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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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Aghili Yajadda MM, Robinson PA, Henderson JA. Generalized neural field theory of cortical plasticity illustrated by an application to the linear phase of ocular dominance column formation in primary visual cortex. BIOLOGICAL CYBERNETICS 2022; 116:33-52. [PMID: 34773503 DOI: 10.1007/s00422-021-00901-w] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Received: 07/09/2021] [Accepted: 09/30/2021] [Indexed: 06/13/2023]
Abstract
Physiologically based neural field theory (NFT) is extended to encompass cortical plasticity dynamics. An illustrative application is provided which treats the evolution of the connectivity of left- and right-eye visual stimuli to neuronal populations in the primary visual cortex (V1), and the initial, linear phase of formation of approximately one-dimensional (1D) ocular dominance columns (ODCs) that sets their transverse spatial scale. This links V1 activity, structure, and physiology within a single theory that already accounts for a range of other brain activity and connectivity phenomena, thereby enabling ODC formation and many other phenomena to be interrelated and cortical parameters to be constrained across multiple domains. The results accord with experimental ODC widths for realistic cortical parameters and are based directly on a unified description of the neuronal populations involved, their connection strengths, and the neuronal activity they support. Other key results include simple analytic approximations for ODC widths and the parameters of maximum growth rate, constraints on cortical excitatory and inhibitory gains, elucidation of the roles of specific poles of the V1 response function, and the fact that ODCs are not formed when input stimuli are fully correlated between eyes. This work provides a basis for further generalization of NFT to model other plasticity phenomena, thereby linking them to the range multiscale phenomena accounted for by NFT.
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Affiliation(s)
- M M Aghili Yajadda
- School of Physics, University of Sydney, Sydney, NSW, 2006, Australia
- Center for Integrative Brain Function, University of Sydney, Sydney, NSW, 2006, Australia
| | - P A Robinson
- School of Physics, University of Sydney, Sydney, NSW, 2006, Australia
- Center for Integrative Brain Function, University of Sydney, Sydney, NSW, 2006, Australia
| | - J A Henderson
- School of Physics, University of Sydney, Sydney, NSW, 2006, Australia.
- Center for Integrative Brain Function, University of Sydney, Sydney, NSW, 2006, Australia.
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Griffiths JD, Bastiaens SP, Kaboodvand N. Whole-Brain Modelling: Past, Present, and Future. ADVANCES IN EXPERIMENTAL MEDICINE AND BIOLOGY 2022; 1359:313-355. [DOI: 10.1007/978-3-030-89439-9_13] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 10/18/2022]
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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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Robinson PA. Neural field theory of effects of brain modifications and lesions on functional connectivity: Acute effects, short-term homeostasis, and long-term plasticity. Phys Rev E 2019; 99:042407. [PMID: 31108595 DOI: 10.1103/physreve.99.042407] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/06/2018] [Indexed: 11/07/2022]
Abstract
Neural field theory is used to predict the functional connectivity effects of lesions or other modifications to effective connectivity. Widespread initial changes are predicted after localized or diffuse changes to white or gray matter, consistent with observations, and enabling lesion severity indexes to be defined. It is shown how short-term homeostasis and longer-term plasticity can reduce perturbations while maintaining brain criticality under conditions where some connections remain fixed because of damage in the lesion core. The extent to which such effects can compensate for initial connectivity changes is then explored, showing that the strongest corrective changes are concentrated toward the edges of the perturbation if it is localized and its core is fixed. The results are applicable to inferring underlying connectivity changes and to interpreting and monitoring functional connectivity modifications after lesions, injury, surgery, drugs, or brain stimulation.
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Affiliation(s)
- P A Robinson
- School of Physics, University of Sydney, New South Wales 2006, Australia and Center for Integrative Brain Function, University of Sydney, New South Wales 2006, Australia
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Assadzadeh S, Robinson PA. Necessity of the sleep-wake cycle for synaptic homeostasis: system-level analysis of plasticity in the corticothalamic system. ROYAL SOCIETY OPEN SCIENCE 2018; 5:171952. [PMID: 30473798 PMCID: PMC6227995 DOI: 10.1098/rsos.171952] [Citation(s) in RCA: 3] [Impact Index Per Article: 0.5] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Figures] [Subscribe] [Scholar Register] [Received: 01/03/2018] [Accepted: 09/13/2018] [Indexed: 06/09/2023]
Abstract
Neural field theory is used to study the system-level effects of plasticity in the corticothalamic system, where arousal states are represented parametrically by the connection strengths of the system, among other physiologically based parameters. It is found that the plasticity dynamics have no fixed points or closed cycles in the parameter space of the connection strengths, but parameter subregions exist where flows have opposite signs. Remarkably, these subregions coincide with previously identified regions that correspond to wake and slow-wave sleep, thus demonstrating state dependence of the sign of synaptic modification. We then show that a closed cycle in the parameter space is possible when the plasticity dynamics are driven by the ascending arousal system, which cycles the brain between sleep and wake to complete a closed loop that includes arcs through the opposite-flow subregions. Thus, it is concluded that both wake and sleep are necessary, and together are able to stabilize connection weights in the brain over the daily cycle, thereby providing quantitative realization of the synaptic homeostasis hypothesis.
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Affiliation(s)
- S. Assadzadeh
- School of Physics, The University of Sydney, New South Wales 2006, Australia
- Center for Integrative Brain Function, The University of Sydney, New South Wales 2006, Australia
| | - P. A. Robinson
- School of Physics, The University of Sydney, New South Wales 2006, Australia
- Center for Integrative Brain Function, The University of Sydney, New South Wales 2006, Australia
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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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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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Roy N, Sanz-Leon P, Robinson PA. Spectral signatures of activity-dependent neural feedback in the corticothalamic system. Phys Rev E 2017; 96:052310. [PMID: 29347805 DOI: 10.1103/physreve.96.052310] [Citation(s) in RCA: 3] [Impact Index Per Article: 0.4] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/05/2017] [Indexed: 11/07/2022]
Abstract
The modulation of neural quantities by presynaptic and postsynaptic activities via local feedback processes is investigated by incorporating nonlinear phenomena such as relative refractory period, synaptic enhancement, synaptic depression, and habituation. This is done by introducing susceptibilities, which quantify the response in either firing threshold or synaptic strength to unit change in either presynaptic or postsynaptic activity. Effects on the power spectra are then analyzed for a realistic corticothalamic model to determine the spectral signatures of various nonlinear processes and to what extent these are distinct. Depending on the feedback processes, there can be enhancements or reductions in low-frequency and/or alpha power, splitting of the alpha resonance, and/or appearance of new resonances at high frequencies. These features in the power spectra allow processes to be fully distinguished where they are unique, or partly distinguished if they are common to only a subset of feedbacks, and can potentially be used to constrain the types, strengths, and dynamics of feedbacks present.
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Affiliation(s)
- N Roy
- School of Physics, University of Sydney, New South Wales 2006, Australia and Center for Integrative Brain Function, University of Sydney, New South Wales 2006, Australia
| | - P Sanz-Leon
- School of Physics, University of Sydney, New South Wales 2006, Australia and Center for Integrative Brain Function, University of Sydney, New South Wales 2006, Australia
| | - P A Robinson
- School of Physics, University of Sydney, New South Wales 2006, Australia and Center for Integrative Brain Function, University of Sydney, New South Wales 2006, 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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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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Robinson PA, Roy N. Neural field theory of nonlinear wave-wave and wave-neuron processes. PHYSICAL REVIEW. E, STATISTICAL, NONLINEAR, AND SOFT MATTER PHYSICS 2015; 91:062719. [PMID: 26172747 DOI: 10.1103/physreve.91.062719] [Citation(s) in RCA: 14] [Impact Index Per Article: 1.6] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Received: 04/23/2015] [Indexed: 06/04/2023]
Abstract
Systematic expansion of neural field theory equations in terms of nonlinear response functions is carried out to enable a wide variety of nonlinear wave-wave and wave-neuron processes to be treated systematically in systems involving multiple neural populations. The results are illustrated by analyzing second-harmonic generation, and they can also be applied to wave-wave coalescence, multiharmonic generation, facilitation, depression, refractoriness, and other nonlinear processes.
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Affiliation(s)
- P A Robinson
- School of Physics, University of Sydney, New South Wales 2006, Australia
- Center for Integrative Brain Function, University of Sydney, New South Wales 2006, Australia
- Neurosleep, 431 Glebe Point Road, Glebe, New South Wales 2037, Australia
| | - N Roy
- School of Physics, University of Sydney, New South Wales 2006, Australia
- Center for Integrative Brain Function, University of Sydney, New South Wales 2006, Australia
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Sanz-Leon P, Knock SA, Spiegler A, Jirsa VK. Mathematical framework for large-scale brain network modeling in The Virtual Brain. Neuroimage 2015; 111:385-430. [PMID: 25592995 DOI: 10.1016/j.neuroimage.2015.01.002] [Citation(s) in RCA: 157] [Impact Index Per Article: 17.4] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/27/2014] [Revised: 12/29/2014] [Accepted: 01/01/2015] [Indexed: 12/19/2022] Open
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Neural field theory of synaptic metaplasticity with applications to theta burst stimulation. J Theor Biol 2014; 340:164-76. [DOI: 10.1016/j.jtbi.2013.09.021] [Citation(s) in RCA: 19] [Impact Index Per Article: 1.9] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/18/2013] [Revised: 09/12/2013] [Accepted: 09/13/2013] [Indexed: 11/19/2022]
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Wilson MT, Goodwin DP, Brownjohn PW, Shemmell J, Reynolds JNJ. Numerical modelling of plasticity induced by transcranial magnetic stimulation. J Comput Neurosci 2013; 36:499-514. [PMID: 24150916 DOI: 10.1007/s10827-013-0485-1] [Citation(s) in RCA: 13] [Impact Index Per Article: 1.2] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/10/2013] [Revised: 09/09/2013] [Accepted: 10/02/2013] [Indexed: 10/26/2022]
Abstract
We use neural field theory and spike-timing dependent plasticity to make a simple but biophysically reasonable model of long-term plasticity changes in the cortex due to transcranial magnetic stimulation (TMS). We show how common TMS protocols can be captured and studied within existing neural field theory. Specifically, we look at repetitive TMS protocols such as theta burst stimulation and paired-pulse protocols. Continuous repetitive protocols result mostly in depression, but intermittent repetitive protocols in potentiation. A paired pulse protocol results in depression at short ( < ∼ 10 ms) and long ( > ∼ 100 ms) interstimulus intervals, but potentiation for mid-range intervals. The model is sensitive to the choice of neural populations that are driven by the TMS pulses, and to the parameters that describe plasticity, which may aid interpretation of the high variability in existing experimental results. Driving excitatory populations results in greater plasticity changes than driving inhibitory populations. Modelling also shows the merit in optimizing a TMS protocol based on an individual's electroencephalogram. Moreover, the model can be used to make predictions about protocols that may lead to improvements in repetitive TMS outcomes.
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Affiliation(s)
- M T Wilson
- School of Engineering, Faculty of Science and Engineering, University of Waikato, Private Bag 3105, Hamilton, 3240, New Zealand,
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Fung P, Robinson P. Neural field theory of calcium dependent plasticity with applications to transcranial magnetic stimulation. J Theor Biol 2013; 324:72-83. [DOI: 10.1016/j.jtbi.2013.01.013] [Citation(s) in RCA: 16] [Impact Index Per Article: 1.5] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/02/2012] [Revised: 01/17/2013] [Accepted: 01/20/2013] [Indexed: 10/27/2022]
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