About this Research Topic
Any brain activity depends on the interaction of thousands of neurons, each of which depending on the interaction of thousands of synapses. While neurons are the building blocks of the brain, their interactions occur by means of synaptic transmission, thus making synapses the main loci of information transfer, and leading to the emergence of neuronal code.
Any project aimed at understanding nervous system function or information processing in the brain strongly benefits from realistic models of synaptic activity. Such a modeling task proves challenging for many reasons. First, synaptic responses display a wide range of variability. Indeed, even a single synapse can generate a large amount of variability in its responses depending on many pre- and postsynaptic factors, the source of which is, in many cases, of stochastic nature. Second, synaptic responses also display a wide range of responses that differ with activity and time. Finally, experimental research on this topic, although able to furnish provide a large amount of information, remains limited for physical reasons. So far, the best way to approach the problem is a good combination of experimental research accompanied by and set side by side with theoretical and/or computational modeling of synaptic activity.
This Research Topic is intended to bring together foundational work aimed at shedding much-needed light on the details underlying synaptic mechanisms and resulting functions through experimental and computational approaches. Its scope aims to showcase recent developments and ideas in the study of synaptic dynamics, and the interplay between structure and the dynamical processes that take place in both healthy and pathological brains. This Research Topic includes, but is not limited to, studies of presynaptic mechanisms (e.g. modulation of release process), neuron-glia interactions, receptors and channels characterization, metabotropic receptor activation, intracellular molecular pathways, plasticity-related changes and energy-dependent processes. The research presented may range from the molecular level (e.g. work on a specific receptor type), up to single neuron/cell integration in the spatial scale, while dynamics studied may span from microseconds (diffusion processes) to minutes in the temporal scale.
Any project aimed at understanding nervous system function or information processing in the brain strongly benefits from realistic models of synaptic activity. Such a modeling task proves challenging for many reasons. First, synaptic responses display a wide range of variability. Indeed, even a single synapse can generate a large amount of variability in its responses depending on many pre- and postsynaptic factors, the source of which is, in many cases, of stochastic nature. Second, synaptic responses also display a wide range of responses that differ with activity and time. Finally, experimental research on this topic, although able to furnish provide a large amount of information, remains limited for physical reasons. So far, the best way to approach the problem is a good combination of experimental research accompanied by and set side by side with theoretical and/or computational modeling of synaptic activity.
This Research Topic is intended to bring together foundational work aimed at shedding much-needed light on the details underlying synaptic mechanisms and resulting functions through experimental and computational approaches. Its scope aims to showcase recent developments and ideas in the study of synaptic dynamics, and the interplay between structure and the dynamical processes that take place in both healthy and pathological brains. This Research Topic includes, but is not limited to, studies of presynaptic mechanisms (e.g. modulation of release process), neuron-glia interactions, receptors and channels characterization, metabotropic receptor activation, intracellular molecular pathways, plasticity-related changes and energy-dependent processes. The research presented may range from the molecular level (e.g. work on a specific receptor type), up to single neuron/cell integration in the spatial scale, while dynamics studied may span from microseconds (diffusion processes) to minutes in the temporal scale.
Keywords: Excitatory Synapse, Inhibitory Synapses, Synaptic Modeling, Synaptic Integration, Brain Information Processing
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