Role of spike-frequency adaptation in shaping neuronal response to dynamic stimuli

被引:0
|
作者
Simon Peter Peron
Fabrizio Gabbiani
机构
[1] Baylor College of Medicine,Department of Neuroscience
[2] Rice University,Department of Computational and Applied Mathematics
来源
Biological Cybernetics | 2009年 / 100卷
关键词
Spike-frequency adaptation; Single neuron computation; LGMD; DCMD; Insect vision; Collision avoidance;
D O I
暂无
中图分类号
学科分类号
摘要
Spike-frequency adaptation is the reduction of a neuron’s firing rate to a stimulus of constant intensity. In the locust, the Lobula Giant Movement Detector (LGMD) is a visual interneuron that exhibits rapid adaptation to both current injection and visual stimuli. Here, a reduced compartmental model of the LGMD is employed to explore adaptation’s role in selectivity for stimuli whose intensity changes with time. We show that supralinearly increasing current injection stimuli are best at driving a high spike count in the response, while linearly increasing current injection stimuli (i.e., ramps) are best at attaining large firing rate changes in an adapting neuron. This result is extended with in vivo experiments showing that the LGMD’s response to translating stimuli having a supralinear velocity profile is larger than the response to constant or linearly increasing velocity translation. Furthermore, we show that the LGMD’s preference for approaching versus receding stimuli can partly be accounted for by adaptation. Finally, we show that the LGMD’s adaptation mechanism appears well tuned to minimize sensitivity for the level of basal input.
引用
收藏
页码:505 / 520
页数:15
相关论文
共 50 条
  • [21] Spike-frequency adaptation and intrinsic properties of an identified, looming-sensitive neuron
    Gabbiani, Fabrizio
    Krapp, Holger G.
    JOURNAL OF NEUROPHYSIOLOGY, 2006, 96 (06) : 2951 - 2962
  • [22] Spike-frequency adaptation of a generalized leaky integrate-and-fire model neuron
    Liu, YH
    Wang, XJ
    JOURNAL OF COMPUTATIONAL NEUROSCIENCE, 2001, 10 (01) : 25 - 45
  • [23] Input-driven components of spike-frequency adaptation can be unmasked in vivo
    Gollisch, T
    Herz, AVM
    JOURNAL OF NEUROSCIENCE, 2004, 24 (34): : 7435 - 7444
  • [24] Bio-inspired computing: A deep learning algorithm with the spike-frequency adaptation
    Wang, Jixuan
    Deng, Bin
    Gao, Tianshi
    Wang, Jiang
    Yi, Guosheng
    2022 IEEE INTERNATIONAL INSTRUMENTATION AND MEASUREMENT TECHNOLOGY CONFERENCE (I2MTC 2022), 2022,
  • [25] Spike-frequency adaptation separates transient communication signals from background oscillations
    Benda, J
    Longtin, A
    Maler, L
    JOURNAL OF NEUROSCIENCE, 2005, 25 (09): : 2312 - 2321
  • [26] Spike-frequency adaptation in neocortical pyramidal neurons under simulated in vivo conditions
    Fuhrmann, G
    Tsodyks, M
    Markram, H
    NEUROSCIENCE LETTERS, 1998, : S12 - S12
  • [27] Spike-frequency adapting neural ensembles: Beyond mean adaptation and renewal theories
    Muller, Eilif
    Buesing, Lars
    Schemmel, Johannes
    Meier, Karlheinz
    NEURAL COMPUTATION, 2007, 19 (11) : 2958 - 3010
  • [28] Spike-Frequency Adaptation of a Generalized Leaky Integrate-and-Fire Model Neuron
    Ying-Hui Liu
    Xiao-Jing Wang
    Journal of Computational Neuroscience, 2001, 10 : 25 - 45
  • [29] Contribution of persistent sodium currents to spike-frequency adaptation in rat hypoglossal motoneurons
    Zeng, JS
    Powers, RK
    Newkirk, G
    Yonkers, M
    Binder, MD
    JOURNAL OF NEUROPHYSIOLOGY, 2005, 93 (02) : 1035 - 1041
  • [30] Is the purpose of reverse spike-frequency adaptation to enhance correlations? Focus on "A model of reverse spike frequency adaptation and repetitive firing of subthalamic nucleus neurons"
    Destexhe, A
    JOURNAL OF NEUROPHYSIOLOGY, 2004, 91 (05) : 1943 - 1944