Are you sure you want to leave this community? Leaving the community will revoke any permissions you have been granted in this community.
Repetitive transcranial magnetic stimulation (rTMS) is used as a research tool and clinical treatment for the non-clinical and clinical populations, to modulate brain plasticity. In the case of neurologic and psychiatric disease, there is significant evidence to suggest that rTMS plays an important role in the functional recovery after neurological dysfunction. However, the causal role for rTMS in the recovery of nervous dysfunction remains unclear. The purpose of the present study is to detect the regulation of rTMS on the excitatory neuronal transmission and specify the mode of action of rTMS on the neural plasticity using Drosophila whole brain. Therefore, we identified the effects of rTMS on the neural plasticity of central neural system (CNS) by detecting the electrophysiology properties of projection neurons (PNs) from adult Drosophila brain after rTMS. Using patch clamp recordings, we recorded the mini excitatory postsynaptic current (mEPSC) of PNs after rTMS at varying frequencies (1 Hz and 100 Hz) and intensities (1%, 10%, 50%, and 100%). Then, the chronic electrophysiology recordings, including mEPSC, spontaneous action potential (sAP), and calcium channel currents from PNs after rTMS at low frequency (1 Hz), with low intensity (1%) were detected and the properties of the recordings were analyzed. Finally, the frequency and decay time of mEPSC, the resting potential and frequency of sAP, and the current density and rise time of calcium channel currents were significantly changed by rTMS. Our work reveals that rTMS can be used as a tool to regulate the presynaptic function of neural circuit, by modulating the calcium channel in a frequency-, intensity- and time-dependent manner.
Pubmed ID: 31540425
Publication data is provided by the National Library of Medicine ® and PubMed ®. Data is retrieved from PubMed ® on a weekly schedule. For terms and conditions see the National Library of Medicine Terms and Conditions.
Software package used for interactive, or batched, statistical analysis in social science, health sciences and marketing. Software platform offers advanced statistical analysis, a library of machine-learning algorithms, text analysis, open-source extensibility, integration with big data and deployment into applications.Versions that were produced by SPSS Inc. before the IBM acquisition (Versions 18 and earlier) would be given origin or publisher of SPSS Inc. in Chicago.
View all literature mentionsNEURON is a simulation environment for modeling individual neurons and networks of neurons. It provides tools for conveniently building, managing, and using models in a way that is numerically sound and computationally efficient. It is particularly well-suited to problems that are closely linked to experimental data, especially those that involve cells with complex anatomical and biophysical properties. NEURON has benefited from judicious revision and selective enhancement, guided by feedback from the growing number of neuroscientists who have used it to incorporate empirically-based modeling into their research strategies. NEURON's computational engine employs special algorithms that achieve high efficiency by exploiting the structure of the equations that describe neuronal properties. It has functions that are tailored for conveniently controlling simulations, and presenting the results of real neurophysiological problems graphically in ways that are quickly and intuitively grasped. Instead of forcing users to reformulate their conceptual models to fit the requirements of a general purpose simulator, NEURON is designed to let them deal directly with familiar neuroscience concepts. Consequently, users can think in terms of the biophysical properties of membrane and cytoplasm, the branched architecture of neurons, and the effects of synaptic communication between cells. * helps users focus on important biological issues rather than purely computational concerns * has a convenient user interface * has a user-extendable library of biophysical mechanisms * has many enhancements for efficient network modeling * offers customizable initialization and simulation flow control * is widely used in neuroscience research by experimentalists and theoreticians * is well-documented and actively supported * is free, open source, and runs on (almost) everything
View all literature mentionsDrosophila melanogaster with name Canton-S from BDSC.
View all literature mentions