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Self-Organized Near-Zero-Lag Synchronization Induced by Spike-Timing Dependent Plasticity in Cortical Populations.

Matias FS, Carelli PV, Mirasso CR, Copelli M - PLoS ONE (2015)

Bottom Line: We show that STDP can promote auto-organized zero-lag synchronization in unidirectionally coupled neuronal populations.We also find synchronization regimes with negative phase difference (AS) that are stable against plasticity.Finally, we show that the interplay between negative phase difference and STDP provides limited synaptic weight distribution without the need of imposing artificial boundaries.

View Article: PubMed Central - PubMed

Affiliation: Instituto de Física, Universidade Federal de Alagoas, Maceió AL 57072-970, Brazil.

ABSTRACT
Several cognitive tasks related to learning and memory exhibit synchronization of macroscopic cortical areas together with synaptic plasticity at neuronal level. Therefore, there is a growing effort among computational neuroscientists to understand the underlying mechanisms relating synchrony and plasticity in the brain. Here we numerically study the interplay between spike-timing dependent plasticity (STDP) and anticipated synchronization (AS). AS emerges when a dominant flux of information from one area to another is accompanied by a negative time lag (or phase). This means that the receiver region pulses before the sender does. In this paper we study the interplay between different synchronization regimes and STDP at the level of three-neuron microcircuits as well as cortical populations. We show that STDP can promote auto-organized zero-lag synchronization in unidirectionally coupled neuronal populations. We also find synchronization regimes with negative phase difference (AS) that are stable against plasticity. Finally, we show that the interplay between negative phase difference and STDP provides limited synaptic weight distribution without the need of imposing artificial boundaries.

No MeSH data available.


Robustness of synchronization regimes against model parameters.(a) Effect of external noise with and without plasticity: time delay normalized to the period of the Master population τ/T versus the Poisson rate R of the external noise. The inhibitory conductances in the Slave-Interneuron population is gIS = 5 nS and A+ = 0.5. (b) Time delay τ versus the parameter of the STDP rule A+ (see Eq 11) for gIS = 4 nS. A smooth transition from AS to DS can be observed.
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pone.0140504.g005: Robustness of synchronization regimes against model parameters.(a) Effect of external noise with and without plasticity: time delay normalized to the period of the Master population τ/T versus the Poisson rate R of the external noise. The inhibitory conductances in the Slave-Interneuron population is gIS = 5 nS and A+ = 0.5. (b) Time delay τ versus the parameter of the STDP rule A+ (see Eq 11) for gIS = 4 nS. A smooth transition from AS to DS can be observed.

Mentions: Despite the time decay of the chemical synapses, the neuronal variability and the external noise, the network exhibits τ ≈ 0 synchronized solution for a large set of parameters. For large enough Poisson rate (R > 3500 Hz in our simulations, see Methods) the STDP rule brings the system closer to zero-lag synchronization (see Fig 5(a)). Although the conductance value of each individual synapse gMS can change in time, the near-zero-lag regime is stable. In fact, in the near-zero-lag regime, the standard deviation of τ (≈ 1.5 ms, see Fig 4(a)–(c)) is much smaller than the mean period of each population (≈ 130 ms, see Fig 2(b) and 2(c)). Altogether, these results reveal a new mechanism which may contribute to the large-scale synchronization phenomena in the brain.


Self-Organized Near-Zero-Lag Synchronization Induced by Spike-Timing Dependent Plasticity in Cortical Populations.

Matias FS, Carelli PV, Mirasso CR, Copelli M - PLoS ONE (2015)

Robustness of synchronization regimes against model parameters.(a) Effect of external noise with and without plasticity: time delay normalized to the period of the Master population τ/T versus the Poisson rate R of the external noise. The inhibitory conductances in the Slave-Interneuron population is gIS = 5 nS and A+ = 0.5. (b) Time delay τ versus the parameter of the STDP rule A+ (see Eq 11) for gIS = 4 nS. A smooth transition from AS to DS can be observed.
© Copyright Policy
Related In: Results  -  Collection

License
Show All Figures
getmorefigures.php?uid=PMC4608682&req=5

pone.0140504.g005: Robustness of synchronization regimes against model parameters.(a) Effect of external noise with and without plasticity: time delay normalized to the period of the Master population τ/T versus the Poisson rate R of the external noise. The inhibitory conductances in the Slave-Interneuron population is gIS = 5 nS and A+ = 0.5. (b) Time delay τ versus the parameter of the STDP rule A+ (see Eq 11) for gIS = 4 nS. A smooth transition from AS to DS can be observed.
Mentions: Despite the time decay of the chemical synapses, the neuronal variability and the external noise, the network exhibits τ ≈ 0 synchronized solution for a large set of parameters. For large enough Poisson rate (R > 3500 Hz in our simulations, see Methods) the STDP rule brings the system closer to zero-lag synchronization (see Fig 5(a)). Although the conductance value of each individual synapse gMS can change in time, the near-zero-lag regime is stable. In fact, in the near-zero-lag regime, the standard deviation of τ (≈ 1.5 ms, see Fig 4(a)–(c)) is much smaller than the mean period of each population (≈ 130 ms, see Fig 2(b) and 2(c)). Altogether, these results reveal a new mechanism which may contribute to the large-scale synchronization phenomena in the brain.

Bottom Line: We show that STDP can promote auto-organized zero-lag synchronization in unidirectionally coupled neuronal populations.We also find synchronization regimes with negative phase difference (AS) that are stable against plasticity.Finally, we show that the interplay between negative phase difference and STDP provides limited synaptic weight distribution without the need of imposing artificial boundaries.

View Article: PubMed Central - PubMed

Affiliation: Instituto de Física, Universidade Federal de Alagoas, Maceió AL 57072-970, Brazil.

ABSTRACT
Several cognitive tasks related to learning and memory exhibit synchronization of macroscopic cortical areas together with synaptic plasticity at neuronal level. Therefore, there is a growing effort among computational neuroscientists to understand the underlying mechanisms relating synchrony and plasticity in the brain. Here we numerically study the interplay between spike-timing dependent plasticity (STDP) and anticipated synchronization (AS). AS emerges when a dominant flux of information from one area to another is accompanied by a negative time lag (or phase). This means that the receiver region pulses before the sender does. In this paper we study the interplay between different synchronization regimes and STDP at the level of three-neuron microcircuits as well as cortical populations. We show that STDP can promote auto-organized zero-lag synchronization in unidirectionally coupled neuronal populations. We also find synchronization regimes with negative phase difference (AS) that are stable against plasticity. Finally, we show that the interplay between negative phase difference and STDP provides limited synaptic weight distribution without the need of imposing artificial boundaries.

No MeSH data available.