The glutamatergic synapse: a complex machinery for information processing

Abstract

Being the most abundant synaptic type, the glutamatergic synapse is responsible for the larger part of the brain's information processing. Despite the conceptual simplicity of the basic mechanism of synaptic transmission, the glutamatergic synapse shows a large variation in the response to the presynaptic release of the neurotransmitter. This variability is observed not only among different synapses but also in the same single synapse. The synaptic response variability is due to several mechanisms of control of the information transferred among the neurons and suggests that the glutamatergic synapse is not a simple bridge for the transfer of information but plays an important role in its elaboration and management. The control of the synaptic information is operated at pre, post, and extrasynaptic sites in a sort of cooperation between the pre and postsynaptic neurons which also involves the activity of other neurons. The interaction between the different mechanisms of control is extremely complicated and its complete functionality is far from being fully understood. The present review, although not exhaustively, is intended to outline the most important of these mechanisms and their complexity, the understanding of which will be among the most intriguing challenges of future neuroscience.

Keywords: AMPA; Brain information processing; EPSC; EPSP; Glutamatergic synapse; LTD; LTP; NMDA; Synaptic information processing; Synaptic modeling; Synaptic transmission; dendritic integration; dendritic spines.

Fig. 1

Examples of simulated EPSPs and EPSCs

Fig. 2

Schema of a typical Glu Synapse. The red pathway shows the information flow

Fig. 3

Simplified schematic representation of the SNARE complex configuration and vesicle docking

Fig. 4

Simulated AMPA-EPSC (black line) and NMDA-EPSC (red line)

Fig. 5

Simplified electrical circuit of the spine and its connection to the dendrite. $V_{\mathit{PSD}}$ is the difference of potential at the level of the PSD, $V_d$ is the difference of potential at the level of the dendrite. $R_{\mathit{PSD}}$ is the input resistance at the PSD, $R_d$ is the dendrite resistance and $R_l$ is the longitudinal resistance of the intracellular liquid into the dendrite. $R_n$ is the neck resistance and $C_m$ the membrane capacitance

Fig. 6

Variability of the EPSP depending on the parameters of Eq. (10). Panel A: ${\tau }_1$ and ${\tau }_2$ are kept constant while k is varied. Panel B: k and ${\tau }_2$ are kept constant and ${\tau }_1$ is varied. Panel C: k and ${\tau }_1$ are kept constant and ${\tau }_2$ is varied

Fig. 7

Left panel: Results of a single run simulation of an EPSP occurring after 600ms while a pool of 160 excitatory and 40 inhibitory synapses fires in neighbor dendrites with respectively a mean excitatory frequency of 5 Hz (black line) and 6 Hz red line and an inhibitory firing frequency of 3 Hz. The right panel is the same as the left panel but averaged over 1000 runs