Brain StimulationPub Date : 2025-01-01DOI: 10.1016/j.brs.2024.12.035
Keiichi Kitajo
{"title":"Metastability and Consistency of Large-scale Neural Networks revealed by TMS-EEGMetastability and Consistency of Large-scale Neural Networks revealed by TMS-EEG","authors":"Keiichi Kitajo","doi":"10.1016/j.brs.2024.12.035","DOIUrl":"10.1016/j.brs.2024.12.035","url":null,"abstract":"","PeriodicalId":9206,"journal":{"name":"Brain Stimulation","volume":"18 1","pages":"Page 225"},"PeriodicalIF":7.6,"publicationDate":"2025-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143480457","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":1,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Brain StimulationPub Date : 2025-01-01DOI: 10.1016/j.brs.2024.12.031
Pedro Gordon , Yufei Song , Olivier Roy , Johanna Metsomaa , Paolo Belardinelli , Maryam Rostami , Ulf Ziemann
{"title":"Two optimized sham-control methods for TMS-EEG and what they reveal about peripherally evoked potentials","authors":"Pedro Gordon , Yufei Song , Olivier Roy , Johanna Metsomaa , Paolo Belardinelli , Maryam Rostami , Ulf Ziemann","doi":"10.1016/j.brs.2024.12.031","DOIUrl":"10.1016/j.brs.2024.12.031","url":null,"abstract":"","PeriodicalId":9206,"journal":{"name":"Brain Stimulation","volume":"18 1","pages":"Pages 223-224"},"PeriodicalIF":7.6,"publicationDate":"2025-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143480612","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":1,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Brain StimulationPub Date : 2025-01-01DOI: 10.1016/j.brs.2024.12.1192
Zhen Qi , Gregory M. Noetscher , Alton Miles , Konstantin Weise , Thomas R. Knösche , Cameron R. Cadman , Alina R. Potashinsky , Kelu Liu , William A. Wartman , Guillermo Nunez Ponasso , Marom Bikson , Hanbing Lu , Zhi-De Deng , Aapo R. Nummenmaa , Sergey N. Makaroff
{"title":"Enabling electric field model of microscopically realistic brain","authors":"Zhen Qi , Gregory M. Noetscher , Alton Miles , Konstantin Weise , Thomas R. Knösche , Cameron R. Cadman , Alina R. Potashinsky , Kelu Liu , William A. Wartman , Guillermo Nunez Ponasso , Marom Bikson , Hanbing Lu , Zhi-De Deng , Aapo R. Nummenmaa , Sergey N. Makaroff","doi":"10.1016/j.brs.2024.12.1192","DOIUrl":"10.1016/j.brs.2024.12.1192","url":null,"abstract":"<div><h3>Background</h3><div>Modeling brain stimulation at the microscopic scale may reveal new paradigms for various stimulation modalities.</div></div><div><h3>Objective</h3><div>We present the largest map to date of extracellular electric field distributions within a layer L2/L3 mouse primary visual cortex brain sample. This was enabled by the automated analysis of serial section electron microscopy images with improved handling of image defects, covering a volume of 250 × 140 × 90 μm³.</div></div><div><h3>Methods</h3><div>The map was obtained by applying a uniform brain stimulation electric field at three different polarizations and accurately computing microscopic field perturbations using the boundary element fast multipole method. We used the map to identify the effect of microscopic field perturbations on the activation thresholds of individual neurons. Previous relevant studies modeled a macroscopically homogeneous cortical volume.</div></div><div><h3>Result</h3><div>Our result shows that the microscopic field perturbations – an ‘electric field spatial noise’ with a mean value of zero – only modestly influence the macroscopically predicted stimulation field strengths necessary for neuronal activation. The thresholds do not change by more than 10 % on average.</div></div><div><h3>Conclusion</h3><div>Under the stated limitations and assumptions of our method, this result essentially justifies the conventional theory of \"invisible\" neurons embedded in a macroscopic brain model for transcranial magnetic and transcranial electrical stimulation. However, our result is solely sample-specific and is only relevant to this relatively small sample with 396 neurons. It largely neglects the effect of the microcapillary network. Furthermore, we only considered the uniform impressed field and a single-pulse stimulation time course.</div></div>","PeriodicalId":9206,"journal":{"name":"Brain Stimulation","volume":"18 1","pages":"Pages 77-93"},"PeriodicalIF":7.6,"publicationDate":"2025-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142876100","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":1,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Brain StimulationPub Date : 2025-01-01DOI: 10.1016/j.brs.2025.01.008
Elva Arulchelvan , Sven Vanneste
{"title":"Transcutaneous electrical stimulation enhances episodic memory encoding via a noradrenaline-attention network, with associated neuroinflammatory changes","authors":"Elva Arulchelvan , Sven Vanneste","doi":"10.1016/j.brs.2025.01.008","DOIUrl":"10.1016/j.brs.2025.01.008","url":null,"abstract":"<div><h3>Background</h3><div>Attention plays a central role in learning and memory processes. Prior research has demonstrated how goal-directed attention influences successful performance on both attention and working memory tasks. However, an important question remains about whether long-term memory outcomes can be reliably enhanced by targeting attention processes.</div></div><div><h3>Objective</h3><div>To test the hypothesis that 40 Hz Non-invasive Transcutaneous Electrical Stimulation of the Greater Occipital Nerve (NITESGON) would enhance long-term memory encoding by upregulating theta activity in the dorsal attention network. We also hypothesised that this would be in association with upregulated noradrenaline activity and downregulated cytokine activity.</div></div><div><h3>Methods</h3><div>In two double-blinded experiments, learning and memory were tested via a Swahili-English word-association task completed on 2 visits (separated by 1 week). 60 individuals were randomized to assess 40 Hz NITESGON's effect compared to active-control (1 Hz) or sham conditions. Before and after stimulation, rs-EEG assessed theta activity in the dorsal attention network, and saliva measures were collected incl. salivary alpha amylase (sAA; a proxy for noradrenaline activity) and cytokines (IL-6, IL-1β and TNF-α).</div></div><div><h3>Results</h3><div>Participants receiving 40 Hz NITESGON learned and remembered more words than control or sham groups. There were no significant differences in consolidation between the groups. 40 Hz NITESGON was associated with increased theta activity in the dorsal attention network, and this activation was associated with enhanced learning but not memory performance. The 40 Hz NITESGON group had significantly upregulated sAA post-stimulation, with this associated with learning and memory (supporting a LC-NA mechanism). Modulation of IL-1β and TNF-α were not frequency specific. However, modulation of IL-6 was specific to 40 Hz and was associated with memory outcomes.</div></div><div><h3>Conclusion</h3><div>40 Hz NITESGON can activate a noradrenaline – dorsal attention network, to facilitate goal-directed attention during encoding stages of a long-term memory task, in association with neuroinflammatory changes.</div></div>","PeriodicalId":9206,"journal":{"name":"Brain Stimulation","volume":"18 1","pages":"Pages 191-207"},"PeriodicalIF":7.6,"publicationDate":"2025-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143000409","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":1,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Brain StimulationPub Date : 2025-01-01DOI: 10.1016/j.brs.2024.12.1193
Uttara U. Khatri , Kristen Pulliam , Muskan Manesiya , Melanie Vieyra Cortez , José del R. Millán , Sara J. Hussain
{"title":"Personalized whole-brain activity patterns predict human corticospinal tract activation in real-time","authors":"Uttara U. Khatri , Kristen Pulliam , Muskan Manesiya , Melanie Vieyra Cortez , José del R. Millán , Sara J. Hussain","doi":"10.1016/j.brs.2024.12.1193","DOIUrl":"10.1016/j.brs.2024.12.1193","url":null,"abstract":"<div><h3>Background</h3><div>Transcranial magnetic stimulation (TMS) interventions could feasibly treat stroke-related motor impairments, but their effects are highly variable. Brain state-dependent TMS approaches are a promising solution to this problem, but inter-individual variation in lesion location and oscillatory dynamics can make translating them to the poststroke brain challenging. Personalized brain state-dependent approaches specifically designed to address these challenges are needed.</div></div><div><h3>Methods</h3><div>As a first step towards this goal, we tested a novel machine learning-based EEG-TMS system that identifies personalized brain activity patterns reflecting strong and weak corticospinal tract (CST) activation (strong and weak CST states) in healthy adults in real-time. Participants completed a single-session study that included the acquisition of a TMS-EEG-EMG training dataset, personalized classifier training, and real-time EEG-informed single-pulse TMS during classifier-predicted personalized CST states.</div></div><div><h3>Results</h3><div>MEP amplitudes elicited in real-time during classifier-predicted personalized strong CST states were significantly larger than those elicited during corresponding weak and random CST states. MEP amplitudes elicited in real-time during classifier-predicted personalized strong CST states were also significantly less variable than those elicited during corresponding weak CST states. Personalized CST states lasted for ∼1–2 s at a time and ∼1 s elapsed between consecutive similar states. Individual participants exhibited unique differences in spectro-spatial EEG patterns between classifier-predicted personalized strong and weak CST states.</div></div><div><h3>Conclusion</h3><div>Our results show for the first time that personalized whole-brain EEG activity patterns predict CST activation in real-time in healthy humans. These findings represent a pivotal step towards using personalized brain state-dependent TMS interventions to promote poststroke CST function.</div></div>","PeriodicalId":9206,"journal":{"name":"Brain Stimulation","volume":"18 1","pages":"Pages 64-76"},"PeriodicalIF":7.6,"publicationDate":"2025-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142881306","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":1,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}