Relationship between the mechanisms of gamma rhythm generation and the magnitude of the macroscopic phase response function in a population of excitatory and inhibitory modified quadratic integrate-and-fire neurons

被引:13
作者
Akao, Akihiko [1 ]
Ogawa, Yutaro [2 ]
Jimbo, Yasuhiko [1 ]
Ermentrout, G. Bard [3 ]
Kotani, Kiyoshi [4 ]
机构
[1] Univ Tokyo, Grad Sch Engn, Bunkyo Ku, 7-3-1 Hongo, Tokyo 1130033, Japan
[2] Univ Tokyo, Res Ctr Adv Sci & Technol, Meguro Ku, 4-6-1 Komaba, Tokyo 1538904, Japan
[3] Univ Pittsburgh, Dept Math, Pittsburgh, PA 15260 USA
[4] JST, PRESTO, 4-1-8 Honcho, Kawaguchi, Saitama 3320012, Japan
基金
美国国家科学基金会;
关键词
FAST NETWORK OSCILLATIONS; HIPPOCAMPUS IN-VITRO; INTERNEURON NETWORKS; COUPLED OSCILLATORS; SYNAPSES; DYNAMICS; SYNCHRONIZATION; FREQUENCY; CURRENTS; MODEL;
D O I
10.1103/PhysRevE.97.012209
中图分类号
O35 [流体力学]; O53 [等离子体物理学];
学科分类号
070204 ; 080103 ; 080704 ;
摘要
Gamma oscillations are thought to play an important role in brain function. Interneuron gamma (ING) and pyramidal interneuron gamma (PING) mechanisms have been proposed as generation mechanisms for these oscillations. However, the relation between the generationmechanisms and the dynamical properties of the gamma oscillation are still unclear. Among the dynamical properties of the gamma oscillation, the phase response function (PRF) is important because it encodes the response of the oscillation to inputs. Recently, the PRF for an inhibitory population of modified theta neurons that generate an ING rhythm was computed by the adjoint method applied to the associated Fokker-Planck equation (FPE) for the model. The modified theta model incorporates conductancebased synapses as well as the voltage and current dynamics. Here, we extended this previous work by creating an excitatory-inhibitory (E-I) network using the modified theta model and described the population dynamics with the corresponding FPE. We conducted a bifurcation analysis of the FPE to find parameter regions which generate gamma oscillations. In order to label the oscillatory parameter regions by their generation mechanisms, we defined ING-and PING-type gamma oscillation in a mathematically plausible way based on the driver of the inhibitory population. We labeled the oscillatory parameter regions by these generation mechanisms and derived PRFs via the adjoint method on the FPE in order to investigate the differences in the responses of each type of oscillation to inputs. PRFs for PING and ING mechanisms are derived and compared. We found the amplitude of the PRF for the excitatory population is larger in the PING case than in the ING case. Finally, the E-I population of the modified theta neuron enabled us to analyze the PRFs of PING-type gamma oscillation and the entrainment ability of E and I populations. We found a parameter region in which PRFs of E and I are both purely positive in the case of PING oscillations. The different entrainment abilities of E and I stimulation as governed by the respective PRFs was compared to direct simulations of finite populations of model neurons. We find that it is easier to entrain the gamma rhythm by stimulating the inhibitory population than by stimulating the excitatory population as has been found experimentally.
引用
收藏
页数:11
相关论文
共 38 条
  • [1] Oscillatory dynamics in the hippocampus support dentate gyrus-CA3 coupling
    Akam, Thomas
    Oren, Iris
    Mantoan, Laura
    Ferenczi, Emily
    Kullmann, Dimitri M.
    [J]. NATURE NEUROSCIENCE, 2012, 15 (05) : 763 - 768
  • [2] [Anonymous], 2002, SPIKING NEURON MODEL
  • [3] Rapid signaling at inhibitory synapses in a dentate gyrus interneuron network
    Bartos, M
    Vida, I
    Frotscher, M
    Geiger, JRP
    Jonas, P
    [J]. JOURNAL OF NEUROSCIENCE, 2001, 21 (08) : 2687 - 2698
  • [4] Synaptic mechanisms of synchronized gamma oscillations in inhibitory interneuron networks
    Bartos, Marlene
    Vida, Imre
    Jonas, Peter
    [J]. NATURE REVIEWS NEUROSCIENCE, 2007, 8 (01) : 45 - 56
  • [5] Gamma oscillations and stimulus selection
    Boergers, Christoph
    Kopell, Nancy J.
    [J]. NEURAL COMPUTATION, 2008, 20 (02) : 383 - 414
  • [6] Minimal Size of Cell Assemblies Coordinated by Gamma Oscillations
    Boergers, Christoph
    Franzesi, Giovanni Talei
    LeBeau, Fiona E. N.
    Boyden, Edward S.
    Kopell, Nancy J.
    [J]. PLOS COMPUTATIONAL BIOLOGY, 2012, 8 (02)
  • [7] Synchronization in networks of excitatory and inhibitory neurons with sparse, random connectivity
    Börgers, C
    Kopell, N
    [J]. NEURAL COMPUTATION, 2003, 15 (03) : 509 - 538
  • [8] On the phase reduction and response dynamics of neural oscillator populations
    Brown, E
    Moehlis, J
    Holmes, P
    [J]. NEURAL COMPUTATION, 2004, 16 (04) : 673 - 715
  • [9] What determines the frequency of fast network oscillations with irregular neural discharges? I. Synaptic dynamics and excitation-inhibition balance
    Brunel, N
    Wang, XJ
    [J]. JOURNAL OF NEUROPHYSIOLOGY, 2003, 90 (01) : 415 - 430
  • [10] Mechanisms of Gamma Oscillations
    Buzsaki, Gyoergy
    Wang, Xiao-Jing
    [J]. ANNUAL REVIEW OF NEUROSCIENCE, VOL 35, 2012, 35 : 203 - 225