使用具有中度强抑制作用的动态神经场来跟踪种群密度。
Tracking population densities using dynamic neural fields with moderately strong inhibition.
机构信息
Faculty of Computer Science, Dalhousie University, 6050 University Avenue, Halifax, NS, Canada, B3H 1W5,
出版信息
Cogn Neurodyn. 2008 Sep;2(3):171-7. doi: 10.1007/s11571-008-9046-0. Epub 2008 Apr 17.
Abstract
We discuss the ability of dynamic neural fields to track noisy population codes in an online fashion when signals are constantly applied to the recurrent network. To report on the quantitative performance of such networks we perform population decoding of the 'orientation' embedded in the noisy signal and determine which inhibition strength in the network provides the best decoding performance. We also study the performance of decoding on time-varying signals. Simulations of the system show good performance even in the very noisy case and also show that noise is beneficial to decoding time-varying signals.
摘要
我们讨论了动态神经场在信号不断施加于递归网络时以在线方式跟踪噪声群体代码的能力。为了报告此类网络的定量性能，我们对噪声信号中嵌入的“方向”进行了群体解码，并确定了网络中哪种抑制强度提供了最佳解码性能。我们还研究了对时变信号的解码性能。即使在非常嘈杂的情况下，系统的模拟也表现出良好的性能，并且还表明噪声有利于解码时变信号。
相似文献
1
Tracking population densities using dynamic neural fields with moderately strong inhibition.
Cogn Neurodyn. 2008 Sep;2(3):171-7. doi: 10.1007/s11571-008-9046-0. Epub 2008 Apr 17.
2
Impact of Different Acoustic Components on EEG-Based Auditory Attention Decoding in Noisy and Reverberant Conditions.
IEEE Trans Neural Syst Rehabil Eng. 2019 Apr;27(4):652-663. doi: 10.1109/TNSRE.2019.2903404. Epub 2019 Mar 7.
3
Anticipatory Neural Activity Improves the Decoding Accuracy for Dynamic Head-Direction Signals.
J Neurosci. 2019 Apr 10;39(15):2847-2859. doi: 10.1523/JNEUROSCI.2605-18.2019. Epub 2019 Jan 28.
4
Non-linear filtering of ultrasonic signals using neural networks.
Ultrasonics. 2004 Apr;42(1-9):355-60. doi: 10.1016/j.ultras.2003.11.002.
5
EEG-based auditory attention decoding using unprocessed binaural signals in reverberant and noisy conditions?
Annu Int Conf IEEE Eng Med Biol Soc. 2017 Jul;2017:484-488. doi: 10.1109/EMBC.2017.8036867.
6
Speaker separation in realistic noise environments with applications to a cognitively-controlled hearing aid.
Neural Netw. 2021 Aug;140:136-147. doi: 10.1016/j.neunet.2021.02.020. Epub 2021 Mar 4.
7
On Decoding Grid Cell Population Codes Using Approximate Belief Propagation.
Neural Comput. 2017 Mar;29(3):716-734. doi: 10.1162/NECO_a_00902. Epub 2016 Oct 20.
8
Decoding the Attended Speaker From EEG Using Adaptive Evaluation Intervals Captures Fluctuations in Attentional Listening.
Front Neurosci. 2020 Jun 16;14:603. doi: 10.3389/fnins.2020.00603. eCollection 2020.
9
A probabilistic recurrent neural network for decoding hind limb kinematics from multi-segment recordings of the dorsal horn neurons.
J Neural Eng. 2019 Jun;16(3):036023. doi: 10.1088/1741-2552/ab0e51. Epub 2019 Mar 8.
10
Effects of directional sound processing and listener's motivation on EEG responses to continuous noisy speech: Do normal-hearing and aided hearing-impaired listeners differ?
Hear Res. 2019 Jun;377:260-270. doi: 10.1016/j.heares.2019.04.005. Epub 2019 Apr 11.
引用本文的文献
1
The effect of inhibitory neuron on the evolution model of higher-order coupling neural oscillator population.
Comput Math Methods Med. 2014;2014:174274. doi: 10.1155/2014/174274. Epub 2014 Jan 2.
2
Effect of inhibitory feedback on correlated firing of spiking neural network.
Cogn Neurodyn. 2013 Aug;7(4):325-31. doi: 10.1007/s11571-013-9241-5. Epub 2013 Jan 9.
3
Gain modulation by an urgency signal controls the speed-accuracy trade-off in a network model of a cortical decision circuit.
Front Comput Neurosci. 2011 Feb 11;5:7. doi: 10.3389/fncom.2011.00007. eCollection 2011.
4
A dynamic neural field model of mesoscopic cortical activity captured with voltage-sensitive dye imaging.
PLoS Comput Biol. 2010 Sep 9;6(9):e1000919. doi: 10.1371/journal.pcbi.1000919.
本文引用的文献
1
Robustness of neural codes and its implication on natural image processing.
Cogn Neurodyn. 2007 Sep;1(3):261-72. doi: 10.1007/s11571-007-9021-1. Epub 2007 Jul 12.
2
Learning multiple layers of representation.
Trends Cogn Sci. 2007 Oct;11(10):428-34. doi: 10.1016/j.tics.2007.09.004.
3
A theory of cortical responses.
Philos Trans R Soc Lond B Biol Sci. 2005 Apr 29;360(1456):815-36. doi: 10.1098/rstb.2005.1622.
4
Information processing in a neuron ensemble with the multiplicative correlation structure.
Neural Netw. 2004 Mar;17(2):205-14. doi: 10.1016/j.neunet.2003.10.003.
5
Receptive fields, binocular interaction and functional architecture in the cat's visual cortex.
J Physiol. 1962 Jan;160(1):106-54. doi: 10.1113/jphysiol.1962.sp006837.
6
Self-organizing continuous attractor networks and path integration: one-dimensional models of head direction cells.
Network. 2002 May;13(2):217-42.
7
Population coding and decoding in a neural field: a computational study.
Neural Comput. 2002 May;14(5):999-1026. doi: 10.1162/089976602753633367.
8
Efficient computation and cue integration with noisy population codes.
Nat Neurosci. 2001 Aug;4(8):826-31. doi: 10.1038/90541.
9
Information processing with population codes.
Nat Rev Neurosci. 2000 Nov;1(2):125-32. doi: 10.1038/35039062.
10
Population dynamics of spiking neurons: fast transients, asynchronous states, and locking.
Neural Comput. 2000 Jan;12(1):43-89. doi: 10.1162/089976600300015899.
Zotero 插件