[HTML][HTML] Continuous attractor neural networks: candidate of a canonical model for neural information representation
Owing to its many computationally desirable properties, the model of continuous attractor
neural networks (CANNs) has been successfully applied to describe the encoding of simple …
neural networks (CANNs) has been successfully applied to describe the encoding of simple …
Fundamental limits on persistent activity in networks of noisy neurons
Neural noise limits the fidelity of representations in the brain. This limitation has been
extensively analyzed for sensory coding. However, in short-term memory and integrator …
extensively analyzed for sensory coding. However, in short-term memory and integrator …
[HTML][HTML] Stability of working memory in continuous attractor networks under the control of short-term plasticity
Continuous attractor models of working-memory store continuous-valued information in
continuous state-spaces, but are sensitive to noise processes that degrade memory …
continuous state-spaces, but are sensitive to noise processes that degrade memory …
[HTML][HTML] Continuous attractors for dynamic memories
Episodic memory has a dynamic nature: when we recall past episodes, we retrieve not only
their content, but also their temporal structure. The phenomenon of replay, in the …
their content, but also their temporal structure. The phenomenon of replay, in the …
Slow and weak attractor computation embedded in fast and strong EI balanced neural dynamics
Attractor networks require neuronal connections to be highly structured in order to maintain
attractor states that represent information, while excitation and inhibition balanced networks …
attractor states that represent information, while excitation and inhibition balanced networks …
[HTML][HTML] Firing rate adaptation affords place cell theta sweeps, phase precession, and procession
Hippocampal place cells in freely moving rodents display both theta phase precession and
procession, which is thought to play important roles in cognition, but the neural mechanism …
procession, which is thought to play important roles in cognition, but the neural mechanism …
[HTML][HTML] Fractional neural sampling as a theory of spatiotemporal probabilistic computations in neural circuits
Y Qi, P Gong - Nature communications, 2022 - nature.com
A range of perceptual and cognitive processes have been characterized from the
perspective of probabilistic representations and inference. To understand the neural circuit …
perspective of probabilistic representations and inference. To understand the neural circuit …
Adaptation accelerating sampling-based bayesian inference in attractor neural networks
The brain performs probabilistic Bayesian inference to interpret the external world. The
sampling-based view assumes that the brain represents the stimulus posterior distribution …
sampling-based view assumes that the brain represents the stimulus posterior distribution …
Decentralized multisensory information integration in neural systems
How multiple sensory cues are integrated in neural circuitry remains a challenge. The
common hypothesis is that information integration might be accomplished in a dedicated …
common hypothesis is that information integration might be accomplished in a dedicated …
Phase reduction of waves, patterns, and oscillations subject to spatially extended noise
J MacLaurin - SIAM Journal on Applied Mathematics, 2023 - SIAM
In this paper we present a framework in which one can rigorously study the effect of spatio-
temporal noise on traveling waves, stationary patterns, and oscillations that are invariant …
temporal noise on traveling waves, stationary patterns, and oscillations that are invariant …