An integrated framework for targeting functional networks via transcranial magnetic stimulation

Transcranial magnetic stimulation (TMS) is a powerful investigational tool for in vivo manipulation of regional or network activity, with a growing number of potential clinical applications. Unfortunately, the vast majority of targeting strategies remain limited by their reliance on non-realistic brain models and assumptions that anatomo-functional relationships are 1:1. Here, we present an integrated framework that combines anatomically realistic finite element models of the human head with resting functional MRI to predict functional networks targeted via TMS at a given coil location and orientation. Using data from the Human Connectome Project, we provide an example implementation focused on dorsolateral prefrontal cortex (DLPFC). Three distinct DLPFC stimulation zones were identified, differing with respect to the network to be affected (default, frontoparietal) and sensitivity to coil orientation. Network profiles generated for DLPFC targets previously published for treating depression revealed substantial variability across studies, highlighting a potentially critical technical issue.

[1]  Mark Jenkinson,et al.  The minimal preprocessing pipelines for the Human Connectome Project , 2013, NeuroImage.

[2]  Rainer Goebel,et al.  Optimizing Functional Accuracy of TMS in Cognitive Studies: A Comparison of Methods , 2009, Journal of Cognitive Neuroscience.

[3]  W. Paulus,et al.  Opposite Optimal Current Flow Directions for Induction of Neuroplasticity and Excitation Threshold in the Human Motor Cortex , 2013, Brain Stimulation.

[4]  C. McIntyre,et al.  Tractography-Activation Models Applied to Subcallosal Cingulate Deep Brain Stimulation , 2013, Brain Stimulation.

[5]  Daniela Balslev,et al.  Inter-individual variability in optimal current direction for transcranial magnetic stimulation of the motor cortex , 2007, Journal of Neuroscience Methods.

[6]  S. Rossi,et al.  Evidence-based guidelines on the therapeutic use of repetitive transcranial magnetic stimulation (rTMS) , 2014, Clinical Neurophysiology.

[7]  M. George,et al.  Repetitive transcranial magnetic stimulation of the prefrontal cortex in depression , 2009, Experimental Neurology.

[8]  R. Buckner,et al.  Efficacy of Transcranial Magnetic Stimulation Targets for Depression Is Related to Intrinsic Functional Connectivity with the Subgenual Cingulate , 2012, Biological Psychiatry.

[9]  Alexander Opitz,et al.  Neuroimage: Clinical Validating Computationally Predicted Tms Stimulation Areas Using Direct Electrical Stimulation in Patients with Brain Tumors near Precentral Regions , 2022 .

[10]  Justin K. Rajendra,et al.  Defining Critical White Matter Pathways Mediating Successful Subcallosal Cingulate Deep Brain Stimulation for Treatment-Resistant Depression , 2014, Biological Psychiatry.

[11]  William W. McDonald,et al.  Prefrontal rTMS for treating depression: Location and intensity results from the OPT-TMS multi-site clinical trial , 2013, Brain Stimulation.

[12]  Jack L Lancaster,et al.  Evaluation of an image‐guided, robotically positioned transcranial magnetic stimulation system , 2004, Human brain mapping.

[13]  Timothy Edward John Behrens,et al.  Cerebral Cortex doi:10.1093/cercor/bhm167 Anatomical Connectivity of the Subgenual Cingulate Region Targeted with Deep Brain Stimulation for Treatment-Resistant Depression , 2007 .

[14]  Alexander Opitz,et al.  Electric field calculations in brain stimulation based on finite elements: An optimized processing pipeline for the generation and usage of accurate individual head models , 2013, Human brain mapping.

[15]  Steven J. M. Jones,et al.  Circos: an information aesthetic for comparative genomics. , 2009, Genome research.

[16]  K. Schleifer,et al.  Targeted enhancement of cortical-hippocampal brain networks and associative memory , 2014 .

[17]  A. Dale,et al.  Cortical Surface-Based Analysis II: Inflation, Flattening, and a Surface-Based Coordinate System , 1999, NeuroImage.

[18]  Gereon R. Fink,et al.  Neuronavigation for transcranial magnetic stimulation (TMS): Where we are and where we are going , 2010, Cortex.

[19]  J. Rothwell,et al.  What Makes the Muscle Twitch: Motor System Connectivity and TMS-Induced Activity. , 2015, Cerebral cortex.

[20]  Michael Petrides,et al.  Distinct Parietal and Temporal Connectivity Profiles of Ventrolateral Frontal Areas Involved in Language Production , 2013, The Journal of Neuroscience.

[21]  Akimasa Hirata,et al.  Effects of coil orientation on the electric field induced by TMS over the hand motor area , 2014, Physics in medicine and biology.

[22]  P. Fox,et al.  Column‐based model of electric field excitation of cerebral cortex , 2004, Human brain mapping.

[23]  Alvaro Pascual-Leone,et al.  Identification of reproducible individualized targets for treatment of depression with TMS based on intrinsic connectivity , 2013, NeuroImage.

[24]  T. Paus,et al.  Transcranial magnetic stimulation and the challenge of coil placement: A comparison of conventional and stereotaxic neuronavigational strategies , 2008, Human brain mapping.

[25]  Alexander Opitz,et al.  How the brain tissue shapes the electric field induced by transcranial magnetic stimulation , 2011, NeuroImage.

[26]  Lars Richter,et al.  Optimal Coil Orientation for Transcranial Magnetic Stimulation , 2013, PloS one.

[27]  Simon B. Eickhoff,et al.  Inter-individual variability in cortical excitability and motor network connectivity following multiple blocks of rTMS , 2015, NeuroImage.

[28]  Giulio Ruffini,et al.  The electric field in the cortex during transcranial current stimulation , 2013, NeuroImage.

[29]  Mark S. George,et al.  More Lateral and Anterior Prefrontal Coil Location Is Associated with Better Repetitive Transcranial Magnetic Stimulation Antidepressant Response , 2009, Biological Psychiatry.

[30]  W. Paulus,et al.  Is sham cTBS real cTBS? The effect on EEG dynamics , 2015, Front. Hum. Neurosci..

[31]  Kevin Murphy,et al.  The impact of global signal regression on resting state correlations: Are anti-correlated networks introduced? , 2009, NeuroImage.

[32]  A. Barker,et al.  NON-INVASIVE MAGNETIC STIMULATION OF HUMAN MOTOR CORTEX , 1985, The Lancet.

[33]  R W Cox,et al.  AFNI: software for analysis and visualization of functional magnetic resonance neuroimages. , 1996, Computers and biomedical research, an international journal.

[34]  Stephen M Smith,et al.  Correspondence of the brain's functional architecture during activation and rest , 2009, Proceedings of the National Academy of Sciences.

[35]  Alexander Opitz,et al.  Impact of the gyral geometry on the electric field induced by transcranial magnetic stimulation , 2011, NeuroImage.

[36]  M. Hallett,et al.  Optimal Focal Transcranial Magnetic Activation of the Human Motor Cortex: Effects of Coil Orientation, Shape of the Induced Current Pulse, and Stimulus Intensity , 1992, Journal of clinical neurophysiology : official publication of the American Electroencephalographic Society.

[37]  Peter Stiers,et al.  Unravelling the Intrinsic Functional Organization of the Human Lateral Frontal Cortex: A Parcellation Scheme Based on Resting State fMRI , 2012, The Journal of Neuroscience.

[38]  E. Wassermann,et al.  Transcranial magnetic brain stimulation: therapeutic promises and scientific gaps. , 2012, Pharmacology & therapeutics.

[39]  J. Karhu,et al.  Navigated transcranial magnetic stimulation , 2010, Neurophysiologie Clinique/Clinical Neurophysiology.

[40]  Marisa O. Hollinshead,et al.  The organization of the human cerebral cortex estimated by intrinsic functional connectivity. , 2011, Journal of neurophysiology.

[41]  Alexander Opitz,et al.  Physiological observations validate finite element models for estimating subject-specific electric field distributions induced by transcranial magnetic stimulation of the human motor cortex , 2013, NeuroImage.

[42]  Dick F Stegeman,et al.  The coil orientation dependency of the electric field induced by TMS for M1 and other brain areas , 2015, Journal of NeuroEngineering and Rehabilitation.

[43]  Michael C. Ridding,et al.  Low-intensity, short-interval theta burst stimulation modulates excitatory but not inhibitory motor networks , 2011, Clinical Neurophysiology.

[44]  Steen Moeller,et al.  The Human Connectome Project: A data acquisition perspective , 2012, NeuroImage.

[45]  R. Buckner,et al.  Resting-state networks link invasive and noninvasive brain stimulation across diverse psychiatric and neurological diseases , 2014, Proceedings of the National Academy of Sciences.