Neuromodulation effect of temporal interference stimulation based on network computational model
Deep brain stimulation (DBS) has long been the conventional method for targeting deep brain structures, but noninvasive alternatives like transcranial Temporal Interference Stimulation (tTIS) are gaining traction. Research has shown that alternating current influences brain oscillations through neur...
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Frontiers Media S.A.
2024-09-01
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| Series: | Frontiers in Human Neuroscience |
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| Online Access: | https://www.frontiersin.org/articles/10.3389/fnhum.2024.1436205/full |
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| author | Nafiseh Karimi Rassoul Amirfattahi Abolghasem Zeidaabadi Nezhad |
| author_facet | Nafiseh Karimi Rassoul Amirfattahi Abolghasem Zeidaabadi Nezhad |
| author_sort | Nafiseh Karimi |
| collection | DOAJ |
| description | Deep brain stimulation (DBS) has long been the conventional method for targeting deep brain structures, but noninvasive alternatives like transcranial Temporal Interference Stimulation (tTIS) are gaining traction. Research has shown that alternating current influences brain oscillations through neural modulation. Understanding how neurons respond to the stimulus envelope, particularly considering tTIS’s high-frequency carrier, is vital for elucidating its mechanism of neuronal engagement. This study aims to explore the focal effects of tTIS across varying amplitudes and modulation depths in different brain regions. An excitatory-inhibitory network using the Izhikevich neuron model was employed to investigate responses to tTIS and compare them with transcranial Alternating Current Stimulation (tACS). We utilized a multi-scale model that integrates brain tissue modeling and network computational modeling to gain insights into the neuromodulatory effects of tTIS on the human brain. By analyzing the parametric space, we delved into phase, amplitude, and frequency entrainment to elucidate how tTIS modulates endogenous alpha oscillations. Our findings highlight a significant difference in current intensity requirements between tTIS and tACS, with tTIS requiring notably higher intensity. We observed distinct network entrainment patterns, primarily due to tTIS’s high-frequency component, whereas tACS exhibited harmonic entrainment that tTIS lacked. Spatial resolution analysis of tTIS, conducted via computational modeling and brain field distribution at a 13 Hz stimulation frequency, revealed modulation in deep brain areas, with minimal effects on the surface. Notably, we observed increased power within intrinsic and stimulation bands beneath the electrodes, attributed to the high stimulus signal amplitude. Additionally, Phase Locking Value (PLV) showed slight increments in non-deep areas. Our analysis indicates focal stimulation using tTIS, prompting further investigation into the necessity of high amplitudes to significantly affect deep brain regions, which warrants validation through clinical experiments. |
| format | Article |
| id | doaj-art-1351fa8967ec41ca89b565bf0a375ad0 |
| institution | OA Journals |
| issn | 1662-5161 |
| language | English |
| publishDate | 2024-09-01 |
| publisher | Frontiers Media S.A. |
| record_format | Article |
| series | Frontiers in Human Neuroscience |
| spelling | doaj-art-1351fa8967ec41ca89b565bf0a375ad02025-08-20T01:54:44ZengFrontiers Media S.A.Frontiers in Human Neuroscience1662-51612024-09-011810.3389/fnhum.2024.14362051436205Neuromodulation effect of temporal interference stimulation based on network computational modelNafiseh KarimiRassoul AmirfattahiAbolghasem Zeidaabadi NezhadDeep brain stimulation (DBS) has long been the conventional method for targeting deep brain structures, but noninvasive alternatives like transcranial Temporal Interference Stimulation (tTIS) are gaining traction. Research has shown that alternating current influences brain oscillations through neural modulation. Understanding how neurons respond to the stimulus envelope, particularly considering tTIS’s high-frequency carrier, is vital for elucidating its mechanism of neuronal engagement. This study aims to explore the focal effects of tTIS across varying amplitudes and modulation depths in different brain regions. An excitatory-inhibitory network using the Izhikevich neuron model was employed to investigate responses to tTIS and compare them with transcranial Alternating Current Stimulation (tACS). We utilized a multi-scale model that integrates brain tissue modeling and network computational modeling to gain insights into the neuromodulatory effects of tTIS on the human brain. By analyzing the parametric space, we delved into phase, amplitude, and frequency entrainment to elucidate how tTIS modulates endogenous alpha oscillations. Our findings highlight a significant difference in current intensity requirements between tTIS and tACS, with tTIS requiring notably higher intensity. We observed distinct network entrainment patterns, primarily due to tTIS’s high-frequency component, whereas tACS exhibited harmonic entrainment that tTIS lacked. Spatial resolution analysis of tTIS, conducted via computational modeling and brain field distribution at a 13 Hz stimulation frequency, revealed modulation in deep brain areas, with minimal effects on the surface. Notably, we observed increased power within intrinsic and stimulation bands beneath the electrodes, attributed to the high stimulus signal amplitude. Additionally, Phase Locking Value (PLV) showed slight increments in non-deep areas. Our analysis indicates focal stimulation using tTIS, prompting further investigation into the necessity of high amplitudes to significantly affect deep brain regions, which warrants validation through clinical experiments.https://www.frontiersin.org/articles/10.3389/fnhum.2024.1436205/fulltranscranial temporal interference stimulationbrain stimulationnetwork computational modelmulti scale modelneuromodulation |
| spellingShingle | Nafiseh Karimi Rassoul Amirfattahi Abolghasem Zeidaabadi Nezhad Neuromodulation effect of temporal interference stimulation based on network computational model Frontiers in Human Neuroscience transcranial temporal interference stimulation brain stimulation network computational model multi scale model neuromodulation |
| title | Neuromodulation effect of temporal interference stimulation based on network computational model |
| title_full | Neuromodulation effect of temporal interference stimulation based on network computational model |
| title_fullStr | Neuromodulation effect of temporal interference stimulation based on network computational model |
| title_full_unstemmed | Neuromodulation effect of temporal interference stimulation based on network computational model |
| title_short | Neuromodulation effect of temporal interference stimulation based on network computational model |
| title_sort | neuromodulation effect of temporal interference stimulation based on network computational model |
| topic | transcranial temporal interference stimulation brain stimulation network computational model multi scale model neuromodulation |
| url | https://www.frontiersin.org/articles/10.3389/fnhum.2024.1436205/full |
| work_keys_str_mv | AT nafisehkarimi neuromodulationeffectoftemporalinterferencestimulationbasedonnetworkcomputationalmodel AT rassoulamirfattahi neuromodulationeffectoftemporalinterferencestimulationbasedonnetworkcomputationalmodel AT abolghasemzeidaabadinezhad neuromodulationeffectoftemporalinterferencestimulationbasedonnetworkcomputationalmodel |