Bursts as a unit of neural information: Making unreliable synapses reliable

被引:1077
|
作者
Lisman, JE
机构
[1] Volen Center for Complex Systems, Biology Dept., Brandeis University, Waltham
关键词
D O I
10.1016/S0166-2236(96)10070-9
中图分类号
Q189 [神经科学];
学科分类号
071006 ;
摘要
Several lines of evidence indicate that brief (<25 ms) bursts of high-frequency firing have special importance in brain function. Recent work shows that many central synapses ave surprisingly unreliable at signaling the arrival of single presynaptic action potentials to the postsynaptic neuron. However, bursts are reliably signaled because transmitter release is facilitated. Thus, these synapses can be viewed as filters that transmit bursts, but filter out single spikes. Bursts appear to have a special role in synaptic plasticity and information processing. In the hippocampus, a single burst can produce long-term synaptic modifications. In brain structures whose computational role is known, action potentials that arrive in bursts provide more-precise information than action potentials that arrive singly. These results, and the requirement for multiple inputs to fire a cell suggest that the best stimulus for exciting a cell (that is, a neural code) is coincident bursts.
引用
收藏
页码:38 / 43
页数:6
相关论文
共 50 条
  • [31] Dynamical Synapses Enhance Neural Information Processing: Gracefulness, Accuracy, and Mobility
    Fung, C. C. Alan
    Wong, K. Y. Michael
    Wang, He
    Wu, Si
    NEURAL COMPUTATION, 2012, 24 (05) : 1147 - 1185
  • [32] Why Empathy Is Not a Reliable Source of Information in Moral Decision Making
    Decety, Jean
    CURRENT DIRECTIONS IN PSYCHOLOGICAL SCIENCE, 2021, 30 (05) : 425 - 430
  • [33] THERE IS MUCH INFORMATION IN NEURAL NETWORK UNIT ACTIVATIONS
    RAGER, JE
    BEHAVIORAL AND BRAIN SCIENCES, 1992, 15 (04) : 792 - 792
  • [34] A spiking recurrent neural network with phase change memory synapses for decision making
    Pedretti, G.
    Milo, V
    Hashemkhani, S.
    Mannocci, P.
    Melnic, O.
    Chicca, E.
    Ielmini, D.
    2020 IEEE INTERNATIONAL SYMPOSIUM ON CIRCUITS AND SYSTEMS (ISCAS), 2020,
  • [35] Reliable computing with unreliable components: Using separable environments to stabilize long-term information storage
    Nugent, M. A.
    Porter, R.
    Kenyon, G. T.
    PHYSICA D-NONLINEAR PHENOMENA, 2008, 237 (09) : 1196 - 1206
  • [36] Super-steep synapses based on positive feedback devices for reliable binary neural networks
    Kwon, Dongseok
    Kim, Hyeongsu
    Lee, Kyu-Ho
    Hwang, Joon
    Shin, Wonjun
    Bae, Jong-Ho
    Woo, Sung Yun
    Lee, Jong-Ho
    APPLIED PHYSICS LETTERS, 2023, 122 (10)
  • [37] "Reliable organisms from unreliable components " revisited: the linear drift, linear infinitesimal variance model of decision making
    Smith, Philip L.
    PSYCHONOMIC BULLETIN & REVIEW, 2023, 30 (04) : 1323 - 1359
  • [38] “Reliable organisms from unreliable components” revisited: the linear drift, linear infinitesimal variance model of decision making
    Philip L. Smith
    Psychonomic Bulletin & Review, 2023, 30 : 1323 - 1359
  • [39] Information transmission by stochastic synapses with short-term depression: neural coding and optimization
    de la Rocha, J
    Nevado, A
    Parga, N
    NEUROCOMPUTING, 2002, 44 : 85 - 90
  • [40] Making use of population information in evolutionary artificial neural networks
    Yao, X
    Liu, Y
    IEEE TRANSACTIONS ON SYSTEMS MAN AND CYBERNETICS PART B-CYBERNETICS, 1998, 28 (03): : 417 - 425