Gap junctions promote synchronous activities in a network of inhibitory interneurons

Garbo, Angelo Di; Panarese, Alessandro; Chillemi, Santi

doi:10.1016/j.biosystems.2004.09.004

Cited by 17 publications

(15 citation statements)

References 25 publications

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“…In the FS cell model, the dependence of phase locking on intrinsic frequency is qualitatively the same as that seen in integrate-and-fire models (Chow and Kopell, 2000;Lewis, 2003;Lewis and Rinzel, 2003;Pfeuty et al, 2003) and in other conductance-based models (Nomura et al, 2003;Pfeuty et al, 2003;Di Garbo et al, 2005).…”

Section: Experimentally Determined Prcs Predict Only Synchronous Actisupporting

confidence: 59%

“…Recent theoretical work has suggested that the ability of electrical coupling to synchronize the activity of cells depends on a number of factors, including coupling strength and firing frequency (Chow and Kopell, 2000;Lewis and Rinzel, 2003;Nomura et al, 2003;Pfeuty et al, 2003;Di Garbo et al, 2005;Bem et al, 2005;Saraga et al, 2006). This theoretical work predicts that, under most conditions, electrical synapses promote synchronous activity, but they can also support antiphase activity between coupled neurons.…”

Section: Introductionmentioning

confidence: 99%

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Synchronization of Electrically Coupled Pairs of Inhibitory Interneurons in Neocortex

Mancilla¹,

Lewis²,

Pinto³

et al. 2007

J. Neurosci.

198

163

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We performed a systematic analysis of phase locking in pairs of electrically coupled neocortical fast-spiking (FS) and low-thresholdspiking (LTS) interneurons and in a conductance-based model of a pair of FS cells. Phase-response curves (PRCs) were obtained for real interneurons and the model cells. We used PRCs and the theory of weakly coupled oscillators to make predictions about phase-locking characteristics of cell pairs. Phase locking and the robustness of phase-locked states to differences in intrinsic frequencies of cells were directly examined by driving interneuron pairs through a wide range of firing frequencies.Calculations using PRCs accurately predicted that electrical coupling robustly synchronized the firing of interneurons over all frequencies studied (FS, ϳ25-80 Hz; LTS, ϳ10 -30 Hz). The synchronizing ability of electrical coupling and the robustness of the phaselocked states were directly dependent on the strength of coupling but not on firing frequency. The FS cell model also predicted the existence of stable antiphase firing at frequencies below ϳ30 Hz, but no evidence for stable antiphase firing was found using the experimentally determined PRCs or in direct measures of phase locking in pairs of interneurons. Despite significant differences in biophysical properties of FS and LTS cells, their phase-locking behavior was remarkably similar. The wide spikes and shallow action potential afterhyperpolarizations of interneurons, compared with the model, prohibited antiphase behavior. Electrical coupling between cortical interneurons of the same type maintained robust synchronous firing of cell pairs for up to ϳ10% heterogeneity in their intrinsic frequencies.

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Section: Experimentally Determined Prcs Predict Only Synchronous Actisupporting

confidence: 59%

Section: Introductionmentioning

confidence: 99%

Synchronization of Electrically Coupled Pairs of Inhibitory Interneurons in Neocortex

Mancilla¹,

Lewis²,

Pinto³

et al. 2007

J. Neurosci.

198

163

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“…In addition, magnetoencephalography (MEG), a functional neuroimaging technique, is used for mapping brain activity. The signals measured in EEG and MEG can be decomposed into distinct frequency bands such as 1-3 Hz (delta), 4-7 Hz (theta), [8][9][10][11][12][13][14][15] Hz (alpha), 16-31 Hz (beta), and 32-70 Hz (gamma). There is a correlation between these rhythms and behaviors [3].…”

Section: Introductionmentioning

confidence: 99%

“…Modeling the dynamic behavior of a network has attracted much attention in recent years [4][5][6][7][8][9][10][11][12][13][14][15][16][17][18][19][20][21][22]. Gibson et al [6] showed by paired-cell recordings that while the same type of inhibitory neurons were strongly interconnected by electrical synapses, electrical synapses between different inhibitory cell types were rare.…”

Section: Introductionmentioning

confidence: 99%

“…In the literature, there are some works that used both synapses for synchronization behavior of neurons with different scale neuron models. In these works, the dynamics of FS interneurons were described either by the Wang-Buzsaki model [12] or by conductance-based model [2], and some other works used Hodgkin-Huxley type models [11,15]. To the best of my knowledge, the modeling capabilities of the Izhikevich model in terms of synchronization have not been investigated.…”

Section: Introductionmentioning

confidence: 99%

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Modeling of time delay-induced multiple synchronization behavior of interneuronal networks with the Izhikevich neuron model

Cakir¹

2017

Turk J Elec Eng & Comp Sci

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Abstract:The synchronization behavior of the networks of fast-spiking interneurons is investigated by using one of the phenomenological neural network models, the Izhikevich model. Since electrical and chemical synapses exist within the same networks of inhibitory cells, delayed inhibitory and fast electrical synapses are coupled in the simulations. The effects of hybrid synapses in promoting synchronous activity in neural networks are investigated with short and long time delays. The distinct frequency bands observed in electroencephalography and magnetoencephalography signals are determined using the raster plots of neural networks. For quantitative comparison of activities in networks, the degree of synchrony in the network is calculated. The influences of several network parameters such as inhibitory synaptic strength, electrical synaptic strength, synaptic time constant, and time delay on the network activity are investigated.It is observed that the coupling of electrical and chemical synapses promotes multiple synchronous behaviors in the network. Another important finding is that even though the synchronization measure is highly dependent on inhibitory synaptic strengths at low electrical synaptic strength and synaptic time constant, not much dependence on inhibitory synaptic strengths is observed at high electrical synaptic strength.

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Gap-Junctions Promote Synchrony in a Network of Inhibitory Interneurons in the Presence of Heterogeneities and Noise

Chillemi

Panarese

Barbi

et al. 2005

Lecture Notes in Computer Science

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Gap junctions promote synchronous activities in a network of inhibitory interneurons

Cited by 17 publications

References 25 publications

Synchronization of Electrically Coupled Pairs of Inhibitory Interneurons in Neocortex

Synchronization of Electrically Coupled Pairs of Inhibitory Interneurons in Neocortex

Modeling of time delay-induced multiple synchronization behavior of interneuronal networks with the Izhikevich neuron model

Gap-Junctions Promote Synchrony in a Network of Inhibitory Interneurons in the Presence of Heterogeneities and Noise

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