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Effects of Spike Anticipation on the Spiking Dynamics of Neural Networks.

de Santos-Sierra D, Sanchez-Jimenez A, Garcia-Vellisca MA, Navas A, Villacorta-Atienza JA - Front Comput Neurosci (2015)

Bottom Line: We show that the introduction of intermediary neurons in the network enhances spike anticipation and analyse how these variations in spike anticipation can significantly change the firing regime of the neural network according to its functional and structural properties.In addition we show that the interspike interval (ISI), one of the main features of the neural response associated with the information coding, can be closely related to spike anticipation by each spike, and how synaptic plasticity can be modulated through that relationship.This study has been performed through numerical simulation of a coupled system of Hindmarsh-Rose neurons.

View Article: PubMed Central - PubMed

Affiliation: Group of Biometrics, Biosignals and Security, Research Centre for Smart Buildings and Energy Efficiency (CeDInt), Technical University of Madrid Madrid, Spain ; Laboratory of Computational System Biology, Center for Biomedical Technology, Technical University of Madrid Madrid, Spain.

ABSTRACT
Synchronization is one of the central phenomena involved in information processing in living systems. It is known that the nervous system requires the coordinated activity of both local and distant neural populations. Such an interplay allows to merge different information modalities in a whole processing supporting high-level mental skills as understanding, memory, abstraction, etc. Though, the biological processes underlying synchronization in the brain are not fully understood there have been reported a variety of mechanisms supporting different types of synchronization both at theoretical and experimental level. One of the more intriguing of these phenomena is the anticipating synchronization, which has been recently reported in a pair of unidirectionally coupled artificial neurons under simple conditions (Pyragiene and Pyragas, 2013), where the slave neuron is able to anticipate in time the behavior of the master one. In this paper, we explore the effect of spike anticipation over the information processing performed by a neural network at functional and structural level. We show that the introduction of intermediary neurons in the network enhances spike anticipation and analyse how these variations in spike anticipation can significantly change the firing regime of the neural network according to its functional and structural properties. In addition we show that the interspike interval (ISI), one of the main features of the neural response associated with the information coding, can be closely related to spike anticipation by each spike, and how synaptic plasticity can be modulated through that relationship. This study has been performed through numerical simulation of a coupled system of Hindmarsh-Rose neurons.

No MeSH data available.


Related in: MedlinePlus

Fast spiking in slow burst induced by spike anticipation. (A) Neuron X activity. (B) Corresponding ISI histogram. Parameters: n = 3, J0X = 3.25, CX = 1, kMX = 0.6 and kSX = −0.3.
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Figure 4: Fast spiking in slow burst induced by spike anticipation. (A) Neuron X activity. (B) Corresponding ISI histogram. Parameters: n = 3, J0X = 3.25, CX = 1, kMX = 0.6 and kSX = −0.3.

Mentions: A different functional regime for the neuron X appears with three intermediary neurons and by changing the functional parameters properly to elicit a qualitatively different behavior, as illustrated in Figure 4. Such behavior is characterized by slow bursts of fast spikes with decreasing amplitudes, resembling real neural activity observed experimentally in different contexts (Weyand et al., 2001; Viemari et al., 2013).


Effects of Spike Anticipation on the Spiking Dynamics of Neural Networks.

de Santos-Sierra D, Sanchez-Jimenez A, Garcia-Vellisca MA, Navas A, Villacorta-Atienza JA - Front Comput Neurosci (2015)

Fast spiking in slow burst induced by spike anticipation. (A) Neuron X activity. (B) Corresponding ISI histogram. Parameters: n = 3, J0X = 3.25, CX = 1, kMX = 0.6 and kSX = −0.3.
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Related In: Results  -  Collection

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getmorefigures.php?uid=PMC4663270&req=5

Figure 4: Fast spiking in slow burst induced by spike anticipation. (A) Neuron X activity. (B) Corresponding ISI histogram. Parameters: n = 3, J0X = 3.25, CX = 1, kMX = 0.6 and kSX = −0.3.
Mentions: A different functional regime for the neuron X appears with three intermediary neurons and by changing the functional parameters properly to elicit a qualitatively different behavior, as illustrated in Figure 4. Such behavior is characterized by slow bursts of fast spikes with decreasing amplitudes, resembling real neural activity observed experimentally in different contexts (Weyand et al., 2001; Viemari et al., 2013).

Bottom Line: We show that the introduction of intermediary neurons in the network enhances spike anticipation and analyse how these variations in spike anticipation can significantly change the firing regime of the neural network according to its functional and structural properties.In addition we show that the interspike interval (ISI), one of the main features of the neural response associated with the information coding, can be closely related to spike anticipation by each spike, and how synaptic plasticity can be modulated through that relationship.This study has been performed through numerical simulation of a coupled system of Hindmarsh-Rose neurons.

View Article: PubMed Central - PubMed

Affiliation: Group of Biometrics, Biosignals and Security, Research Centre for Smart Buildings and Energy Efficiency (CeDInt), Technical University of Madrid Madrid, Spain ; Laboratory of Computational System Biology, Center for Biomedical Technology, Technical University of Madrid Madrid, Spain.

ABSTRACT
Synchronization is one of the central phenomena involved in information processing in living systems. It is known that the nervous system requires the coordinated activity of both local and distant neural populations. Such an interplay allows to merge different information modalities in a whole processing supporting high-level mental skills as understanding, memory, abstraction, etc. Though, the biological processes underlying synchronization in the brain are not fully understood there have been reported a variety of mechanisms supporting different types of synchronization both at theoretical and experimental level. One of the more intriguing of these phenomena is the anticipating synchronization, which has been recently reported in a pair of unidirectionally coupled artificial neurons under simple conditions (Pyragiene and Pyragas, 2013), where the slave neuron is able to anticipate in time the behavior of the master one. In this paper, we explore the effect of spike anticipation over the information processing performed by a neural network at functional and structural level. We show that the introduction of intermediary neurons in the network enhances spike anticipation and analyse how these variations in spike anticipation can significantly change the firing regime of the neural network according to its functional and structural properties. In addition we show that the interspike interval (ISI), one of the main features of the neural response associated with the information coding, can be closely related to spike anticipation by each spike, and how synaptic plasticity can be modulated through that relationship. This study has been performed through numerical simulation of a coupled system of Hindmarsh-Rose neurons.

No MeSH data available.


Related in: MedlinePlus