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Wilson MT, Goldsworthy MR, Vallence AM, Fornito A, Rogasch NC. Finding synaptic couplings from a biophysical model of motor evoked potentials after theta-burst transcranial magnetic stimulation. Brain Res 2023; 1801:148205. [PMID: 36563834 DOI: 10.1016/j.brainres.2022.148205] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/29/2022] [Revised: 12/14/2022] [Accepted: 12/15/2022] [Indexed: 12/24/2022]
Abstract
OBJECTIVE We aimed to use measured input-output (IO) data to identify the best fitting model for motor evoked potentials. METHODS We analyzed existing IO data before and after intermittent and continuous theta-burst stimulation (iTBS & cTBS) from a small group of subjects (18 for each). We fitted individual synaptic couplings and sensitivity parameters using variations of a biophysical model. A best performing model was selected and analyzed. RESULTS cTBS gives a broad reduction in MEPs for amplitudes larger than resting motor threshold (RMT). Close to threshold, iTBS gives strong potentiation. The model captures individual IO curves. There is no change to the population average synaptic weights post TBS but the change in excitatory-to-excitatory synaptic coupling is strongly correlated with the experimental post-TBS response relative to baseline. CONCLUSIONS The model describes population-averaged and individual IO curves, and their post-TBS change. Variation among individuals is accounted for with variation in synaptic couplings, and variation in sensitivity of neural response to stimulation. SIGNIFICANCE The best fitting model could be applied more broadly and validation studies could elucidate underlying biophysical meaning of parameters.
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Affiliation(s)
- Marcus T Wilson
- Te Aka Mātuatua-School of Science, University of Waikato, Hamilton, New Zealand.
| | - Mitchell R Goldsworthy
- Lifespan Human Neurophysiology Group, Adelaide Medical School, University of Adelaide, Adelaide, Australia; Hopwood Centre for Neurobiology, Lifelong Health Theme, South Australian Health and Medical Research Institute (SAHMRI), Adelaide, Australia; Discipline of Psychiatry, Adelaide Medical School, University of Adelaide, Adelaide, Australia
| | - Ann-Maree Vallence
- Discipline of Psychology, College of Science, Health, Engineering and Education, Murdoch University, Perth, Australia; Centre for Healthy Ageing, Health Futures Institute, Murdoch University, Perth, Australia
| | - Alex Fornito
- Turner Institute for Brain and Mental Health, School of Psychological Sciences, and Monash Biomedical Imaging, Monash University, Victoria, Australia
| | - Nigel C Rogasch
- Discipline of Psychiatry, Adelaide Medical School, University of Adelaide, Adelaide, Australia; Turner Institute for Brain and Mental Health, School of Psychological Sciences, and Monash Biomedical Imaging, Monash University, Victoria, Australia; South Australian Health and Medical Research Institute, Australia
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Zhang H, Shen Z, Zhao Y, Du L, Deng Z. Dynamical Mechanism Analysis of Three Neuroregulatory Strategies on the Modulation of Seizures. Int J Mol Sci 2022; 23:13652. [PMID: 36362443 PMCID: PMC9657301 DOI: 10.3390/ijms232113652] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.5] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/31/2022] [Revised: 10/30/2022] [Accepted: 11/02/2022] [Indexed: 08/11/2023] Open
Abstract
This paper attempts to explore and compare the regulatory mechanisms of optogenetic stimulation (OS), deep brain stimulation (DBS) and electromagnetic induction on epilepsy. Based on the Wilson-Cowan model, we first demonstrate that the external input received by excitatory and inhibitory neural populations can induce rich dynamic bifurcation behaviors such as Hopf bifurcation, and make the system exhibit epileptic and normal states. Then, both OS and DBS are shown to be effective in controlling the epileptic state to a normal low-level state, and the stimulus parameters have a broad effective range. However, electromagnetic induction cannot directly control epilepsy to this desired state, even if it can significantly reduce the oscillation frequency of neural populations. One main difference worth noting is that the high spatiotemporal specificity of OS allows it to target inhibitory neuronal populations, whereas DBS and electromagnetic induction can only stimulate excitatory as well as inhibitory neuronal populations together. Next, the propagation behavior of epilepsy is explored under a typical three-node feedback loop structure. An increase in coupling strength accelerates and exacerbates epileptic activity in other brain regions. Finally, OS and DBS applied to the epileptic focus play similar positive roles in controlling the behavior of the area of seizure propagation, while electromagnetic induction still only achieves unsatisfactory effects. It is hoped that these dynamical results can provide insights into the treatment of epilepsy as well as other neurological disorders.
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Affiliation(s)
- Honghui Zhang
- School of Mathematics and Statistics, Northwestern Polytechnical University, Xi’an 710072, China
- MIIT Key Laboratory of Dynamics and Control of Complex Systems, Xi’an 710072, China
| | - Zhuan Shen
- School of Mathematics and Statistics, Northwestern Polytechnical University, Xi’an 710072, China
- MIIT Key Laboratory of Dynamics and Control of Complex Systems, Xi’an 710072, China
| | - Yuzhi Zhao
- School of Mathematics and Statistics, Northwestern Polytechnical University, Xi’an 710072, China
- MIIT Key Laboratory of Dynamics and Control of Complex Systems, Xi’an 710072, China
| | - Lin Du
- School of Mathematics and Statistics, Northwestern Polytechnical University, Xi’an 710072, China
- MIIT Key Laboratory of Dynamics and Control of Complex Systems, Xi’an 710072, China
| | - Zichen Deng
- School of Mathematics and Statistics, Northwestern Polytechnical University, Xi’an 710072, China
- MIIT Key Laboratory of Dynamics and Control of Complex Systems, Xi’an 710072, China
- School of Aeronautics, Northwestern Polytechnical University, Xi’an 710072, China
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Wilson MT, Moezzi B, Rogasch NC. Modeling motor-evoked potentials from neural field simulations of transcranial magnetic stimulation. Clin Neurophysiol 2020; 132:412-428. [PMID: 33450564 DOI: 10.1016/j.clinph.2020.10.032] [Citation(s) in RCA: 3] [Impact Index Per Article: 0.8] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/24/2019] [Revised: 10/18/2020] [Accepted: 10/28/2020] [Indexed: 12/19/2022]
Abstract
OBJECTIVE To develop a population-based biophysical model of motor-evoked potentials (MEPs) following transcranial magnetic stimulation (TMS). METHODS We combined an existing MEP model with population-based cortical modeling. Layer 2/3 excitatory and inhibitory neural populations, modeled with neural-field theory, are stimulated with TMS and feed layer 5 corticospinal neurons, which also couple directly but weakly to the TMS pulse. The layer 5 output controls mean motoneuron responses, which generate a series of single motor-unit action potentials that are summed to estimate a MEP. RESULTS A MEP waveform was generated comparable to those observed experimentally. The model captured TMS phenomena including a sigmoidal input-output curve, common paired pulse effects (short interval intracortical inhibition, intracortical facilitation, long interval intracortical inhibition) including responses to pharmacological interventions, and a cortical silent period. Changes in MEP amplitude following theta burst paradigms were observed including variability in outcome direction. CONCLUSIONS The model reproduces effects seen in common TMS paradigms. SIGNIFICANCE The model allows population-based modeling of changes in cortical dynamics due to TMS protocols to be assessed in terms of changes in MEPs, thus allowing a clear comparison between population-based modeling predictions and typical experimental outcome measures.
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Affiliation(s)
- Marcus T Wilson
- Te Aka Mātuatua-School of Science, University of Waikato, Hamilton, New Zealand.
| | - Bahar Moezzi
- Cognitive Ageing and Impairment Neurosciences Laboratory, School of Psychology, Social Work and Social Policy, The University of South Australia, Australia
| | - Nigel C Rogasch
- Discipline of Psychiatry, Adelaide Medical School, University of Adelaide, Australia; South Australian Health and Medical Research Institute, Australia; Brain, Mind and Society Research Hub, The School of Psychologcial Sciences, The Turner Institute for Brain and Mental Health and Monash Biomedical Imaging, Monash University, Australia
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Merolli A, Mao Y, Voronin G, Steele JAM, Murthy NS, Kohn J. A method to deliver patterned electrical impulses to Schwann cells cultured on an artificial axon. Neural Regen Res 2019; 14:1052-1059. [PMID: 30762018 PMCID: PMC6404504 DOI: 10.4103/1673-5374.250626] [Citation(s) in RCA: 3] [Impact Index Per Article: 0.6] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 01/29/2023] Open
Abstract
Information from the brain travels back and forth along peripheral nerves in the form of electrical impulses generated by neurons and these impulses have repetitive patterns. Schwann cells in peripheral nerves receive molecular signals from axons to coordinate the process of myelination. There is evidence, however, that non-molecular signals play an important role in myelination in the form of patterned electrical impulses generated by neuronal activity. The role of patterned electrical impulses has been investigated in the literature using co-cultures of neurons and myelinating cells. The co-culturing method, however, prevents the uncoupling of the direct effect of patterned electrical impulses on myelinating cells from the indirect effect mediated by neurons. To uncouple these effects and focus on the direct response of Schwann cells, we developed an in vitro model where an electroconductive carbon fiber acts as an artificial axon. The fiber provides only the biophysical characteristics of an axon but does not contribute any molecular signaling. In our “suspended wire model”, the carbon fiber is suspended in a liquid media supported by a 3D printed scaffold. Patterned electrical impulses are generated by an Arduino 101 microcontroller. In this study, we describe the technology needed to set-up and eventually replicate this model. We also report on our initial in vitro tests where we were able to document the adherence and ensheath of human Schwann cells to the carbon fiber in the presence of patterned electrical impulses (hSCs were purchased from ScienCell Research Laboratories, Carlsbad, CA, USA; ScienCell fulfills the ethic requirements, including donor’s consent). This technology will likely make feasible to investigate the response of Schwann cells to patterned electrical impulses in the future.
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Affiliation(s)
- Antonio Merolli
- New Jersey Center for Biomaterials, Rutgers - The State University of New Jersey, Piscataway, NJ, USA
| | - Yong Mao
- New Jersey Center for Biomaterials, Rutgers - The State University of New Jersey, Piscataway, NJ, USA
| | - Gregory Voronin
- In Vivo Research Services, Rutgers - The State University of New Jersey, Piscataway, NJ, USA
| | - Joseph A M Steele
- New Jersey Center for Biomaterials, Rutgers - The State University of New Jersey, Piscataway, NJ, USA
| | - N Sanjeeva Murthy
- New Jersey Center for Biomaterials, Rutgers - The State University of New Jersey, Piscataway, NJ, USA
| | - Joachim Kohn
- New Jersey Center for Biomaterials, Rutgers - The State University of New Jersey, Piscataway, NJ, USA
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Sanz-Leon P, Robinson PA, Knock SA, Drysdale PM, Abeysuriya RG, Fung FK, Rennie CJ, Zhao X. NFTsim: Theory and Simulation of Multiscale Neural Field Dynamics. PLoS Comput Biol 2018; 14:e1006387. [PMID: 30133448 PMCID: PMC6122812 DOI: 10.1371/journal.pcbi.1006387] [Citation(s) in RCA: 21] [Impact Index Per Article: 3.5] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/11/2018] [Revised: 09/04/2018] [Accepted: 07/22/2018] [Indexed: 01/02/2023] Open
Abstract
A user ready, portable, documented software package, NFTsim, is presented to facilitate numerical simulations of a wide range of brain systems using continuum neural field modeling. NFTsim enables users to simulate key aspects of brain activity at multiple scales. At the microscopic scale, it incorporates characteristics of local interactions between cells, neurotransmitter effects, synaptodendritic delays and feedbacks. At the mesoscopic scale, it incorporates information about medium to large scale axonal ranges of fibers, which are essential to model dissipative wave transmission and to produce synchronous oscillations and associated cross-correlation patterns as observed in local field potential recordings of active tissue. At the scale of the whole brain, NFTsim allows for the inclusion of long range pathways, such as thalamocortical projections, when generating macroscopic activity fields. The multiscale nature of the neural activity produced by NFTsim has the potential to enable the modeling of resulting quantities measurable via various neuroimaging techniques. In this work, we give a comprehensive description of the design and implementation of the software. Due to its modularity and flexibility, NFTsim enables the systematic study of an unlimited number of neural systems with multiple neural populations under a unified framework and allows for direct comparison with analytic and experimental predictions. The code is written in C++ and bundled with Matlab routines for a rapid quantitative analysis and visualization of the outputs. The output of NFTsim is stored in plain text file enabling users to select from a broad range of tools for offline analysis. This software enables a wide and convenient use of powerful physiologically-based neural field approaches to brain modeling. NFTsim is distributed under the Apache 2.0 license.
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Affiliation(s)
- Paula Sanz-Leon
- School of Physics, University of Sydney, Sydney, Australia
- Center for Integrative Brain Function, University of Sydney, Sydney, Australia
| | - Peter A. Robinson
- School of Physics, University of Sydney, Sydney, Australia
- Center for Integrative Brain Function, University of Sydney, Sydney, Australia
| | - Stuart A. Knock
- School of Physics, University of Sydney, Sydney, Australia
- Center for Integrative Brain Function, University of Sydney, Sydney, Australia
| | | | - Romesh G. Abeysuriya
- School of Physics, University of Sydney, Sydney, Australia
- Center for Integrative Brain Function, University of Sydney, Sydney, Australia
- Oxford Centre for Human Brain Activity, Wellcome Centre for Integrative Neuroimaging, Department of Psychiatry, University of Oxford, Oxford, United Kingdom
| | - Felix K. Fung
- School of Physics, University of Sydney, Sydney, Australia
- Center for Integrative Brain Function, University of Sydney, Sydney, Australia
- Downstate Medical Center, State University of New York, Brooklyn, New York, United States of America
| | | | - Xuelong Zhao
- School of Physics, University of Sydney, Sydney, Australia
- Center for Integrative Brain Function, University of Sydney, Sydney, Australia
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Wilson MT, Fulcher BD, Fung PK, Robinson P, Fornito A, Rogasch NC. Biophysical modeling of neural plasticity induced by transcranial magnetic stimulation. Clin Neurophysiol 2018; 129:1230-1241. [DOI: 10.1016/j.clinph.2018.03.018] [Citation(s) in RCA: 19] [Impact Index Per Article: 3.2] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/06/2017] [Revised: 02/28/2018] [Accepted: 03/14/2018] [Indexed: 10/17/2022]
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Müller EJ, Robinson PA. Quantitative theory of deep brain stimulation of the subthalamic nucleus for the suppression of pathological rhythms in Parkinson's disease. PLoS Comput Biol 2018; 14:e1006217. [PMID: 29813060 PMCID: PMC5993558 DOI: 10.1371/journal.pcbi.1006217] [Citation(s) in RCA: 10] [Impact Index Per Article: 1.7] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/21/2018] [Revised: 06/08/2018] [Accepted: 05/21/2018] [Indexed: 11/28/2022] Open
Abstract
Deep brain stimulation (DBS) of the subthalamic nucleus (STN) is modeled to explore the mechanisms of this effective, but poorly understood, treatment for motor symptoms of drug-refractory Parkinson's disease and dystonia. First, a neural field model of the corticothalamic-basal ganglia (CTBG) system is developed that reproduces key clinical features of Parkinson's disease, including its characteristic 4-8 Hz and 13-30 Hz electrophysiological signatures. Deep brain stimulation of the STN is then modeled and shown to suppress the pathological 13-30 Hz (beta) activity for physiologically realistic and optimized stimulus parameters. This supports the idea that suppression of abnormally coherent activity in the CTBG system is a major factor in DBS therapy for Parkinson's disease, by permitting normal dynamics to resume. At high stimulus intensities, nonlinear effects in the target population mediate wave-wave interactions between resonant beta activity and the stimulus pulse train, leading to complex spectral structure that shows remarkable similarity to that seen in steady-state evoked potential experiments.
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Affiliation(s)
- Eli J. Müller
- School of Physics, The University of Sydney, Sydney, New South Wales, Australia
- Center for Integrative Brain Function, The University of Sydney, Sydney, New South Wales, Australia
| | - Peter A. Robinson
- School of Physics, The University of Sydney, Sydney, New South Wales, Australia
- Center for Integrative Brain Function, The University of Sydney, Sydney, New South Wales, Australia
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Cocchi L, Zalesky A. Personalized Transcranial Magnetic Stimulation in Psychiatry. BIOLOGICAL PSYCHIATRY: COGNITIVE NEUROSCIENCE AND NEUROIMAGING 2018; 3:731-741. [PMID: 29571586 DOI: 10.1016/j.bpsc.2018.01.008] [Citation(s) in RCA: 34] [Impact Index Per Article: 5.7] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Subscribe] [Scholar Register] [Received: 11/22/2017] [Revised: 01/18/2018] [Accepted: 01/20/2018] [Indexed: 01/02/2023]
Abstract
Transcranial magnetic stimulation (TMS) is a noninvasive brain stimulation technique that allows for modulating the activity of local neural populations and related neural networks. TMS is touted as a viable intervention to normalize brain activity and alleviate some psychiatric symptoms. However, TMS interventions are known to be only moderately reliable, and the efficacy of such therapies remains to be proven for psychiatric disorders other than depression. We review new opportunities to personalize TMS interventions using neuroimaging and computational modeling, aiming to optimize treatment to suit particular individuals and clinical subgroups. Specifically, we consider the prospect of improving the efficacy of existing TMS interventions by parsing broad diagnostic categories into biologically and clinically homogeneous biotypes. Biotypes can provide distinct treatment targets for optimized TMS interventions. We further discuss the utility of computational models in refining TMS personalization and efficiently establishing optimal cortical targets for distinct biotypes. Personalizing cortical stimulation targets, treatment frequencies, and intensities can improve the therapeutic efficacy of TMS and potentially establish noninvasive brain stimulation as a viable treatment for psychiatric symptoms.
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Affiliation(s)
- Luca Cocchi
- QIMR Berghofer Medical Research Institute, University of Queensland, Brisbane, Queensland, Australia.
| | - Andrew Zalesky
- Melbourne Neuropsychiatry Centre, University of Melbourne, Melbourne, Victoria, Australia; Department of Biomedical Engineering, University of Melbourne, Melbourne, Victoria, Australia
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Goetz SM, Deng ZD. The development and modelling of devices and paradigms for transcranial magnetic stimulation. Int Rev Psychiatry 2017; 29:115-145. [PMID: 28443696 PMCID: PMC5484089 DOI: 10.1080/09540261.2017.1305949] [Citation(s) in RCA: 38] [Impact Index Per Article: 5.4] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 10/12/2016] [Revised: 03/03/2017] [Accepted: 03/09/2017] [Indexed: 12/20/2022]
Abstract
Magnetic stimulation is a non-invasive neurostimulation technique that can evoke action potentials and modulate neural circuits through induced electric fields. Biophysical models of magnetic stimulation have become a major driver for technological developments and the understanding of the mechanisms of magnetic neurostimulation and neuromodulation. Major technological developments involve stimulation coils with different spatial characteristics and pulse sources to control the pulse waveform. While early technological developments were the result of manual design and invention processes, there is a trend in both stimulation coil and pulse source design to mathematically optimize parameters with the help of computational models. To date, macroscopically highly realistic spatial models of the brain, as well as peripheral targets, and user-friendly software packages enable researchers and practitioners to simulate the treatment-specific and induced electric field distribution in the brains of individual subjects and patients. Neuron models further introduce the microscopic level of neural activation to understand the influence of activation dynamics in response to different pulse shapes. A number of models that were designed for online calibration to extract otherwise covert information and biomarkers from the neural system recently form a third branch of modelling.
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Affiliation(s)
- Stefan M Goetz
- a Department of Psychiatry & Behavioral Sciences, Division for Brain Stimulation & Neurophysiology , Duke University , Durham , NC , USA
- b Department of Electrical & Computer Engineering , Duke University , Durham , NC , USA
- c Department of Neurosurgery , Duke University , Durham , NC , USA
| | - Zhi-De Deng
- a Department of Psychiatry & Behavioral Sciences, Division for Brain Stimulation & Neurophysiology , Duke University , Durham , NC , USA
- d Intramural Research Program, Experimental Therapeutics & Pathophysiology Branch, Noninvasive Neuromodulation Unit , National Institutes of Health, National Institute of Mental Health , Bethesda , MD , USA
- e Duke Institute for Brain Sciences , Duke University , Durham , NC , USA
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Gollo LL, Roberts JA, Cocchi L. Mapping how local perturbations influence systems-level brain dynamics. Neuroimage 2017; 160:97-112. [PMID: 28126550 DOI: 10.1016/j.neuroimage.2017.01.057] [Citation(s) in RCA: 78] [Impact Index Per Article: 11.1] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/01/2016] [Revised: 12/12/2016] [Accepted: 01/23/2017] [Indexed: 11/15/2022] Open
Abstract
The human brain exhibits a distinct spatiotemporal organization that supports brain function and can be manipulated via local brain stimulation. Such perturbations to local cortical dynamics are globally integrated by distinct neural systems. However, it remains unclear how local changes in neural activity affect large-scale system dynamics. Here, we briefly review empirical and computational studies addressing how localized perturbations affect brain activity. We then systematically analyze a model of large-scale brain dynamics, assessing how localized changes in brain activity at the different sites affect whole-brain dynamics. We find that local stimulation induces changes in brain activity that can be summarized by relatively smooth tuning curves, which relate a region's effectiveness as a stimulation site to its position within the cortical hierarchy. Our results also support the notion that brain hubs, operating in a slower regime, are more resilient to focal perturbations and critically contribute to maintain stability in global brain dynamics. In contrast, perturbations of peripheral regions, characterized by faster activity, have greater impact on functional connectivity. As a parallel with this region-level result, we also find that peripheral systems such as the visual and sensorimotor networks were more affected by local perturbations than high-level systems such as the cingulo-opercular network. Our findings highlight the importance of a periphery-to-core hierarchy to determine the effect of local stimulation on the brain network. This study also provides novel resources to orient empirical work aiming at manipulating functional connectivity using non-invasive brain stimulation.
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Affiliation(s)
| | - James A Roberts
- QIMR Berghofer Medical Research Institute, Brisbane, Australia; Centre of Excellence for Integrative Brain Function, QIMR Berghofer Medical Research Institute, Brisbane, Australia
| | - Luca Cocchi
- QIMR Berghofer Medical Research Institute, Brisbane, Australia.
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Matheson NA, Shemmell JBH, De Ridder D, Reynolds JNJ. Understanding the Effects of Repetitive Transcranial Magnetic Stimulation on Neuronal Circuits. Front Neural Circuits 2016; 10:67. [PMID: 27601980 PMCID: PMC4993761 DOI: 10.3389/fncir.2016.00067] [Citation(s) in RCA: 12] [Impact Index Per Article: 1.5] [Reference Citation Analysis] [Key Words] [Track Full Text] [Download PDF] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/05/2016] [Accepted: 08/09/2016] [Indexed: 01/26/2023] Open
Affiliation(s)
- Natalie A Matheson
- Department of Anatomy, Brain Research NZ, University of Otago Dunedin, New Zealand
| | - Jon B H Shemmell
- School of Physical Education, Sport and Exercise Sciences, Brain Research NZ, University of Otago Dunedin, New Zealand
| | - Dirk De Ridder
- Department of Surgical Sciences, Dunedin School of Medicine, Brain Research NZ, University of Otago Dunedin, New Zealand
| | - John N J Reynolds
- Department of Anatomy, Brain Research NZ, University of Otago Dunedin, New Zealand
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Wilson MT, St George L. Repetitive Transcranial Magnetic Stimulation: A Call for Better Data. Front Neural Circuits 2016; 10:57. [PMID: 27536222 PMCID: PMC4971102 DOI: 10.3389/fncir.2016.00057] [Citation(s) in RCA: 15] [Impact Index Per Article: 1.9] [Reference Citation Analysis] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/13/2016] [Accepted: 07/20/2016] [Indexed: 01/20/2023] Open
Affiliation(s)
- Marcus T Wilson
- School of Engineering, University of Waikato Hamilton, New Zealand
| | - Lynley St George
- School of Engineering, University of Waikato Hamilton, New Zealand
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Wilson MT, Fung PK, Robinson PA, Shemmell J, Reynolds JNJ. Calcium dependent plasticity applied to repetitive transcranial magnetic stimulation with a neural field model. J Comput Neurosci 2016; 41:107-25. [DOI: 10.1007/s10827-016-0607-7] [Citation(s) in RCA: 9] [Impact Index Per Article: 1.1] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/29/2015] [Revised: 05/05/2016] [Accepted: 05/12/2016] [Indexed: 10/21/2022]
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Barry MD, Boddington LJ, Igelström KM, Gray JP, Shemmell J, Tseng KY, Oorschot DE, Reynolds JN. Utility of intracerebral theta burst electrical stimulation to attenuate interhemispheric inhibition and to promote motor recovery after cortical injury in an animal model. Exp Neurol 2014; 261:258-66. [DOI: 10.1016/j.expneurol.2014.05.023] [Citation(s) in RCA: 18] [Impact Index Per Article: 1.8] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/18/2013] [Revised: 05/12/2014] [Accepted: 05/23/2014] [Indexed: 10/25/2022]
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