Natural Firing Patterns Imply Low Sensitivity of Synaptic Plasticity to Spike Timing Compared with Firing Rate

Graupner, Michael; Wallisch, Pascal; Ostojic, Srdjan

doi:10.1523/jneurosci.0104-16.2016

Cited by 51 publications

(110 citation statements)

References 58 publications

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“…This prediction that irregular IPIs strengthen tLTP when the spike timing is constant confirms the result obtained independently and with different mathematical models (see Fig. 3 in [13]). When…”

Section: Discussionsupporting

confidence: 87%

“…Regular stimulation paradigms produce patterns of activity that are likely to differ from the variability expected in in vivo-like firing. A recent theoretical study has started to explore more naturalistic stimulations [13]. However, whether STDP emergence and maintenance is robust against biological variability remains to be investigated.…”

Section: Introductionmentioning

confidence: 99%

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Robustness of STDP to spike timing jitter

Cui

Prokin

Mendes

et al. 2018

Preprint

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In Hebbian plasticity, neural circuits adjust their synaptic weights depending on patterned firing of action potential on either side of the synapse. Spike-timing-dependent plasticity (STDP) is an experimental implementation of Hebb's postulate that relies on the precise order and the millisecond timing of the paired activities in pre-and postsynaptic neurons. In recent years, STDP has attracted considerable attention in computational and experimental neurosciences. However, canonical STDP is assessed with deterministic (constant) spike timings and time intervals between successive pairings, thus exhibiting a regularity that strongly differs from the biological variability. Hence, the emergence of STDP from noisy neural activity patterns as expected in in vivo-like firing remains unresolved. Here, we used noisy STDP stimulations where the spike timing and/or the interval between successive pairings were jittered. We explored with a combination of experimental neurophysiology and mathematical modeling, the impact of jittering on three distinct forms of STDP at corticostriatal synapses: NMDAR-mediated tLTP, endocannabinoid-mediated tLTD and endocannabinoid-mediated tLTP. As the main result, we found a differential sensitivity to jittered spike timing: NMDAR-tLTP was highly fragile whereas endocannabinoid-plasticity (tLTD and tLTP) appeared more resistant. Moreover, when the frequency or the number of pairings was increased, NMDAR-tLTP became more robust and could be expressed despite strong jittering of the spike timing. Taken together, our results identify endocannabinoidmediated plasticity as a robust form of STDP while the sensitivity to jitter of NMDAR-tLTP varies with activity frequency. This provides new insights into the mechanisms at play during the different phases of learning and memory and the emergence of Hebbian plasticity in in vivo-like firing.

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Section: Discussionsupporting

confidence: 87%

Section: Introductionmentioning

confidence: 99%

Robustness of STDP to spike timing jitter

Cui

Prokin

Mendes

et al. 2018

Preprint

View full text Add to dashboard Cite

show abstract

“…[66]), and to relate them to the detailed map formation models discussed earlier [67 • ]. Moreover, it would be interesting to examine the emergence of functional organization under realistic developmental patterns of activity, which as discussed earlier are sluggish and might utilize different plasticity rules than those that rely on precise spike timing [68].…”

Section: The Emergence Of Systems-level Organizationmentioning

confidence: 99%

Understanding neural circuit development through theory and models

Richter

Gjorgjieva

2017

Preprint

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How are neural circuits organized and tuned to achieve stable function and produce robust behavior? The organization process begins early in development and involves a diversity of mechanisms unique to this period. We summarize recent progress in theoretical neuroscience that has substantially contributed to our understanding of development at the single neuron, synaptic and network level. We go beyond classical models of topographic map formation, and focus on the generation of complex spatiotemporal activity patterns, their role in refinements of particular circuit features, and the emergence of functional computations. Aided by the development of novel quantitative methods for data analysis, theoretical and computational models have enabled us to test the adequacy of specific assumptions, explain experimental data and propose testable hypotheses. With the accumulation of larger data sets, theory and models will likely play an even more important role in understanding the development of neural circuits.

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“…Our results clearly do not depend on the actual spike timing since our model neurons generate spikes as Poisson processes; rather, all lasting changes in the connectivity are due to time-varying modulations of the firing rates. In fact, recent work with a spiking neuron model suggests that such modulations in the firing rate, as opposed to exact spike timing, are sufficient to explain the effect of plasticity from STDP and more realistic calcium-based plasticity rules in general (Graupner et al 2016). In any case the contribution of pairwise spike correlations to the evolution of the recurrent connectivity can be formally taken into account in Eq.4, i.e.…”

Section: Robustness To Changes In the Plasticity Model And To The Prementioning

confidence: 99%

Theta-modulation drives the emergence of network-wide connectivity patterns underlying replay in a model of hippocampal place cells

Theodoni

Rovira

et al. 2017

Preprint

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SummaryPlace cells of the rodent hippocampus fire action potentials when the animal traverses a particular spatial location in a given environment. Therefore, for any given trajectory one will observe a repeatable sequence of place cell activations as the animal explores. Interestingly, when the animal is quiescent or sleeping, one can observe similar sequences of activation, although at a highly compressed rate, known as "replays". It is hypothesized that this replay underlies the process of memory consolidation whereby memories are "transferred" from hippocampus to cortex. However, it remains unclear how the memory of a particular environment is actually encoded in the place cell activity and what the mechanism for replay is. Here we study how plasticity during spatial exploration shapes the patterns of synaptic connectivity in model networks of place cells.Specifically, we show how plasticity leads to the formation of attracting manifolds: patterns of activity which represent the spatial environment learned. These states become spontaneously active when the animal is quiescent, reproducing the phenomenology of replays. Interestingly, the attractors are formed most rapidly when place cell activity is modulated by an ongoing oscillation.The optimal oscillation frequency can be calculated analytically, is directly related to the plasticity rule, and for experimentally determined values of the plasticity window in rodent slices gives values in the theta range. A major prediction of these model is that the pairwise correlation of place cells which encode for neighboring locations should increase during initial exploration, leading up to the . CC-BY 4.0 International license not peer-reviewed) is the author/funder. It is made available under a The copyright holder for this preprint (which was . http://dx.doi.org/10.1101/118489 doi: bioRxiv preprint first posted online Mar. 20, 2017; critical transition. We find such an increase in a population of simultaneously recorded CA1 pyramidal cells from a rat exploring a novel track. Furthermore, in a rat in which hippocampal theta is reduced through inactivition of the medial septum we find no such increase. This is consistent with the model, which predicts orders of magnitude lower learning rates when theta is absent.

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Natural Firing Patterns Imply Low Sensitivity of Synaptic Plasticity to Spike Timing Compared with Firing Rate

Cited by 51 publications

References 58 publications

Robustness of STDP to spike timing jitter

Robustness of STDP to spike timing jitter

Understanding neural circuit development through theory and models

Theta-modulation drives the emergence of network-wide connectivity patterns underlying replay in a model of hippocampal place cells

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