Short-Term Plasticity Optimizes Synaptic Information Transmission

Department of Biomedical Engineering, Center for Investigations of Membrane Excitability Disorders, Washington University School of Medicine, St. Louis, Missouri 63110, USA.
The Journal of Neuroscience : The Official Journal of the Society for Neuroscience (Impact Factor: 6.34). 10/2011; 31(41):14800-9. DOI: 10.1523/JNEUROSCI.3231-11.2011
Source: PubMed


Short-term synaptic plasticity (STP) is widely thought to play an important role in information processing. This major function of STP has recently been challenged, however, by several computational studies indicating that transmission of information by dynamic synapses is broadband, i.e., frequency independent. Here we developed an analytical approach to quantify time- and rate-dependent synaptic information transfer during arbitrary spike trains using a realistic model of synaptic dynamics in excitatory hippocampal synapses. We found that STP indeed increases information transfer in a wide range of input rates, which corresponds well to the naturally occurring spike frequencies at these synapses. This increased information transfer is observed both during Poisson-distributed spike trains with a constant rate and during naturalistic spike trains recorded in hippocampal place cells in exploring rodents. Interestingly, we found that the presence of STP in low release probability excitatory synapses leads to optimization of information transfer specifically for short high-frequency bursts, which are indeed commonly observed in many excitatory hippocampal neurons. In contrast, more reliable high release probability synapses that express dominant short-term depression are predicted to have optimal information transmission for single spikes rather than bursts. This prediction is verified in analyses of experimental recordings from high release probability inhibitory synapses in mouse hippocampal slices and fits well with the observation that inhibitory hippocampal interneurons do not commonly fire spike bursts. We conclude that STP indeed contributes significantly to synaptic information transfer and may serve to maximize information transfer for specific firing patterns of the corresponding neurons.

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Available from: Ziv Rotman, Oct 09, 2015
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    • "Teoria informacji z powodzeniem służy jako obiektywna miara zmian zachowania w reakcji na określone bodźce oraz zmian zachodzących podczas procesu uczenia się. Wiele z tych procesów można wyjaśnić jako dążące do optymalizacji transmisji informacji (Chechik, 2003; Lindner i in., 2009; Rieke i in., 1999; Rotman i in., 2011; Scott i in., 2012). "
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    ABSTRACT: Understanding how nervous cells encode and decode information, process it, and control its transmission, is one of the greatest challenges of the contemporary science. Experiments have shown that information transmitted between neurons is represented by action potentials, i.e electrical impulses in form of short, sharp cell membrane voltage spikes of similar amplitude. For many years, method of coding these signals by neurons is subject of increased effort among researchers around the world. The purpose of research presented here is, first, to develop methods based on information theory and numerical tools, that allow effective determination optimal parameters (including energetic costs) of neuronal information transmission and to examine effects of synergy of cooperating cells in terms of transmission efficiency and reliability. Second, using obtained results and methods, to describe, in both quantitative and qualitative way, simplified brain model, so called brain–like, built of neurons considered earlier. A nonclassical approach to neural networks is taken in the research: non-deterministic cells are considered, based on neuron model proposed by Levy & Baxter (2002). Networks are studied as a communication channels (Shannon, 1948). Therefore, among examined quantities are such as: channel capacity, transmission redundancy, mutual information between input signals (stimuli) and cell response (excitation), and energetic costs of communication. This requires optimal implementation of calculation-expensive entropy estimators. Thus, Strong (1998) estimator is chosen. First, single neurons and feed–forward networks are examined. Optimal information transmission is analyzed in regard to changes of firing rates, synaptic noise and height of activation threshold. Influence of different information source types is also described, as well as impact of amplitude fluctuations. Next, brain–like networks are studied. Information transmission efficiency of excitatory neurons is analyzed as a function of: geometrical size of network (and size-related communication delays), inhibition strength, information source accessibility and additional long–range connections. Conducted computer calculations are accurate and precise. Input sequences used in simulations are at least 106 bits long – as opposed to experimental data, much shorter due to biological restrictions.
    09/2014, Degree: PhD, Supervisor: Janusz Szczepański
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    • "The dynamics of these processes (Table 1) also impacts the variability in postsynaptic conductance, in particular when synaptic transmission is treated as a stochastic event. The variability affects information processing via the signal-to-noise ratio [9-11] and also determines the stability, or robustness, of discrete memory states [12,13]. "
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    ABSTRACT: Bistability within a small neural circuit can arise through an appropriate strength of excitatory recurrent feedback. The stability of a state of neural activity, measured by the mean dwelling time before a noise-induced transition to another state, depends on the neural firing-rate curves, the net strength of excitatory feedback, the statistics of spike times and increases exponentially with the number of equivalent neurons in the circuit. Here we show that such stability is greatly enhanced by synaptic facilitation and reduced by synaptic depression. We take into account the alteration in times of synaptic vesicle release, by calculating distributions of inter-release intervals of a synapse, which differ from the distribution of its incoming inter-spike intervals when the synapse is dynamic. In particular, release intervals produced by a Poisson spike train have a coefficient of variation greater than one when synapses are probabilistic and facilitating, whereas the coefficient of variation is less than one when synapses are depressing. However, in spite of the increased variability in postsynaptic input produced by facilitating synapses, their dominant effect is reduced synaptic efficacy at low input rates compared to high rates, which increases the curvature of neural input-output functions, leading to wider regions of bistability in parameter space and enhanced lifetimes of memory states. Our results are based on analytic methods with approximate formulae and bolstered by simulations of both Poisson processes and of circuits of noisy spiking model neurons.
    Journal of Mathematical Neuroscience 12/2013; 3(1):19. DOI:10.1186/2190-8567-3-19
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    • "These changes are similar to those that we have previously observed after early life generalized seizures induced using flurothyl inhalation and occur without alterations in shorter forms of STP (Hernan et al., 2012). It may seem counterintuitive that increases in STP can be associated with deleterious cognitive outcomes, however it is expected that alterations in STP in either direction would interfere with the induction and maintenance of sustained activity and synaptic filtering properties of the neural network, thereby leading to alterations in information processing in the PFC (Abbott and Regehr, 2004; Deng and Klyachko, 2011; Rotman et al., 2011). Although no direct link between STP and behavior has been made, STP is thought to underlie decision making, attention and temporal encoding in the PFC (Buonomano, 2000; Deco et al., 2010; Deng and Klyachko, 2011). "
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    ABSTRACT: There is a well-described association between childhood epilepsy and pervasive cognitive and behavioral deficits. Often these children have not only ictal EEG events, but also frequent interictal abnormalities. The precise role of these interictal discharges in cognition remains unclear. In order to understand the relationship between frequent epileptiform discharges during neurodevelopment and cognition later in life, we developed a model of frequent focal interictal spikes (IIS). Postnatal day (p) 21 rats received injections of bicuculline methiodine into the prefrontal cortex (PFC). Injections were repeated in order to achieve 5 consecutive days of transient inhibitory/excitatory imbalance resulting in IIS. Short-term plasticity (STP) and behavioral outcomes were studied in adulthood. IIS is associated with a significant increase in STP bilaterally in the PFC. IIS rats did not show working memory deficits, but rather showed marked inattentiveness without significant alterations in motivation, anxiety or hyperactivity. Rats also demonstrated significant deficits in social behavior. We conclude that GABAergic blockade during early-life and resultant focal IIS in the PFC disrupt neural networks and are associated with long-term consequences for behavior at a time when IIS are no longer present, and thus may have important implications for ADHD and autism spectrum disorder associated with childhood epilepsy.
    Neurobiology of Disease 11/2013; 63. DOI:10.1016/j.nbd.2013.11.012 · 5.08 Impact Factor
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