Efficient computation and cue integration with noisy population codes

By Sophie Denève, Peter E. Latham, Alexandre Pouget. Nature Neuroscience, 2001

390 citations recorded by the source corpus.

Subfields: Artificial Intelligence, Cognitive Neuroscience, Electrical and Electronic Engineering

View Paper: https://www.semanticscholar.org/paper/feb1adce32c24e99844710bed5569e3dccadd998

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Citations in the corpus

A connectome of the Drosophila central complex reveals network motifs suitable for flexible navigation and context-dependent action selection (2020, background): “…should provide an implementation-level understanding of a variety of computations related to dynamic multisensory integration (Pouget et al., 2002) and the resolution of conflicts between cues of different reliability (Deneve et al., 2001; Hoinville and Wehner, 2018; Wystrach et al., 2015).”
A Neural Implementation of the Kalman Filter (2009, background): “Several authors have proposed models addressing aspects of this issue [15, 10, 9, 19, 2, 3, 16, 4, 11, 18, 17, 7, 6, 8], but as yet, there is no conclusive experimental evidence in favour of any one and the question remains open.”
Vestibular system: the many facets of a multimodal sense. (2008, neutral): “…information from disparate sources (e.g., visual and auditory or vestibular) needs to be brought into a common frame of reference (Cohen & Andersen 2002) before it can be combined in a useful way, although this assumption has recently been challenged (Deneve et al. 2001, Avillac et al. 2005).”
Intention, action planning, and decision making in parietal-frontal circuits. (2009, background): “Intermediate representations occur in the middle layer if there is strong recurrent feedback from the output layer or if the network has separate output layers that code in different coordinate frames (Deneve et al., 2001; Xing and Andersen, 2000b).”
A Novel Approach for the Implementation of Large Scale Spiking Neural Networks on FPGA Hardware (2005, methodology): “A biologically plausible strategy was developed based on the principle of the basis function network proposed by Deneve et al [18] and was further extended by incorporating the STDP algorithm described in section 2 to train the network to perform the function y = x – c.”
A Neural Network Model of Ventriloquism Effect and Aftereffect (2012, neutral): “used Bayesian models also to describe ventriloquism aftereffect; still, the underlying neural activity, circuitry and mechanisms are not elucidated. Some theoretical studies”
Multisensory Interaction in Saccadic Reaction Time: A Time-Window-of-Integration Model (2004, neutral): “Deneve, Latham, & Pouget, 2001; Xing & 1 Universitaet Oldenburg, 2 International University Bremen”
Probabilistic brains: knowns and unknowns (2013, result): “Such an implementation is consistent with the of motor neurons such as the ones found in the motor layer of the superior colliculus 61,62 .”
Inference and computation with population codes. (2003, methodology): “When the probability distributions are encoded using the position and gain of population codes, the only solution that has been proposed so far is that of Deneve et al. (2001), which we reviewed in the first half of this paper.”