Abstract
A great number of biological experiments show that gamma oscillation occurs in many brain areas after the presentation of stimulus. The neural systems in these brain areas are highly heterogeneous. Specifically, the neurons and synapses in these neural systems are diversified; the external inputs and parameters of these neurons and synapses are heterogeneous. How the gamma oscillation generated in such highly heterogeneous networks remains a challenging problem. Aiming at this problem, a highly heterogeneous complex network model that takes account of many aspects of real neural circuits was constructed. The network model consists of excitatory neurons and fast spiking interneurons, has three types of synapses (GABAA, AMPA, and NMDA), and has highly heterogeneous external drive currents. We found a new regime for robust gamma oscillation, i.e. the oscillation in inhibitory neurons is rather accurate but the oscillation in excitatory neurons is weak, in such highly heterogeneous neural networks. We also found that the mechanism of the oscillation is a mixture of interneuron gamma (ING) and pyramidal-interneuron gamma (PING). We explained the mixture ING and PING mechanism in a consistent-way by a compound post-synaptic current, which has a slowly rising-excitatory stage and a sharp decreasing-inhibitory stage.
This is a preview of subscription content, log in via an institution to check access.
Similar content being viewed by others
References
Ahmed OJ, Mehta MR (2012) Running speed alters the frequency of hippocampal gamma oscillations. J Neurosci 32(21):7373–7383
BÄorgers C, Kopell N (2003) Synchronization in networks of excitatory and inhibitory neurons with sparse, random connectivity. Neural Comput 15:509–538
Bartos M, Vida I, Jonas P (2007) Synaptic mechanisms of synchronized gamma oscillations in inhibitory interneuron networks. Nat Rev Neurosci 8:45–56
Bathellier B, Carleton A, Gerstner W (2008) Gamma oscillations in a nonlinear regime: a minimal model approach using heterogeneous integrate-and-fire networks. Neural Comput 20:2973–3002
Bosman CA, Schoffelen JM, Brunet N et al (2012) Attentional stimulus selection through selective synchronization between monkey visual areas. Neuron 75(5):875–888
Brunel N, Hakim V (1999) Fast global oscillations in networks of integrate-and-fire neurons with low firing rates. Neural Comput 11:1621–1671
Brunel N, Wang XJ (2003) What determines the frequency of fast network oscillations with irregular neural discharges? I. Synaptic dynamics and excitation-inhibition balance. J Neurophysiol 90:415–430
Buzsaki G, Wang XJ et al (2012) Mechanisms of gamma oscillations. Annu Rev Neurosci 35:203–225
Dayan P, Abbott LF (2001) Theoretical neuroscience: computational and mathematical modeling of neural systems. MIT Press, Cambridge, MA
Du Y, Wang RB, Han F et al (2012) Firing pattern and synchronization property analysis in a network model of the olfactory bulb. Cogn Neurodyn 6(2):203–209
Engelhard B, Ozeri N, Israel Z et al (2013) Inducing gamma oscillations and precise spike synchrony by operant conditioning via brain-machine interface. Neuron 77(2):361–375
Hadjipapas A, Adjamian P, Swettenham JB et al (2007) Stimuli of varying spatial scale induce gamma activity with distinct temporal characteristics in human visual cortex. Neuroimage 35(2):518–530
Hájos N, Paulsen O (2009) Network mechanisms of gamma oscillations in the CA3 region of the hippocampus. Neural Networks 22:1113–1119
Herrmann CS, Mecklinger A (2000) Magnetoencephalographic responses to illusory figures: early evoked gamma is affected by processing of stimulus features. Int J Psychophysiol 38(3):265–281
Jeong HY, Gutkin B (2007) Synchrony of neuronal oscillations controlled by GABAergic reversal potentials. Neural Comput 19:706–729
Laczo B, Antal A, Niebergall R et al (2012) Transcranial alternating stimulation in a high gamma frequency range applied over V1 improves contrast perception but does not modulate spatial attention. Brain Stimul 5(4):484–491
Lapray D, Bergeler J, Luhmann HJ (2009) Stimulus-induced gamma activity in the electrocorticogram of freely moving rats: the neuronal signature of novelty detection. Behav Brain Res 199(2):350–354
Li XM, Morita K, Robinson HPC et al (2011) Impact of gamma-oscillatory inhibition on the signal transmission of a cortical pyramidal neuron. Cogn Neurodyn 5(3):241–251
Muthukumaraswamy SD, Singh KD (2013) Visual gamma oscillations: the effects of stimulus type, visual field coverage and stimulus motion on MEG and EEG recordings. NeuroImage 69:223–230
Neymotin SA, Lee H, Park E et al (2011) Emergence of physiological oscillation frequencies in a computer model of neocortex. Front Comput Neurosci 19:1–17 Article 19
Nikolic D, Fries P, Singer W (2013) Gamma oscillations: precise temporal coordination without a metronome. Trends cogn Sci 17(2):54–55
Perry G, Hamandi K, Brindley LM et al (2013) The properties of induced gamma oscillations in human visual cortex show individual variability in their dependence on stimulus size. NeuroImage 68:83–92
Rojas-Libano D, Kay LM (2008) Olfactory system gamma oscillations: the physiological dissection of a cognitive neural system. Cogn Neurodyn 2(3):179–194
Schadow J, Lenz D, Thaerig S et al (2007a) Stimulus intensity affects early sensory processing: visual contrast modulates evoked gamma-band activity in human EEG. Int J Psychophysiol 66(1):28–36
Schadow J, Lenz D, Thaerig S et al (2007b) Stimulus intensity affects early sensory processing: sound intensity modulates auditory evoked gamma-band activity in human EEG. Int J Psychophysiol 65(2):152–161
Schwarzkopf DS, Robertson DJ, Song C et al (2012) The frequency of visually induced gamma-band oscillations depends on the size of early human visual cortex. J Neurosci 32(4):1507–1512
Tiesinga P, Sejnowski TJ (2009) Cortical enlightenment: are attentional gamma oscillations driven by ING or PING? Neuron 63:727–732
Vida I, Bartos M, Jonas P (2006) Shunting inhibition improves robustness of gamma oscillations in hippocampal interneuron networks by homogenizing firing rates. Neuron 49:107–117
Wang XJ (2010) Neurophysiological and computational principles of cortical rhythms in cognition. Physiol Rev 90:1195–1268
Wang XJ, Buzsáki G (1996) Gamma oscillation by synaptic inhibition in a hippocampal interneuronal network model. J Neurosci 16(20):6402–6413
Wang Z, Wong WK (2013) Key role of voltage-dependent properties of synaptic currents in robust network synchronization. Neural Networks 43:55–62
Wang Z, Fan H, Aihara K (2011) Three synaptic components contributing to robust network synchronization. Phys Rev E 83:051905
Womelsdorf T, Fries P, Mitra PP, Desimone R (2006) Gamma-band synchronization in visual cortex predicts speed of change detection. Nature 439:733–736
Acknowledgments
This research is supported by the NSF of China (Grants No. 70971021, No. 71371046, No. 61075105, and No. 11102038) and Shanghai Education Development Foundation Chenguang Project (No. 10CG33).
Author information
Authors and Affiliations
Corresponding author
Rights and permissions
About this article
Cite this article
Wang, Z., Fan, H. & Han, F. A new regime for highly robust gamma oscillation with co-exist of accurate and weak synchronization in excitatory–inhibitory networks. Cogn Neurodyn 8, 335–344 (2014). https://doi.org/10.1007/s11571-014-9290-4
Received:
Revised:
Accepted:
Published:
Issue Date:
DOI: https://doi.org/10.1007/s11571-014-9290-4