Boris Barbour

Prolonged presence of glutamate during excitatory synaptic transmission to cerebellar Purkinje cells

In the molecular layer of the cerebellar cortex, Purkinje cells and interneurons receive a common excitatory input from parallel fibers. The AMPA/kainate receptor-mediated parallel fiber excitatory postsynaptic current (EPSC) recorded in Purkinje cells decays much more slowly than that recorded in interneurons. We show that this slowness of decay does not result from dendritic filtering and that it is unlikely to reflect the deactivation kinetics of the postsynaptic receptors. Agents blocking glutamate uptake prolong the EPSC in Purkinje cells. We conclude that the slow EPSC decay results from the continued presence of transmitter glutamate. This may be due to retarded transmitter diffusion around spines or to cross-talk between neighboring active synapses.

Functional antigen-independent synapses formed between T cells and dendritic cells

Immunological synapse formation is usually assumed to require antigen recognition by T cell receptors. However, the immunological synapse formed at the interface between naïve T cells and dendritic cells (DCs) has never been described. We show here that in the absence of antigen, and even of major histocompatibility complex molecules, T cell–DC synapses are formed and lead to several T cell responses: a local increase in tyrosine phosphorylation, small Ca2+ responses, weak proliferation and long-term survival. These responses are triggered more readily in CD4+ T cells than in CD8+ T cells, which express a specific isoform of the repulsive molecule CD43. These phenomena may play a major role in the maintenance of the naïve T cell pool in vivo.

Properties of unitary granule cell-->Purkinje cell synapses in adult rat cerebellar slices.

The cerebellar cortex contains huge numbers of synapses between granule cells and Purkinje cells. These synapses are thought to be a major storage site for information required to execute coordinated movements. To obtain a quantitative description of this connection, we recorded unitary synaptic responses between granule cell and Purkinje cell pairs in adult rat cerebellar slices. Our results are consistent with parallel fiber→Purkinje cell synapses having high release probabilities and modest paired pulse facilitation. However, a wide range of response amplitudes was observed. Indeed, we detected many fewer parallel fiber connections (7% of the granule cells that were screened) than expected (54%), leading us to suggest that up to 85% of parallel fiber→Purkinje cell synapses do not generate detectable electrical responses. We also investigated the possible role of granule cell ascending axons by recording granule cells near the Purkinje cell. A high proportion (up to 50%) of local granule cells generated detectable synaptic responses. However, most of these connections were indistinguishable from parallel fiber connections, suggesting that powerful ascending axon connections are rare. The existence of many very weak synapses would provide a mechanism for Purkinje cells to extract information selectively from the mass provided by parallel fibers.

Synaptic currents evoked in purkinje cells by stimulating individual granule cells

Each cerebellar Purkinje cell receives input from about 160,000 glutamatergic granule cells. In anatomically intact preparations this input has hitherto been studied only as a compound synaptic potential or current. Presented here are simultaneous recordings in cerebellar slices of synaptically connected granule cell-Purkinje cell pairs. The mean amplitude of the excitatory synaptic currents evoked by stimulation of individual granule cells ranged from 2 to 60 pA, whereas the great majority of the spontaneous glutamatergic currents in Purkinje cells in the presence of tetrodotoxin were < 40 pA. In several cases, stimulation of a single granule cell evoked a disynaptic inhibitory current. It is estimated that on the order of 50 simultaneously active granule cells are sufficient to excite a Purkinje cell.

Optimal Information Storage and the Distribution of Synaptic Weights: Perceptron versus Purkinje Cell

It is widely believed that synaptic modifications underlie learning and memory. However, few studies have examined what can be deduced about the learning process from the distribution of synaptic weights. We analyze the perceptron, a prototypical feedforward neural network, and obtain the optimal synaptic weight distribution for a perceptron with excitatory synapses. It contains more than 50% silent synapses, and this fraction increases with storage reliability: silent synapses are therefore a necessary byproduct of optimizing learning and reliability. Exploiting the classical analogy between the perceptron and the cerebellar Purkinje cell, we fitted the optimal weight distribution to that measured for granule cell-Purkinje cell synapses. The two distributions agreed well, suggesting that the Purkinje cell can learn up to 5 kilobytes of information, in the form of 40,000 input-output associations.

Currents evoked in Bergmann glial cells by parallel fibre stimulation in rat cerebellar slices

1 Whole‐cell recordings were obtained from Bergmann glial cells in rat cerebellar slices. 2 The cells had low input resistances (70 ± 38 mV; n= 13) and a mean resting potential of −82 ± 6 mV (n= 12) with a potassium‐based internal solution. Electrical and dye coupling between Bergmann glia were confirmed. 3 Stimulation of parallel fibres induced a complex, mostly inward current which could be decomposed pharmacologically. 4 The ionotropic glutamate receptor antagonist, 6‐cyano‐7‐nitroqumoxalme‐2,3‐dione (CNQX; 10 μM), but not DL‐2‐amino‐5‐phosphonopentanoic acid (DL‐APV; 100μM) consistently blocked an early inward current component that may reflect synaptic activation of AMPA/kainate receptors in Bergmann glia. 5 Addition of cadmium ions (100 μM) to inhibit transmitter release blocked most of the CNQX‐APV‐insensitive current. This component probably reflects electrogenic uptake of the synaptically released glutamate. 6 Tetrodotoxin (TTX; 1 μM) blocked the remaining inward current: a slow component, possibly produced by the potassium ion efflux during action potential propagation in parallel fibres. An initial triphasic component of the response was also TTX sensitive and reflected passage of the parallel fibre action potential volley. 7 The putative glutamate uptake current was further characterized; it was blocked by the competitive uptake blockers D‐aspartate (0.5 mM) and L‐trans‐pyrrolidine‐2,4‐dicarboxylic acid (PDC; 0.5 mM), and by replacement of sodium with lithium. Monitoring the triphasic TTX‐sensitive component showed that this inhibition did not result from changes of action potential excitation and propagation. 8 Intracellular nitrate ions increased the putative uptake current, consistent with the effect of this anion on glutamate transporters. 9 The putative uptake current was reduced by depolarization, consistent with the voltage dependence of glutamate uptake. 10 It is concluded that a large fraction of the current induced by parallel fibre stimulation reflects the uptake of synaptically released glutamate. The uptake current activated rapidly, with a 20–80% rise time of 2.3 ± 0.7 ms (n= 10), and decayed with a principal time constant of 25 ± 6 ms (n= 10).

Multiple climbing fibers signal to molecular layer interneurons exclusively via glutamate spillover

Spillover of glutamate under physiological conditions has only been established as an adjunct to conventional synaptic transmission. Here we describe a pure spillover connection between the climbing fiber and molecular layer interneurons in the rat cerebellar cortex. We show that, instead of acting via conventional synapses, multiple climbing fibers activate AMPA- and NMDA-type glutamate receptors on interneurons exclusively via spillover. Spillover from the climbing fiber represents a form of glutamatergic volume transmission that could be triggered in a regionalized manner by experimentally observed synchronous climbing fiber activity. Climbing fibers are known to direct parallel fiber synaptic plasticity in interneurons, so one function of this spillover is likely to involve controlling synaptic plasticity.

High-Frequency Organization and Synchrony of Activity in the Purkinje Cell Layer of the Cerebellum

The cerebellum controls complex, coordinated, and rapid movements, a function requiring precise timing abilities. However, the network mechanisms that underlie the temporal organization of activity in the cerebellum are largely unexplored, because in vivo recordings have usually targeted single units. Here, we use tetrode and multisite recordings to demonstrate that Purkinje cell activity is synchronized by a high-frequency (approximately 200 Hz) population oscillation. We combine pharmacological experiments and modeling to show how the recurrent inhibitory connections between Purkinje cells are sufficient to generate these oscillations. A key feature of these oscillations is a fixed population frequency that is independent of the firing rates of the individual cells. Convergence in the deep cerebellar nuclei of Purkinje cell activity, synchronized by these oscillations, likely organizes temporally the cerebellar output.

What can we learn from synaptic weight distributions

Much research effort into synaptic plasticity has been motivated by the idea that modifications of synaptic weights (or strengths or efficacies) underlie learning and memory. Here, we examine the possibility of exploiting the statistics of experimentally measured synaptic weights to deduce information about the learning process. Analysing distributions of synaptic weights requires a theoretical framework to interpret the experimental measurements, but the results can be unexpectedly powerful, yielding strong constraints on possible learning theories as well as information that is difficult to obtain by other means, such as the information storage capacity of a cell. We review the available experimental and theoretical techniques as well as important open issues.

Event-driven simulation scheme for spiking neural networks using lookup tables to characterize neuronal dynamics

Nearly all neuronal information processing and interneuronal communication in the brain involves action potentials, or spikes, which drive the short-term synaptic dynamics of neurons, but also their long-term dynamics, via synaptic plasticity. In many brain structures, action potential activity is considered to be sparse. This sparseness of activity has been exploited to reduce the computational cost of large-scale network simulations, through the development of event-driven simulation schemes. However, existing event-driven simulations schemes use extremely simplified neuronal models. Here, we implement and evaluate critically an event-driven algorithm (ED-LUT) that uses precalculated look-up tables to characterize synaptic and neuronal dynamics. This approach enables the use of more complex (and realistic) neuronal models or data in representing the neurons, while retaining the advantage of high-speed simulation. We demonstrate the methods application for neurons containing exponential synaptic conductances, thereby implementing shunting inhibition, a phenomenon that is critical to cellular computation. We also introduce an improved two-stage event-queue algorithm, which allows the simulations to scale efficiently to highly connected networks with arbitrary propagation delays. Finally, the scheme readily accommodates implementation of synaptic plasticity mechanisms that depend on spike timing, enabling future simulations to explore issues of long-term learning and adaptation in large-scale networks.