A computational model elucidating mechanisms and variability in theta burst stimulation responses.
Computational modeling
Long-term depression (LTD)
Long-term potentiation (LTP)
TBS variability of responses
Theta burst stimulation (TBS)
Transcranial magnetic stimulation (TMS)
Journal
Journal of computational neuroscience
ISSN: 1573-6873
Titre abrégé: J Comput Neurosci
Pays: United States
ID NLM: 9439510
Informations de publication
Date de publication:
09 Aug 2024
09 Aug 2024
Historique:
received:
07
08
2023
accepted:
17
07
2024
revised:
22
04
2024
medline:
9
8
2024
pubmed:
9
8
2024
entrez:
9
8
2024
Statut:
aheadofprint
Résumé
Theta burst stimulation (TBS) is a form of repetitive transcranial magnetic stimulation (rTMS) with unknown underlying mechanisms and highly variable responses across subjects. To investigate these issues, we developed a simple computational model. Our model consisted of two neurons linked by an excitatory synapse that incorporates two mechanisms: short-term plasticity (STP) and spike-timing-dependent plasticity (STDP). We applied a variable-amplitude current through I-clamp with a TBS time pattern to the pre- and post-synaptic neurons, simulating synaptic plasticity. We analyzed the results and provided an explanation for the effects of TBS, as well as the variability of responses to it. Our findings suggest that the interplay of STP and STDP mechanisms determines the direction of plasticity, which selectively affects synapses in extended neurons and underlies functional effects. Our model describes how the timing, number, and intensity of pulses delivered to neurons during rTMS contribute to induced plasticity. This not only successfully explains the different effects of intermittent TBS (iTBS) and continuous TBS (cTBS), but also predicts the results of other protocols such as 10 Hz rTMS. We propose that the variability in responses to TBS can be attributed to the variable span of neuronal thresholds across individuals and sessions. Our model suggests a biologically plausible mechanism for the diverse responses to TBS protocols and aligns with experimental data on iTBS and cTBS outcomes. This model could potentially aid in improving TBS and rTMS protocols and customizing treatments for patients, brain areas, and brain disorders.
Identifiants
pubmed: 39120822
doi: 10.1007/s10827-024-00875-1
pii: 10.1007/s10827-024-00875-1
doi:
Types de publication
Journal Article
Langues
eng
Sous-ensembles de citation
IM
Informations de copyright
© 2024. The Author(s), under exclusive licence to Springer Science+Business Media, LLC, part of Springer Nature.
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