• Publications
  • Influence
Synchronous Firing and Higher-Order Interactions in Neuron Pool
TLDR
A simple model in which neurons receive common overlapping inputs is analyzed and it is proved that such a model can have a widespread distribution of activity, generating higher-order stochastic interactions. Expand
Action Potential Initiation in Neocortical Inhibitory Interneurons
TLDR
It is found that different populations of inhibitory interneurons in the cerebral cortex express distinct subtypes of sodium channels, resulting in diverse action potential thresholds and network excitability. Expand
Towards artificial general intelligence with hybrid Tianjic chip architecture
TLDR
The Tianjic chip is presented, which integrates neuroscience-oriented and computer-science-oriented approaches to artificial general intelligence to provide a hybrid, synergistic platform and is expected to stimulate AGI development by paving the way to more generalized hardware platforms. Expand
Population Coding with Correlation and an Unfaithful Model
TLDR
It is proved that UMLI is asymptotically efficient when the neuronal correlation is uniform or of limited range and has advantages of decreasing the computational complexity remarkably and maintaining high-leveldecoding accuracy. Expand
Dynamics and Computation of Continuous Attractors
TLDR
This work develops a strategy to reduce the dynamics of a large-size network by utilizing the fact that a continuous attractor can eliminate the noise components perpendicular to the attractor space very quickly, and simplifies it successfully as a one-dimensional Ornstein-Uhlenbeck process. Expand
Decentralized Multisensory Information Integration in Neural Systems
TLDR
A decentralized architecture for multisensory integration is proposed, in which no processor is in the center of the network topology and information integration is achieved in a distributed manner through reciprocally connected local processors. Expand
Population Coding and Decoding in a Neural Field: A Computational Study
TLDR
This study re-discovers main results in existing literatures in a unified way, but also reveals important new features, especially when the neural correlation is strong, as well as clarifying the asymptotic efficiency of the maximum likelihood inference (MLI) type of decoding methods for correlated neural signals. Expand
Compensating time delays with neural predictions: are predictions sensory or motor?
  • R. Nijhawan, Si Wu
  • Computer Science, Medicine
  • Philosophical Transactions of the Royal Society A…
  • 28 March 2009
TLDR
This paper presents evidence showing that compensation can happen in both the motor and sensory systems, and that compensation using ‘diagonal neural pathways’ is a suitable strategy for implementing compensation in the visual system. Expand
Computing with Continuous Attractors: Stability and Online Aspects
  • Si Wu, S. Amari
  • Mathematics, Medicine
  • Neural Computation
  • 1 October 2005
TLDR
This study modified the conventional network model by including extra dynamical interactions between neurons, which effectively implements online Bayesian inference and reveals some interesting behavior in neural population coding, such as the trade-off between decoding stability and the speed of tracking time-varying stimuli. Expand
Selective Modulation of Axonal Sodium Channel Subtypes by 5‐HT1A Receptor in Cortical Pyramidal Neuron
TLDR
Results reveal a selective modulation of NaV1.2 distributed at the proximal AIS region and AP backpropagation by 5‐HT1A receptors, suggesting a potential mechanism for serotonergic regulation of functional polarization in the dendro‐axonal axis, synaptic plasticity and PFC functions. Expand
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