Integrated neural dynamics of sensorimotor decisions and actions

D Thura, JF Cabana, A Feghaly, P Cisek - PLoS biology, 2022 - journals.plos.org
Recent theoretical models suggest that deciding about actions and executing them are not
implemented by completely distinct neural mechanisms but are instead two modes of an …

Adaptation accelerating sampling-based bayesian inference in attractor neural networks

X Dong, Z Ji, T Chu, T Huang… - Advances in Neural …, 2022 - proceedings.neurips.cc
The brain performs probabilistic Bayesian inference to interpret the external world. The
sampling-based view assumes that the brain represents the stimulus posterior distribution …

BrainPy: a flexible, integrative, efficient, and extensible framework towards general-purpose brain dynamics programming

C Wang, X Chen, T Zhang, S Wu - bioRxiv, 2022 - biorxiv.org
The neural mechanisms underlying brain functions are extremely complicated. Brain
dynamics modeling is an indispensable tool for elucidating these mechanisms by modeling …

Translation-equivariant representation in recurrent networks with a continuous manifold of attractors

W Zhang, YN Wu, S Wu - Advances in Neural Information …, 2022 - proceedings.neurips.cc
Equivariant representation is necessary for the brain and artificial perceptual systems to
faithfully represent the stimulus under some (Lie) group transformations. However, it remains …

Oscillatory tracking of continuous attractor neural networks account for phase precession and procession of hippocampal place cells

T Chu, Z Ji, J Zuo, W Zhang… - Advances in Neural …, 2022 - proceedings.neurips.cc
Hippocampal place cells of freely moving rodents display an intriguing temporal
organization in their responses known astheta phase precession', in which individual …

Brain-inspired multiple-target tracking using Dynamic Neural Fields

S Kamkar, HA Moghaddam, R Lashgari, W Erlhagen - Neural Networks, 2022 - Elsevier
Despite considerable progress in the field of automatic multi-target tracking, several
problems such as data association remained challenging. On the other hand, cognitive …

Continuous Recurrent Neural Networks Based on Function Satlins: Coexistence of Multiple Continuous Attractors

Y Huang, J Yu, J Leng, B Liu, Z Yi - Neural Processing Letters, 2022 - Springer
The brief investigates the coexistence of multiple continuous attractors in a recurrent neural
network, ie, the symmetric saturated Satlins linear neural networks, based on a …

Multiple bumps can enhance robustness to noise in continuous attractor networks

R Wang, L Kang - PLOS Computational Biology, 2022 - journals.plos.org
A central function of continuous attractor networks is encoding coordinates and accurately
updating their values through path integration. To do so, these networks produce localized …

Firing rate adaptation in continuous attractor neural networks accounts for theta phase shift of hippocampal place cells

T Chu, Z Ji, J Zuo, Y Mi, W Zhang, T Huang, D Bush… - bioRxiv, 2022 - biorxiv.org
Hippocampal place cells of freely moving animals display 'theta phase precession', whereby
spikes are fired at successively earlier phases of the 6-10 Hz local field potential (LFP) theta …

The Brain-Inspired Cooperative Shared Control for Brain-Machine Interface

S Zheng, L Liu, J Yang, L Qian, G Gao, X Chen… - arXiv preprint arXiv …, 2022 - arxiv.org
In the practical application of brain-machine interface technology, the problem often faced is
the low information content and high noise of the neural signals collected by the electrode …