Cortical network targets of cerebellar transcranial magnetic stimulation

Abstracts / Brain Stimulation 10 (2017) e21ee45

recent studies have presented the use of transcranial Alternating Current Stimulation (tACS) to enhance working memory processes. This study presents a system that monitors workload via EEG during tACS, which can be used in the future to modulate stimulation parameters based on ongoing measures of working memory performance. EEG measures electrical activity which reflects temporal changes in the electrical state of neurons and represents the current flow, which is directly modulated when applying tACS, making these techniques compliment one-another for closed-loop neuromodulation. Subjects performed nBAck and backwards digit-recall tasks which were repeated both with and without tACS stimulation at 5Hz, 0.5mA in a frontal-parietal montage. A feature matrix of 64 features per 5 second epochs was then extracted from EEG data collected during these tasks after tACS artifact removal and was used to train a machine learning classifier. Upon testing, the classifier was able to successfully separate EEG data during the two tasks both with and without stimulation with a performance of 81.3% and 80.6% for the nBack and digit-recall task respectively. This is the first step towards a close-loop, feedback based tACS-BCI. EEG during tACS can be monitored in real-time to provide an ongoing assessment of workload. The next step is to develop systems which can adjust stimulation parameters such as phase matching tACS with ongoing theta activity and adjusting stimulation amplitude based on workload assessment. Abstract #30 CONNECTIVITY STIMULATION

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Rafael O’Halloran 1, Wahaj Patel 2, Brian Kopell 1, 3. 1 Icahn School of Medicine at Mount Sinai, Dept. of Radiology, USA; 2 City College of the City University of New York, USA; 3 Icahn School of Medicine at Mount Sinai, Dept. of Neurosurgery, USA

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current through the same electrodes to modulate brain activity, both of which are useful in several applications, in particular during mapping for surgical guidance. Advances in manufacturing cortical arrays with high electrode density have opened the possibility of increased flexibility for both higher density recording and enhanced control of stimulation. However little is known about the spatial pattern in which stimulation current injected by these arrays flows through the cortex or how it affects brain activity, nor about how electrode array design and current delivery through the array can be optimized to target / avoid regions of interest. We describe our multi-site, multi-national project in which we combine computational bioelectric finite element modeling (FEM) and sophisticated optimization methods with both human and animal experimentation to study these questions. Since FEM of ECOG stimulation is novel, one key step is model validation against experiments. We will present analysis of data human ECOG array recordings to allow comparison to FEM predictions. In addition our project involves the study of the effect of electrode size and pitch on stimulation focality and depth, and optimization of injected current patterns for control of both targeting and safety. One key goal is to combine results from animal experiments and human studies to guide development of more effective stimulation in the clinic. Abstract #32 EMOTION PERCEPTION IMPROVEMENT FOLLOWING HIGH FREQUENCY TRANSCRANIAL RANDOM NOISE OF THE INFERIOR FRONTAL CORTEX Tegan Penton*1, Laura Dixon 2, Lauren Evans 2, Michael J. Banissy 2. 1 MRC Social, Genetic and Developmental Psychiatry Centre, Institute of Psychiatry, Psychology and Neuroscience, King’s College London, 16 De Crespigny Park, London, SE5 8AF, United Kingdom; 2 Department of Psychology, Goldsmiths, University of London, New Cross, London, SE14 6NW, United Kingdom

Abstract Abstract Deep brain stimulation (DBS) is used to treat a variety of neurological and psychiatric conditions. Previously, the impact of white matter tractography on pre-surgical planning in DBS has been demonstrated, but not widely adopted in clinical practice. Here we discuss challenges and solutions to establishing tractography in clinical practice, using the formalism of structural connectivity. Structural connectivity analysis based on diffusion weighted imaging provides a potentially powerful tool to aide in surgical planning. We demonstrate examples of structural connectivity that is translatable to clinical practice. Abstract #31 MODELING AND OPTIMIZING CORTICAL ELECTRIC STIMULATION Kimia Shayestehfard 1, Moritz Dannhauer 2, 3, Seyhmus Guler 4, Alexis Gkogkidis 5, 6, David Caldwell 7, Jeneva Cronin 7, Tonio Ball 5, 6, Jeffrey G. Ojemann 7, Rob MacLeod 2, 3, Dana H. Brooks 1, 2. 1 B-SPIRAL Group, Department of Electrical and Computer Engineering, Northeastern University, Boston, MA, USA; 2 Center for Integrative Biomedical Computing (CIBC), University of Utah, Salt Lake City, UT, USA; 3 Scientific Computing Institute (SCI), University of Utah, Salt Lake City, UT, USA; 4 Computational Radiology Lab, Boston Children’s Hospital and Harvard Medical School, Boston, MA, USA; 5 Intracranial EEG and Brain Imaging Lab, Epilepsy Center, University Hospital Freiburg, Freiburg, Germany; 6 BrainLinksBrainTools Cluster of Excellence and Bernstein Center Freiburg, University of Freiburg, Freiburg, Germany; 7 Department of Neurological Surgery and the Center for Sensorimotor Neural Engineering, University of Washington, Seattle, WA, USA

Abstract Cortical electrode (ECOG) arrays placed on the brain can be used to both record brain electrical activity from the cerebral cortex with higher spatial resolution in comparison to EEG (electroencephalogram) and to inject

Emotion perception plays a key role in daily life. Indeed, difficulties in emotion perception have negative psychosocial consequences. Techniques that enhance this ability could be therefore be valuable. Recent work has demonstrated the utility of high frequency transcranial random noise stimulation (tRNS) as a tool to improve facial identity perception, but whether tRNS can be used to aid emotion perception remains unknown. We conducted three experiments to examine the effects of tRNS to bilateral inferior frontal cortex (IFC) on emotion perception abilities. In Experiment 1, we investigated the effects of active tRNS relative to sham on facial emotion and identity perception using a between groups design. Participants receiving active tRNS to IFC outperformed those receiving sham stimulation in emotion, but not identity, perception. In Experiment 2, we examined the effects of active tRNS to IFC, active tRNS, to somatosensory cortices (SC), and sham stimulation on emotion and identity perception using a within groups design. We observed that individual variability at baseline was related to performance improvement following IFC stimulation only, with lower performers showing greater improvements following tRNS. In Experiment 3, we examined the effects of tRNS to IFC relative to an occipital control site (V5/MT) on emotion and identity recognition using a mixed design. Performance improvement in emotion discrimination was significantly greater for lower baseline performers following IFC stimulation, replicating Experiment 2. This was not observed for those receiving V5/MT stimulation. These findings demonstrate the potential utility of IFC tRNS as a tool to support emotion perception abilities. Abstract #33 CORTICAL NETWORK TARGETS MAGNETIC STIMULATION

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Moritz Dannhauer 1, 2, Irene Gonsalvez 3, Patrick Horn 3, Rob S. MacLeod 1, 2, Dana H. Brooks 2, 4, Alvaro Pascual-Leone 3, Mark A. Halko 3. 1 Scientific Computing and Imaging Institute (SCI), University of Utah, 72 Central Campus Dr, Salt Lake City, UT, 84112, USA; 2 Center for Integrative Biomedical Computing (CIBC), University of Utah, 72 Central Campus Dr, Salt Lake City, UT, 84112, USA; 3 Center for noninvasive brain

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Abstracts / Brain Stimulation 10 (2017) e21ee45

stimulation, Harvard Medical School, Beth Israel Deaconess Medical Center, Boston, MA, 02215, USA; 4 Electrical and Computer Engineering, Northeastern University, 360 Huntington Avenue, Boston, MA, 02115, USA

humans by utilizing computed patterns of low-amplitude currents delivered to specific brain ROIs. In vivo mECoG measurements of stimulationevoked brain responses will help to guide us to assess the effect of the computed current patterns for improved designs of cortical arrays.

Abstract

Abstract #35 DOMICILIARY TRANSCRANIAL DIRECT CURRENT STIMULATION OVER A TWO YEAR PERIOD FOR TREATMENT-REFRACTORY PSYCHIATRIC AND NEUROLOGICAL CONDITIONS. A THREE CASE REPORT

The cerebellum is well known to contain rich reciprocal connectivity to non-motor regions. Recent imaging has revealed the spatial organization of distinct cortical network targets within the cerebellum. Stimulating non-motor network nodes has been demonstrated, however, only for 2 or 3 TMS stimulation sites. Hence, little is known about optimizing positions of a stimulation coil to achieve specific network stimulation effects. Here, we use a computational approach to predict the location of impact of cerebellar stimulation, and thus which network(s) are impacted by the stimulation. The magnetic field magnitude was evaluated in silico for cerebellar gray and white matter voxels for 150 stimulation sites at the back of the head. Using freely available maps of network organization [Bruckner et al., 2011], we evaluated the field strength from each simulated site at nodes of various networks. Seven cerebellar networks were targeted. The default network is best stimulated from positions lateral to the inion. Other networks show different topologies, for example the dorsal attention networks, which have multiple optimal stimulation sites. By combining the maps together in a winner-takeall approach, we found most, but not all, of the 150 sites stimulate default network nodes in the cerebellum Crus I/II region more strongly than any other network. No stimulation site was found that stimulated the sensorimotor network more strongly than at least one association network. Non-motor regions of the cerebellum may be reachable with transcranial magnetic stimulation. Non-motor sites in the cerebellum are likely targets of cerebellar stimulation. Abstract #34 OPTISTIM e COMBINING COMPUTATIONAL NEUROSCIENCE AND ELECTROPHYSIOLOGY FOR OPTIMAL CORTICAL ELECTRIC STIMULATION Moritz Dannhauer 1, 2, 3, Alexis Gkogkidis 4, 5, Seyhmus Guler 2, 3, Kimia Shayestehfard 2, 3, Rob MacLeod 1, 2, Tonio Ball 4, 5, Jeff Ojemann 6, Dana Brooks 2, 3. 1 Scientific Computing and Imaging Institute (SCI), University of Utah, 72 Central Campus Dr, Salt Lake City, UT, 84112, USA; 2 Center for Integrative Biomedical Computing (CIBC), University of Utah, 72 Central Campus Dr, Salt Lake City, UT, 84112, USA; 3 Electrical and Computer Engineering, Northeastern University, 360 Huntington Avenue, Boston, MA, 02115, USA; 4 Intracranial EEG and Brain Imaging Lab, Epilepsy Center, University Hospital Freiburg, Germany; 5 BrainLinks-BrainTools Cluster of Excellence, University of Freiburg, Germany; 6 Seattle Children’s Hospital, Department of Neurological Surgery, University of Washington, USA

Abstract Electrodes placed on the brain surface are predominantly used to study brain activity with high spatio-temporal resolution, but have recently been utilized to inject electrical currents in order to modulate brain activity for rehabilitation and brain-computer interfaces. However, it is only poorly understood how injected currents interact with brain functionality. Recent advances in manufacturing cortical arrays with a high density of electrodes offers the possibility to simultaneously measure brain activity while injecting currents on a submillimeter scale (micro-electrocorticography, mECoG). Hence, computational modeling has become increasingly interesting to predict and understand current flow pattern for targeting specific brain regions (ROI) using mECoG electrode arrays. Our computational framework allows to maximize the current in the target ROI while current flow in non-target ROIs is restricted and safety-related features can be accounted for, e.g., avoiding local concentrations of electrical current density that may harm brain tissue. The goal of our multi-national (USGerman) collaboration is to apply these models to validate cortical and subcortical indwelled mECoG arrays for a phantom, animals (ovine) and

James Fugedy MD*. The Brain Stimulation Clinic, Atlanta, GA, USA

Abstract The domiciliary use of transcranial direct current stimulation (tDCS) for treatment-resistant neurological and psychiatric disorders in three adult patients for a two year period is described. The first patient was diagnosed with chronic treatment-resistant depression, the second with fibromyalgia and the third with borderline personality disorder, bipolar disorder, selfharm, drug addiction and she was also pregnant. The three patients sought treatment for their conditions utilizing tDCS. Initial evaluation confirmed previous diagnoses, treatments, motivation and competency. Individual training to self-administer tDCS was provided at the clinic, with subsequent training, supervision, evaluation and consultation sessions accomplished via Skype. Protocols were individualized and subsequently modified as a result of the patient response and need for additional treatment as the therapeutic benefits waned with time. All three patients improved with the tDCS treatment. The most important indicators of improvement, as evaluated by the patients themselves, were the ability to function at work, social interaction and quality of life. Proficiency to self-administer was accomplished within the first week. Protocols were accurately followed and modifications were made as a result of doctor-patient collaboration. Side effects were minor, rapidly identified and treated. Domiciliary treatment can be a viable option for those conditions which respond to tDCS. Specific advantages include increased availability, convenience and lower cost. Abstract #36 COMPARISONS BETWEEN IN-VIVO CURRENT DENSITY IMAGES AND COMPUTATIONAL MODELS IN HUMAN TACS RECIPIENTS Aprinda Indahlastari 2, Munish Aditya Kumar Kasinadhuni 1, Chauhan 2, Thomas H. Mareci 3, Rosalind J. Sadleir 2. 1 J. Crayton Pruitt Department of Biomedical Engineering, University of Florida, Gainesville, FL, United States; 2 School of biological and health systems engineering, Arizona State University, Tempe, AZ, United States; 3 Department of Biochemistry and Molecular Biology, University of Florida, Gainesville, FL, United States

Abstract Transcranial alternating current stimulation (TACS) has been observed to produce synchronization effects in cortical rhythms, although its mechanism remains unclear. To date, there has been no direct imaging of current density distributions in humans due to TACS. Instead, many sophisticated computational simulations of TACS and TDCS have been developed to predict current distributions in humans. However, these models cannot be easily validated due to the lack of direct measurement methods. Here we present experimental results from in-vivo current density imaging of humans undergoing TACS at 10 Hz, and compare them to computational predictions derived from the same subjects. Two electrode montages, namely FPz-Oz and T7-T8 were investigated in the study. A total current magnitude of 1.5 mA was applied while the subject was being imaged in an MRI scanner. The main magnetic field component of the magnetic flux density distribution caused by the TACS current (Bz) was recovered using magnetic resonance electrical impedance tomography (MREIT) methods, and reconstructed into a projected current density (PCD) distribution in one slice. Computational models derived from T1-weighted datasets of subjects co-registered to MREIT images were used to simulate TACS