feature of ANNs (DNNs/RNNs) when training to perform certain tasks. Is there any common feature between different solutions remains an open questions. This works found that the topology of fixed points of trained network is the universally shared between different network architectures and realizations when those networks are trained for the same task. Further, they demonstrated the topological structure of fixed points of networks indeed interprets computation mechanism of trained networks.