Spike-timing-dependent plasticity in the human dorso-lateral prefrontal cortex

被引:61
|
作者
Casula, Elias Paolo [1 ]
Pellicciari, Maria Concetta [1 ]
Picazio, Silvia [1 ]
Caltagirone, Carlo [1 ,2 ]
Koch, Giacomo [1 ,3 ]
机构
[1] Santa Lucia Fdn IRCCS, Dept Behav & Clin Neurol, Non Invas Brain Stimulat Unit, I-00179 Rome, Italy
[2] Tor Vergata Univ, Dept Syst Med, I-00133 Rome, Italy
[3] Tor Vergata Policlin, Stroke Unit, I-00133 Rome, Italy
关键词
DLPFC; EEG; Plasticity; STDP; TMS; TRANSCRANIAL MAGNETIC STIMULATION; PAIRED ASSOCIATIVE STIMULATION; HUMAN MOTOR CORTEX; IN-VIVO; SYNAPTIC PLASTICITY; CORTICAL REACTIVITY; NEURONAL-ACTIVITY; WORKING-MEMORY; TMS-EEG; INHIBITION;
D O I
10.1016/j.neuroimage.2016.08.060
中图分类号
Q189 [神经科学];
学科分类号
071006 ;
摘要
Changes in the synaptic strength of neural connections are induced by repeated coupling of activity of interconnected neurons with precise timing, a phenomenon known as spike-timing-dependent plasticity (STOP). It is debated if this mechanism exists in large-scale cortical networks in humans. We combined transcranial magnetic stimulation (TMS) with concurrent electroencephalography (EEG) to directly investigate the effects of two paired associative stimulation (PAS) protocols (fronto-parietal and parietofrontal) of pre and post-synaptic inputs within the human fronto-parietal network. We found evidence that the dorsolateral prefrontal cortex (DLPFC) has the potential to form robust STOP. Long-term potentiation/depression of TMS-evoked cortical activity is prompted after that DLPFC stimulation is followed/preceded by posterior parietal stimulation. Such bidirectional changes are paralleled by sustained increase/decrease of high-frequency oscillatory activity, likely reflecting STDP responsivity. The current findings could be important to drive plasticity of damaged cortical circuits in patients with cognitive or psychiatric disorders. (C) 2016 Elsevier Inc. All rights reserved.
引用
收藏
页码:204 / 213
页数:10
相关论文
共 50 条
  • [21] Memory-Efficient Synaptic Connectivity for Spike-Timing-Dependent Plasticity
    Pedroni, Bruno U.
    Joshi, Siddharth
    Deissl, Stephen R.
    Sheik, Sadique
    Detorakis, Georgios
    Paul, Somnath
    Augustine, Charles
    Neftci, Emre O.
    Cauwenberghs, Gert
    FRONTIERS IN NEUROSCIENCE, 2019, 13
  • [22] A Computational Model of Working Memory Based on Spike-Timing-Dependent Plasticity
    Huang, Qiu-Sheng
    Wei, Hui
    FRONTIERS IN COMPUTATIONAL NEUROSCIENCE, 2021, 15
  • [23] Frequency Selectivity Emerging from Spike-Timing-Dependent Plasticity
    Gilson, Matthieu
    Buerck, Moritz
    Burkitt, Anthony N.
    van Hemmen, J. Leo
    NEURAL COMPUTATION, 2012, 24 (09) : 2251 - 2279
  • [24] Supervised Learning with Complex Spikes and Spike-Timing-Dependent Plasticity
    Houghton, Conor
    PLOS ONE, 2014, 9 (06):
  • [25] Equation-free analysis of spike-timing-dependent plasticity
    Laing, Carlo R.
    Kevrekidis, Ioannis G.
    BIOLOGICAL CYBERNETICS, 2015, 109 (06) : 701 - 714
  • [26] Spike-timing-dependent plasticity in small-world networks
    Kube, Karsten
    Herzog, Andreas
    Michaelis, Bernd
    de Lima, Ana D.
    Voigt, Thomas
    NEUROCOMPUTING, 2008, 71 (7-9) : 1694 - 1704
  • [27] Learning Probabilistic Inference through Spike-Timing-Dependent Plasticity
    Pecevski, Dejan
    Maass, Wolfgang
    ENEURO, 2016, 3 (02) : 8616 - 8620
  • [28] Spike-timing-dependent synaptic plasticity: from single spikes to spike trains
    Panchev, C
    Wermter, S
    NEUROCOMPUTING, 2004, 58 : 365 - 371
  • [29] Spike-timing-dependent plasticity: common themes and divergent vistas
    Adam Kepecs
    Mark C.W. van Rossum
    Sen Song
    Jesper Tegner
    Biological Cybernetics, 2002, 87 : 446 - 458
  • [30] Conditional modulation of spike-timing-dependent plasticity for olfactory learning
    Cassenaer, Stijn
    Laurent, Gilles
    NATURE, 2012, 482 (7383) : 47 - U62