Model-free detection of synchrony in neuronal spike trains, with an application to primate somatosensory cortex

被引:3
|
作者
Roy, A [1 ]
Steinmetz, PN [1 ]
Johnson, KO [1 ]
Niebur, E [1 ]
机构
[1] Johns Hopkins Univ, Krieger Mind Brain Inst, Baltimore, MD 21218 USA
基金
美国国家科学基金会;
关键词
synchrony; bootstrap; somatosensory cortex;
D O I
10.1016/S0925-2312(00)00284-8
中图分类号
TP18 [人工智能理论];
学科分类号
081104 ; 0812 ; 0835 ; 1405 ;
摘要
Synchronized neuronal firing has been reported in many neural systems and may play a role in the representation of sensory stimuli and the modification of sensory representations by both experience and attention. In this report we describe a bootstrap procedure for computing the statistical significance of changes in the degree of synchrony and apply it to recordings from the second somatosensory (SII) cortex of Macaques performing tactile and visual discrimination tasks. A majority (68%) of neuron pairs in Sn fire synchronously in response to a tactile stimulus. In a fraction of those pairs (17.5%), the degree of synchrony covaries with the focus of attention. (C) 2000 Elsevier Science B.V. All rights reserved.
引用
收藏
页码:1103 / 1108
页数:6
相关论文
共 50 条
  • [21] in vivo observation of neuronal remodeling in the somatosensory cortex of chronic pain model
    Nabekura, Junichi
    Eto, Kei
    Kim, Sun Kwang
    Inada, Hiroyuki
    NEUROSCIENCE RESEARCH, 2010, 68 : E30 - E30
  • [22] Model-free fault detection: application to Polymer Electrolyte Fuel Cell system
    Ziane, Meziane Ait
    Steiner, Nadia Yousfi
    Join, Cedric
    Benne, Michel
    Damour, Cedric
    Pera, Marie Cecile
    2022 10TH INTERNATIONAL CONFERENCE ON SYSTEMS AND CONTROL (ICSC), 2022, : 340 - 345
  • [23] Model-free adaptive robust control method for high-speed trains
    Li, Zhongqi
    Zhou, Liang
    Yang, Hui
    Yan, Yue
    TRANSPORTATION SAFETY AND ENVIRONMENT, 2024, 6 (01)
  • [24] Model-free direct fault detection and classification
    Hamadouche, Anis
    JOURNAL OF PROCESS CONTROL, 2020, 87 : 130 - 137
  • [25] Model-free adaptive robust control method for high-speed trains
    Zhongqi Li
    Liang Zhou
    Hui Yang
    Yue Yan
    TransportationSafetyandEnvironment, 2024, 6 (01) : 102 - 111
  • [26] Quickest Detection for Abrupt Changes in Neuronal Ensemble Spiking Activity Using Model-based and Model-free Approaches
    Chen, Zhe
    Hu, Sile
    Zhang, Qiaosheng
    Wang, Jing
    2017 8TH INTERNATIONAL IEEE/EMBS CONFERENCE ON NEURAL ENGINEERING (NER), 2017, : 481 - 484
  • [27] Model-based learning and the contribution of the orbitofrontal cortex to the model-free world
    McDannald, Michael A.
    Takahashi, Yuji K.
    Lopatina, Nina
    Pietras, Brad W.
    Jones, Josh L.
    Schoenbaum, Geoffrey
    EUROPEAN JOURNAL OF NEUROSCIENCE, 2012, 35 (07) : 991 - 996
  • [28] Functional Networks Analysis from Multi Neuronal Spike Trains on Prefrontal Cortex of Rat during Working Memory Task and Neuronal Network Simulation
    Qi, Dexuan
    Tian, Xin
    JOURNAL OF COMPUTERS, 2013, 8 (06) : 1377 - 1384
  • [29] Neuronal Ensemble Rate Coding of the Simulated Spike Trains in the Temporal Lobe Cortex via Small-world Network
    Xiao, Zhenguo
    Tian, Xin
    2008 INTERNATIONAL SYMPOSIUM ON INTELLIGENT INFORMATION TECHNOLOGY APPLICATION, VOL III, PROCEEDINGS, 2008, : 727 - 731
  • [30] Scalable and model-free detection of spatial patterns and colocalization
    Liu, Qi
    Hsu, Chih-Yuan
    Shyr, Yu
    GENOME RESEARCH, 2022, 32 (09) : 1736 - 1745