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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

Detailed structure of the relationship between interspike interval (ISI) and spike anticipation. The basic neural network in Figure 1A was used as testbed. For n = 0 it is shown (A) ISI vs. anticipation correlation and (B) the 3D histogram, illustrating the spike distribution over the different regions in (A). Panels (C,D) show the same respective diagrams for n = 3.
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Figure 5: Detailed structure of the relationship between interspike interval (ISI) and spike anticipation. The basic neural network in Figure 1A was used as testbed. For n = 0 it is shown (A) ISI vs. anticipation correlation and (B) the 3D histogram, illustrating the spike distribution over the different regions in (A). Panels (C,D) show the same respective diagrams for n = 3.

Mentions: The Figure 5 shows such correlation for n = 0, i.e., with no intermediary neurons, (upper row) and for n = 3 (lower row), by using different graphical representations. The 2D plot in Figure 5A and the 3D histogram in Figure 5B (showing how spikes are accumulated in each region) reveal that a direct coupling between master and slave neurons provides a similar anticipation for every spikes, regardless of their ISIs. However, when master and slave neurons are coupled through three intermediary neurons a complex relationship appears, correlating different spike anticipations with different ISIs as illustrated in Figures 5C,D. In order to interpret this result we must keep in mind the spiking regime exhibited by the slave neuron (Figure 1B; note that this is almost equal to the master behavior since they are synchronized). This neural activity is organized in bursts, containing spikes whose intra-burst ISIs adapt with time, i.e., in the same burst “fast” (low ISI) and “slow” (higher ISI) spikes coexist. When the basic network contains three intermediary neurons it can be seen that: (1) the lowest spike anticipations ([0.05, 0.18]) correspond to the slowest intra-burst spikes, which signalize the end of the burst, (2) significant higher anticipations appear for faster intra-burst spikes, with a clear difference between the fastest spikes (anticipations in [0.67, 0.75]) and the remaining ones (anticipations in [0.49, 0.57]), and (3) medium anticipations ([0.4, 0.48]) correspond to the inter-burst ISIs (highest ISIs), i.e., to those spikes signalizing the beginning of the burst. In consequence these results indicate that specific parts of the neural code conveying different neural information can be discriminated by using their corresponding spike anticipation, suggesting the potential impact of this phenomenon over neural information processing.


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)

Detailed structure of the relationship between interspike interval (ISI) and spike anticipation. The basic neural network in Figure 1A was used as testbed. For n = 0 it is shown (A) ISI vs. anticipation correlation and (B) the 3D histogram, illustrating the spike distribution over the different regions in (A). Panels (C,D) show the same respective diagrams for n = 3.
© Copyright Policy
Related In: Results  -  Collection

License
Show All Figures
getmorefigures.php?uid=PMC4663270&req=5

Figure 5: Detailed structure of the relationship between interspike interval (ISI) and spike anticipation. The basic neural network in Figure 1A was used as testbed. For n = 0 it is shown (A) ISI vs. anticipation correlation and (B) the 3D histogram, illustrating the spike distribution over the different regions in (A). Panels (C,D) show the same respective diagrams for n = 3.
Mentions: The Figure 5 shows such correlation for n = 0, i.e., with no intermediary neurons, (upper row) and for n = 3 (lower row), by using different graphical representations. The 2D plot in Figure 5A and the 3D histogram in Figure 5B (showing how spikes are accumulated in each region) reveal that a direct coupling between master and slave neurons provides a similar anticipation for every spikes, regardless of their ISIs. However, when master and slave neurons are coupled through three intermediary neurons a complex relationship appears, correlating different spike anticipations with different ISIs as illustrated in Figures 5C,D. In order to interpret this result we must keep in mind the spiking regime exhibited by the slave neuron (Figure 1B; note that this is almost equal to the master behavior since they are synchronized). This neural activity is organized in bursts, containing spikes whose intra-burst ISIs adapt with time, i.e., in the same burst “fast” (low ISI) and “slow” (higher ISI) spikes coexist. When the basic network contains three intermediary neurons it can be seen that: (1) the lowest spike anticipations ([0.05, 0.18]) correspond to the slowest intra-burst spikes, which signalize the end of the burst, (2) significant higher anticipations appear for faster intra-burst spikes, with a clear difference between the fastest spikes (anticipations in [0.67, 0.75]) and the remaining ones (anticipations in [0.49, 0.57]), and (3) medium anticipations ([0.4, 0.48]) correspond to the inter-burst ISIs (highest ISIs), i.e., to those spikes signalizing the beginning of the burst. In consequence these results indicate that specific parts of the neural code conveying different neural information can be discriminated by using their corresponding spike anticipation, suggesting the potential impact of this phenomenon over neural information processing.

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