New Review: A technical guide to tDCS

A technical guide to tDCS, and related non-invasive brain stimulation tools

A. J. Woods, A. Antal, M. Bikson, P.S. Boggio, A.R. Brunoni, P. Celnik, L.G. Cohen, D. Fregni, C.S. Herrmann, E.S. Kappenman, H. Knotkova, D. Liebetanz, C. Miniussi, P.C. Miranda, W. Paulus, A. Priori, D. Reato, C. Stagg, N. Wenderoth, M.A. Nitsche.

Clin Neurophysiol. 2016;127(2):1031-48. doi: 10.1016/j.clinph.2015.11.012.

Full paper: A_technical_guide_to_tDCS_Woods_2016

Abstract: Transcranial electrical stimulation (tES), including transcranial direct and alternating current stimulation (tDCS, tACS) are non-invasive brain stimulation techniques increasingly used for modulation of central nervous system excitability in humans. Here we address methodological issues required for tES application. This review covers technical aspects of tES, as well as applications like exploration of brain physiology, modelling approaches, tES in cognitive neurosciences, and interventional approaches. It aims to help the reader to appropriately design and conduct studies involving these brain stimulation techniques, understand limitations and avoid shortcomings, which might hamper the scientific rigor and potential applications in the clinical domain.

Neural Engineering
Special NE seminar: Malcolm Slaney-Understanding and using audio attention

Malcolm Slaney of the Machine Listening Group at Google Research will be discussing the topic of auditory attention. Malcolm is know for his work on automatic speech recognition and auditory perception, among many other things.

When: Friday, January 22nd, at 3pm

Where: ASRC Auditorium

Important: please confirm your attendance by RSVP’ing to neuroccny@gmail.com.  RSVP will facilitate your entry into the ASRC building. Feel free to extend invites to relevant parties.

Title: Understanding and using audio attention

Abstract: Understanding auditory attention is key to many tasks. In this talk I would like to summarize several aspects of attention that we have used to better understand how humans use attention in our daily lives.  This work extends from top-down and bottom-up models of attention useful for solving the cocktail party problem, to the use of eye-gaze and face-pose information to better understand speech in human-machine and human-human-machine interactions, to new techniques that use EEG (and other brain signals) to infer the direction of auditory attention. The common thread throughout all this work is the use of implicit signals such as auditory saliency, face pose and eye gaze as part of a speech-processing system. I will show algorithms and results from speech recognition, speech understanding, addressee detection, and selecting the desired speech from a complicated auditory environment.  This talk will describe work that I did while at Microsoft Research, and efforts at the Telluride Neuromorphic Cognition Engineering Workshop that were partially supported by Google.

Biography: BSEE, MSEE, and Ph.D., Purdue University. Dr. Malcolm Slaney is a research scientist in the Machine Hearing Group at Google Research. He is a Consulting Professor at Stanford CCRMA, where he has led the Hearing Seminar for more than 20 years, and an Affiliate Faculty in the Electrical Engineering Department at the University of Washington. He is a (former) Associate Editor of IEEE Transactions on Audio, Speech and Signal Processing and IEEE Multimedia Magazine. He has given successful tutorials at ICASSP 1996 and 2009 on “Applications of Psychoacoustics to Signal Processing,” on “Multimedia Information Retrieval” at SIGIR and ICASSP, and “Web-Scale Multimedia Data” at ACM Multimedia 2010. He is a coauthor, with A. C. Kak, of the IEEE book Principles of “Computerized Tomographic Imaging”. This book was republished by SIAM in their “Classics in Applied Mathematics” Series. He is coeditor, with Steven Greenberg, of the book “Computational Models of Auditory Function.” Before joining Microsoft Research, Dr. Slaney has worked at Bell Laboratory, Schlumberger Palo Alto Research, Apple Computer, Interval Research, IBM’s Almaden Research Center, Yahoo! Research, and Microsoft Research. For many years, he has lead the auditory group at the Telluride Neuromorphic (Cognition) Workshop. Dr. Slaney’s recent work is on understanding audio perception and decoding auditory attention from brain signals.  He is a Fellow of the IEEE.

Neural Engineering
Dr. Bikson interview on “TechKnow” available

Watch it here: VIDEO

This episode of TechKnow (Original Air Date: September 27, 2014) explores the applications of “hacking the brain.” For patients suffering from a variety of brain injuries and diseases—from depression to cerebral palsy— there is a sure of interest in an technique called transcranial Direct Current Stimulation (tDCS). Dr. Marom Bikson it interviewed as an expert on tDCS technology and its use at home. All features Soterix Medical technology used for neurorehabilitation.

Neural Engineering
New Paper: Home Use of tDCS for Multiple Sclerosis

A Protocol for the Use of Remotely-Supervised Transcranial Direct Current Stimulation (tDCS) in Multiple Sclerosis (MS)

Margaret Kasschau 1,2, Kathleen Sherman1,2, Lamia Haider 2, Ariana Frontario 1,2, Michael Shaw1,2, Abhishek Datta 3, Marom Bikson 4, Leigh Charvet1,2

1 Multiple Sclerosis Comprehensive Care Center, Department of Neurology, NYU Langone Medical Center, 2 Department of Neurology, Stony Brook Medicine, 3 Soterix Medical, Inc, 4 Department of Biomedical Engineering, The City College of New York

Watch the video here

Soterix Medical Mini-CT device used here 

Neural Engineering
Special NE Seminar: José del R. Millán, Brain-Machine Interfaces: Dec 18

Neural Engineering Journal Club/Speaker Friday (Dec 18th) at 1 PM. Location is the new CCNY building, 3rd floor conference room Directions here

Brain-Machine Interfaces: The Perception-Action Closed Loop

Dr. José del R. Millán

http://actu.epfl.ch/news/neuroprotheses-l-esprit-aux-commandes/

Future neuroprosthetics will be tightly coupled with the user in such a way that the resulting system can replace and restore impaired upper limb functions because controlled by the same neural signals than their natural counterparts. However, robust and natural interaction of subjects with sophisticated prostheses over long periods of time remains a major challenge. To tackle this challenge we can get inspiration from natural motor control, where goal-directed behavior is dynamically modulated by perceptual feedback resulting from executed actions.

Current brain-computer interfaces (BCI) partly emulate human motor control as they decode cortical correlates of movement parameters –from onset of a movement to directions to instantaneous velocity– in order to generate the sequence of movements for the neuroprosthesis. A closer look, though, shows that motor control results from the combined activity of the cerebral cortex, subcortical areas and spinal cord. This hierarchical organization supports the hypothesis that complex behaviours can be controlled using the low-dimensional output of a BCI in conjunction with intelligent devices in charge to perform low-level commands.

A further component that will facilitate intuitive and natural control of motor neuroprosthetics is the incorporation of rich multimodal feedback and neural correlates of perceptual processes resulting from this feedback. As in natural motor control, these sources of information can dynamically modulate interaction.

Bio: José del R. Millán is the Defitech Professor at the Ecole Polytechnique Fédérale de Lausanne (EPFL) where he explores the use of brain signals for multimodal interaction and, in particular, the development of non-invasive brain-controlled robots and neuroprostheses. In this multidisciplinary research effort, Dr. Millán is bringing together his pioneering work on the two fields of brain-machine interfaces and adaptive intelligent robotics. He received his Ph.D. in computer science from the Univ. Politècnica de Catalunya (Barcelona, Spain) in 1992. His research on brain-machine interfaces was nominated finalist of the European Descartes Prize 2001 and he has been named Research Leader 2004 by the journal Scientific American for his work on brain-controlled robots. He is the recipient of the IEEE-SMC Nobert Wiener Award 2011 for his seminal and pioneering contributions to non-invasive brain-machine interfaces. Dr. Millán has coordinated a number of European projects on brain-machine interfaces.

Neural Engineering
Bikson speaks at North American Neuromodulation, Dec 11

UPDATE: Slides from talk Bikson_NAN2015final

Dr. Bikson to speak at the NANS 2015 meeting as part of a special session on NIBS.

Meeting details here  Meeting is Dec 10-13 in Las Vegas.

Chair: Felipe Fregni

-Tim Wagner, PhD//Laura Dipietro, PhD

-Leon Morales, MD

-Marom Bikson, PhD

-Dylan Edwards, PhD

Dec 11: Non-Invasive Brain Neurostimulation

-from biophysical foundations to clinical implementation of neurostimulation technologies

-Using qEEG to guide non-invasive brain stimulation

-High-density transcranial direct current stimulation

-Using robotics and other therapies in combination with brain stimulation

Neural Engineering
Dr.Bikson quoted in New Scientist

Link Nov 18, 2015

Marom Bikson, a biomedical engineer at the City College of New York, who studies electricity’s effect on the body, says there are some essential questions scientists must answer before tDCS becomes widespread: what brain region should be stimulated and at what strength; and is stimulation better before, during or after an activity? “We’re in the ‘baby aspirin’ stages of tDCS,” says Bikson. “We have a tremendous amount to learn about how to optimize it.”

Neural Engineering
New Paper: tSDCS

J Neurophysiol. 2015 Apr 1;113(7):2801-11. doi: 10.1152/jn.00784.2014. Epub 2015 Feb 11.
Transspinal direct current stimulation immediately modifies motor cortex sensorimotor maps.
Song W, Truong DQ, Bikson M, Martin JH.

Full PDF: SongBiksontsDCS_2015
Abstract: Motor cortex (MCX) motor representation reorganization occurs after injury, learning, and different long-term stimulation paradigms. The neuromodulatory approach of transspinal direct current stimulation (tsDCS) has been used to promote evoked cortical motor responses. In the present study, we used cathodal tsDCS (c-tsDCS) of the rat cervical cord to determine if spinal cord activation can modify the MCX forelimb motor map. We used a finite-element method model based on coregistered high-resolution rat MRI and microcomputed tomography imaging data to predict spinal current density to target stimulation to the caudal cervical enlargement. We examined the effects of cathodal and anodal tsDCS on the H-reflex and c-tsDCS on responses evoked by intracortical microstimulation (ICMS). To determine if cervical c-tsDCS also modified MCX somatic sensory processing, we examined sensory evoked potentials (SEPs) produced by wrist electrical stimulation and induced changes in ongoing activity. Cervical c-tsDCS enhanced the H-reflex, and anodal depressed the H-reflex. Using cathodal stimulation to examine cortical effects, we found that cervical c-tsDCS immediately modified the forelimb MCX motor map, with decreased thresholds and an expanded area. c-tsDCS also increased SEP amplitude in the MCX. The magnitude of changes produced by c-tsDCS were greater on the motor than sensory response. Cervical c-tsDCS more strongly enhanced forelimb than hindlimb motor representation and had no effect on vibrissal representation. The finite-element model indicated current density localized to caudal cervical segments, informing forelimb motor selectivity. Our results suggest that c-tsDCS augments spinal excitability in a spatially selective manner and may improve voluntary motor function through MCX representational plasticity.

Neural Engineering
Dr. Bikson to speak at NJIT on Nov 6

Friday, November 6, 2015. 11:30 AM at New Jersey Institute of Technology  link

Talk title: The engineering foundations of non-invasive brain stimulation with weak currents

Few modern investigational medical devices have generated the excitement and research activity associated with transcranial Direct Current Stimulation (tDCS). During tDCS low-intensity DC current is applied across the scalp to treat neuropsychiatric diseases (including pain, depression, TBI, PTSD, epilepsy, tinnitus, stroke rehabilitation) or enhance cognitive performancetraining efficacy (including accelerated learning and memory); moreover tDCS has been suggested to produce minimal side-effects (undesired cognitive changes). This broad use of tDCS itself begs the question: how is specificity of behavioral changes achieved? And more broadly: how does tDCS work at the cellular level. This presentation introduces the current state-of-the-art and in-development technologies of tDCS. The biophysical foundations of tDCS are outlined including MRI-derived computational models of current flow, simulations and animal studies of neuromodulation, and finally essential challenges for ongoing rational and optimized application of tDCS in clinical and cognitive enhancements applications.

ity associated with transcranial Direct Current Stimulation (tDCS). During tDCS low-intensity DC current is applied across the scalp to treat neuropsychiatric diseases (including pain, depression, TBI, PTSD, epilepsy, tinnitus, stroke rehabilitation) or enhance cognitive performancetraining efficacy (including accelerated learning and memory); moreover tDCS has been suggested to produce minimal side-effects (undesired cognitive changes). This broad use of tDCS itself begs the question: how is specificity of behavioral changes achieved? And more broadly: how does tDCS work at the cellular level. This presentation introduces the current state-of-the-art and in-development technologies of tDCS. The biophysical foundations of tDCS are outlined including MRI-derived computational models of current flow, simulations and animal studies of neuromodulation, and finally essential challenges for ongoing rational and optimized application of tDCS in clinical and cognitive enhancements applications.

Neural Engineering
Two new papers on Forward Modeling Methods

Both papers appear in a special issue of Progress in Brain Research.

Modeling sequence and quasi-uniform assumption in computational neurostimulation

Bikson M, Truong DQ, Mourdoukoutas A,  Aboseria M, Khadka N, Adair D, Rahman A

DOI: doi:10.1016/bs.pbr.2015.08.005 Journal Link  PDF: ModelingSequence2015

Abstract: Computational neurostimulation aims to develop mathematical constructs that link the application of neuromodulation with changes in behavior and cognition. This process is critical but daunting for technical challenges and scientific unknowns. The overarching goal of this review is to address how this complex task can be made tractable. We describe a framework of sequential modeling steps to achieve this: (1) current flow models, (2) cell polarization models, (3) network and information processing models, and (4) models of the neuroscientific correlates of behavior. Each step is explained with a specific emphasis on the assumptions underpinning underlying sequential implementation. We explain the further implementation of the quasi-uniform assumption to overcome technical limitations and unknowns. We specifically focus on examples in electrical stimulation, such as transcranial direct current stimulation. Our approach and conclusions are broadly applied to immediate and ongoing efforts to deploy computational neurostimulation.

 

Multilevel computational models for predicting the cellular effects of noninvasive brain stimulation

DOI: doi:10.1016/bs.pbr.2015.09.003  Journal Link  PDF: MultiLevelComputational

Rahman A, Lafon B, Bikson M

Abstract: Since 2000, there has been rapid acceleration in the use of tDCS in both clinical and cognitive neuroscience research, encouraged by the simplicity of the technique (two electrodes and a battery powered stimulator) and the perception that tDCS protocols can be simply designed by placing the anode over the cortex to “excite,” and the cathode over cortex to “inhibit.” A specific and predictive understanding of tDCS needs experimental data to be placed into a quantitative framework. Biologically constrained computational models provide a useful framework within which to interpret results from empirical studies and generate novel, testable hypotheses. Although not without caveats, computational models provide a tool for exploring cognitive and brain processes, are amenable to quantitative analysis, and can inspire novel empirical work that might be difficult to intuit simply by examining experimental results. We approach modeling the effects of tDCS on neurons from multiple levels: modeling the electric field distribution, modeling single-compartment effects, and finally with multicompartment neuron models.

Neural Engineering
SmarthHealth features Dr. Bikson

SmartHealth interviews Marom Bikson on Oct 21, 2015

Read the full interview here

“Which kind of diseases could be improved thanks to electrical stimulation of the brain?

Almost any brain disease can benefit in theory from electrical stimulation.  Electrical stimulation may not always be a cure, but it can enhance the effects of other therapies and increase quality of life.  Applications include depression, chronic pain, epilepsy, learning and attention disorders, and other neuro-psychiatric disorders.”

Neural Engineering
An Overview on Using Simpleware to Simulate and 3D Print Organs

Computer Aided Design of the Body:
An Overview on Using Simpleware to Simulate and 3D Print Organs Date: Friday, October 16, 2015
Venue: City College of New York, Steinman Hall Room 401, 160 Convent Ave, New York, NY 10031 [Directions]

Who should attend:
This one-day course is aimed at those interested in creating high-quality 3D printed models of human anatomy from 3D image data. It will provide an overview to the processing of medical imaging data for the creation of tissue simulations and 3D printing. We will demonstrate typical workflows in Simpleware software for going from 3D image data to STL files suitable for 3D printing, including the ability to visualise and segment complex anatomical data. This will cover the benefits of using image-based models, examples of the work being done at CCNY, and will include opportunities for hands-on demos.You will learn how to:

You will learn how to:

1. Visualise and process image data from a wide range of 3D imaging modalities (e.g. MRI, CT, micro-CT)

2. Create and manipulate computer representations of different parts of the human anatomy

3. Import and position medical device designs within image data

4. Generate image and video files for presentations and demonstration

5. Export to 3D printing equipment

6. Export for the purpose of computer simulation using finite element methods

 

Organizers:

  1. Neuromodec

  2. Bhaskar Paneri

  3. Marom Bikson PhD

  4. Gozde Unal

 

Registration Today:
$50 ($25 Students)

Neural Engineering
Dr. Bikson to speak at UCLA On Dec 10, 2015

UCLA Brain Mapping Center

December 10, 2015 1:00pm – 2:00pm
Neuroscience Research Building (NRB 132) 635 Charles Young Dr. South

link

“How does tDCS work for so many things?” Marom Bikson

Few neuroscience technologies have generated as much recent interest and debate as transcranial Direct Current Stimulation (tDCS). tDCS is explored for a remarkably wide range of behavioral interventions to treat neurological and psychiatric disorders, to accelerate rehabilitation after injury, and to enhance learning in healthy subjects. This talk reviews the technical and mechanism fundamentals of tDCS with the goal of explaining how specificity of action can be achieved. Specifically, how can tDCS be optimized and customized to produce specific changes in brain function. Data from computational models, animal testing, and clinical trials of tDCS is reviewed. New technologies such as High-Definition tDCS and EEG-tDCS coupling will be discussed.

Neural Engineering