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Transcranial magnetic stimulation, synaptic plasticity and network oscillations
Transcranial magnetic stimulation (TMS) has quickly progressed from a technical curiosity to a bona-fide tool for neurological research. The impetus has been due to the promising results obtained when using TMS to uncover neural processes in normal human subjects, as well as in the treatment of intr...
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Published in: | Journal of neuroengineering and rehabilitation 2009-03, Vol.6 (1), p.7-7, Article 7 |
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description | Transcranial magnetic stimulation (TMS) has quickly progressed from a technical curiosity to a bona-fide tool for neurological research. The impetus has been due to the promising results obtained when using TMS to uncover neural processes in normal human subjects, as well as in the treatment of intractable neurological conditions, such as stroke, chronic depression and epilepsy. The basic principle of TMS is that most neuronal axons that fall within the volume of magnetic stimulation become electrically excited, trigger action potentials and release neurotransmitter into the postsynaptic neurons. What happens afterwards remains elusive, especially in the case of repeated stimulation. Here we discuss the likelihood that certain TMS protocols produce long-term changes in cortical synapses akin to long-term potentiation and long-term depression of synaptic transmission. Beyond the synaptic effects, TMS might have consequences on other neuronal processes, such as genetic and protein regulation, and circuit-level patterns, such as network oscillations. Furthermore, TMS might have non-neuronal effects, such as changes in blood flow, which are still poorly understood. |
doi_str_mv | 10.1186/1743-0003-6-7 |
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subjects | Brain - physiology Humans Magnetic brain stimulation Neural Inhibition - physiology Neural transmission Neuronal Plasticity - physiology Neuroplasticity Review Synapses - physiology Synaptic Transmission - physiology Transcranial Magnetic Stimulation |
title | Transcranial magnetic stimulation, synaptic plasticity and network oscillations |
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