4.5 Review

The glutamatergic synapse: a complex machinery for information processing

Journal

COGNITIVE NEURODYNAMICS
Volume 15, Issue 5, Pages 757-781

Publisher

SPRINGER
DOI: 10.1007/s11571-021-09679-w

Keywords

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

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The glutamatergic synapse, as the most abundant synaptic type, plays a crucial role in information processing in the brain. Despite the basic simplicity of synaptic transmission, there is a large variation in response to neurotransmitter release, indicating complex control mechanisms. These mechanisms involve the management and coordination of information transfer among neurons, highlighting the intricate and not fully understood functionality of synaptic control.
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.

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