DOCSLIB.ORG

Intracortical Microstimulation Modulates Cortical Induced Responses

Total Page：16

File Type：pdf, Size：1020Kb

Download full-text PDF Read full-text
Intracortical Microstimulation Modulates Cortical Induced Responses 7774 • The Journal of Neuroscience, September 5, 2018 • 38(36):7774–7786 Systems/Circuits Intracortical Microstimulation Modulates Cortical Induced Responses Mathias Benjamin Voigt,1,2 XPrasandhya Astagiri Yusuf,1,2,3 and XAndrej Kral1,2 1Institute of AudioNeuroTechnology and Department of Experimental Otology, Hannover Medical School, 30625 Hannover, Germany, 2Cluster of Excellence “Hearing4all”, 30625 Hannover, Germany, and 3Department of Medical Physics/Medical Technology Cluster IMERI, Faculty of Medicine Universitas Indonesia, 10430 Jakarta, Indonesia Recentadvancesincorticalprostheticsreliedonintracorticalmicrostimulation(ICMS)toactivatethecorticalneuralnetworkandconvey information to the brain. Here we show that activity elicited by low-current ICMS modulates induced cortical responses to a sensory stimulus in the primary auditory cortex (A1). A1 processes sensory stimuli in a stereotyped manner, encompassing two types of activity: evoked activity (phase-locked to the stimulus) and induced activity (non-phase-locked to the stimulus). Time-frequency analyses of extracellular potentials recorded from all layers and the surface of the auditory cortex of anesthetized guinea pigs of both sexes showed that ICMS during the processing of a transient acoustic stimulus differentially affected the evoked and induced response. Specifically, ICMS enhanced the long-latency-induced component, mimicking physiological gain increasing top-down feedback processes. Further- more, the phase of the local field potential at the time of stimulation was predictive of the response amplitude for acoustic stimulation, ICMS, as well as combined acoustic and electric stimulation. Together, this was interpreted as a sign that the response to electrical stimulation was integrated into the ongoing cortical processes in contrast to substituting them. Consequently, ICMS modulated the cortical response to a sensory stimulus. We propose such targeted modulation of cortical activity (as opposed to a stimulation that substitutes the ongoing processes) as an alternative approach for cortical prostheses. Key words: auditory cortex; cortical implant; hearing; neuroprosthetic; oscillation Significance Statement Intracortical microstimulation (ICMS) is commonly used to activate a specific subset of cortical neurons, without taking into account the ongoing activity at the time of stimulation. Here, we found that a low-current ICMS pulse modulated the way the auditory cortex processed a peripheral stimulus, by supra-additively combining the response to the ICMS with the cortical processing of the peripheral stimulus. This artificial modulation mimicked natural modulations of response magnitude such as attention or expectation. In contrast to what was implied in earlier studies, this shows that the response to electrical stimulation is not substituting ongoing cortical activity but is integrated into the natural processes. Introduction evoking action potentials in neurons close to the stimulation Intracortical microstimulation (ICMS) is widely used in neuro- electrode (Tehovnik, 1996; Clark et al., 2011; Histed et al., 2013). science to identify a causal connection between cortical neuronal In addition to basic neuroscientific research, this method has activity and a specific brain function (Cicmil and Krug, 2015). Its been used for the development of invasive neural prostheses main use is the activation of a subset of the cortical network by (Schwartz, 2004; Lebedev, 2016; Lebedev and Nicolelis, 2017). Most progress in the development of implantable cortical pros- Received April 11, 2018; revised June 19, 2018; accepted July 6, 2018. theses for humans has been achieved in the somatosensory and Author contributions: M.B.V. wrote the first draft of the paper; M.B.V., P.A.Y., and A.K. edited the paper. M.B.V. motor systems of tetraplegic patients (Aflalo et al., 2015; Flesher and A.K. designed research; M.B.V. performed research; M.B.V. and P.A.Y. analyzed data. et al., 2016; Pandarinath et al., 2017). ThisworkwassupportedbytheGermanResearchFoundation,ClusterofExcellence“Hearing4all”(EXC1077).We thank Karl-Ju¨rgen Ku¨hne and Daniela Ku¨hne for support during the experiments and Dr. Peter Hubka for extensive In neural prostheses ICMS is used to evoke a specific function discussion of the data presented herein. of the brain (e.g., elicit a percept or affect a muscle) by activating The authors declare no competing financial interests. a neuronal population that is providing this particular function. Correspondence should be addressed to Mathias B. Voigt, Institute of AudioNeuroTechnology, OE 8891, Han- In theory, activating the responsible network “naturally”, i.e., nover Medical School, Stadtfelddamm 34, 30625 Hannover, Germany. E-mail: [email protected]. DOI:10.1523/JNEUROSCI.0928-18.2018 comparable with physiological activation, would provide optimal Copyright © 2018 the authors 0270-6474/18/387774-13$15.00/0 control of the targeted cortical processing. One precondition to Voigt et al. • ICMS Modulates Induced Responses J. Neurosci., September 5, 2018 • 38(36):7774–7786 • 7775 Figure 1. Methodology. A, Photograph showing the exposed cortex and the recording electrode arrangement. The double shank recording/stimulation electrode array was inserted through a hole in the substrate of the rectangular 16-channel surface electrode array placed on A1. PSS, Pseudo-sylvian sulcus. B, Recording/stimulation channel parameters. The first 16 channels (Shank 1) of the depth electrode array could be connected to a dedicated current source. Cortical layers have been assigned to single electrodes according to literature (Wallace and Palmer, 2008) and current sourcedensityprofiles(Voigtetal.,2017).C,Schematicofthestimuluscombinationused.Auditory(condensationclick,50␮s,40dBaboveABRhearingthreshold)andelectricstimuli(biphasic,200 ␮s/phase, cathodic-leading, ϳ3 ␮A) have been presented either alone or in combination. In combined conditions the auditory stimulus was always leading the electric stimulus with a delay (⌬t) of 5, 15, or 25 ms of the electric stimulus. allow physiological-like activation is that the response to ICMS is The two response components, the evoked and induced re- integrated into ongoing cortical processing. Although the influ- sponse, are usually interpreted as corresponding to two stages ence of the network state (Buonomano and Maass, 2009)on of processing. The evoked component reflects the thalamo- cortical processing has been a well-known fact (Arieli et al., 1996; cortically conveyed bottom-up processes, whereas the induced Henry and Obleser, 2012), internal cortical processing at the mo- responses result from interaction of such thalamo-cortical inputs ment of stimulus presentation received insufficient attention. with weaker corticocortical inputs (Poort et al., 2012; Klink et al., Only recently, discussions on adapting neuroprosthetical stimu- 2017). Functionally, the induced response component likely rep- lation to ongoing cortical processes have been initiated (Panzeri resents top-down feedback processes linking external stimuli to et al., 2016). As examples of the effectiveness of such an approach, an internal cortical model of the environment, i.e., combining the effect size of transcranial magnetic stimulation increased externally driven sensory input with internally generated predic- when stimulation was confined to a specific EEG phase (Zrenner tions (Engel et al., 2001; Chen et al., 2012; Morillon et al., 2015). et al., 2018) and using the internal cortical state as an additional Low-current ICMS alone, at a current level sufficient to gen- prediction variable increased information yield from recorded erate significant local neuronal activity (Voigt et al., 2017), neuronal activity (De Feo et al., 2017), an important bottle-neck showed an evoked component, but no induced component. Add- in brain–computer interfaces (Baranauskas, 2014; Tehovnik and ing ICMS to an acoustic stimulation differentially affected oscil- Chen, 2015; Panzeri et al., 2016). latory responses: the induced responses were supra-additively Here we show that ICMS can lead to a neuronal response that amplified, whereas the evoked responses were reduced. A phase- becomes integrated into ongoing processes similar to an acoustic based response variability analysis revealed an influence of the stimulus, in contrast to substituting the physiological activity prestimulus network state on the response amplitude similarly in with artificially generated activity. We recorded activity from the ICMS and acoustic stimulation. Consequently, low-current in- surface and the depth of the primary auditory cortex (A1; Fig. 1A) tracortical microstimulation can be physiologically integrated of guinea pigs during acoustic stimulation, ICMS, and a combi- into the cortical processing and modulate cortical responses. nation of both (Fig. 1B,C). Oscillatory activity documented the expected response of A1 to transient acoustic stimuli, consisting Materials and Methods of two types of activity: an early phase-locked (“evoked”) re- Animals and preparation. Data from nine Dunkin Hartley guinea pigs sponse and a late non-phase-locked (“induced”) response. This (Crl:HA; Charles River Laboratories; 7 male, 2 female) weighing 350– has been previously described in the auditory cortex of rodents 440 g were used. Data of one additional animal (male, 500 g) were ex- (Delano et al., 2008), cats (Yusuf et al., 2017), nonhuman pri- cluded from analysis, because recordings included a secondary auditory mates
Load more

Recommended publications
  • Challenges in the Design of Large-Scale, High-Density, Wireless Stimulation and Recording Interface
    Challenges in the Design of Large-Scale, High-Density, Wireless Stimulation and Recording Interface Po-Min Wang, Stanislav Culaclii, Kyung Jin Seo, Yushan Wang, Hui Fang, Yi-Kai Lo, and Wentai Liu 1 Introduction Neural stimulation and recording have been widely applied to fundamental research to better understand the nervous systems as well as to the clinical therapy of a variety of diseases. Well-known examples include monitoring and manipulating neural activities in the brain to map the brain function [1–3], spinal cord implant to restore the motor function after spinal cord injury [4–6], gastrointestinal (GI) implant to monitor and treat GI motility disorders [7–9], and retinal prostheses to regain eyesight in the blind [10–12]. These applications require continuous techno- logical advancement in designs of stimulation and recording electronics, electrodes, and the interconnections between the electronics and the electrodes. Despite technological advances to date, there are still challenges to overcome in applications requiring large-scale, high-density, wireless stimulation and recording. Concretely, the study of the brain function through monitoring and manipulating neural activities in freely moving and behaving subjects requires decoding the com- plex brain dynamics by mapping brain activity with both large-scale and high spa- tial resolution. This decoding demands a large-scale, high-density electrode array with small electrode size, which imposes significant challenges in electrode array fabrication as well as its interconnect with electronics. In addition, the capability to record high channel number implies the need for wireless electronics with high P.-M. Wang · S. Culaclii · Y. Wang · W. Liu (*) Department of Bioengineering, University of California, Los Angeles, Los Angeles, CA, USA e-mail: [email protected] K.
    [Show full text]
  • Upper Extremity Rehabilitation
    Stroke Rehabilitation Clinician Handbook 2020 4. Hemiplegic Upper Extremity Rehabilitation Robert Teasell MD, Norhayati Hussein MD, Magdalena Mirkowski MSc, MScOT, Danielle Vanderlaan RRT, Marcus Saikaley HBSc, Mitchell Longval BSc, Jerome Iruthayarajah MSc Table of Contents 4.3.16 Repetitive Transcranial Magnetic 4.1 Recovery for Upper Extremity ............ 2 Stimulation (rTMS) ....................................... 33 4.1.1 Brunnstrom Stages of Motor Recovery 2 4.3.17 Transcranial Direct Current Stimulation 4.1.2 Typical Recovery and Predictors ........... 2 (tDCS) ........................................................... 35 4.1.3 Recovery of Upper Extremity: Fixed 4.3.18 Telerehabilitation ............................. 36 Proportion ...................................................... 3 4.3.19 Orthosis in Hemiparetic Upper 4.2 Evaluation of Upper Extremity ........... 4 Extremity...................................................... 37 4.3.20 Robotics in Rehabilitation of Upper 4.2.1 Upper Extremity Asessement and Extremity Post-Stroke .................................. 38 Outcome Measures ........................................ 4 4.3.21 Virtual Reality ................................... 41 4.2.2 Motor Function ..................................... 5 4.3.22 Antidepressants and Upper Extremity 4.2.3 Dexterity................................................ 7 Function ....................................................... 42 4.2.4 ADLs ...................................................... 7 4.3.23 Peptides ...........................................
    [Show full text]
  • Electronic Approaches to Restoration of Sight
    Home Search Collections Journals About Contact us My IOPscience Electronic approaches to restoration of sight This content has been downloaded from IOPscience. Please scroll down to see the full text. 2016 Rep. Prog. Phys. 79 096701 (http://iopscience.iop.org/0034-4885/79/9/096701) View the table of contents for this issue, or go to the journal homepage for more Download details: IP Address: 171.64.108.170 This content was downloaded on 09/08/2016 at 17:30 Please note that terms and conditions apply. IOP Reports on Progress in Physics Reports on Progress in Physics Rep. Prog. Phys. Rep. Prog. Phys. 79 (2016) 096701 (29pp) doi:10.1088/0034-4885/79/9/096701 79 Review 2016 Electronic approaches to restoration of sight © 2016 IOP Publishing Ltd G A Goetz1,2 and D V Palanker1,3 RPPHAG 1 Hansen Experimental Physics Laboratory, Stanford University, Stanford, CA 94305, USA 2 Neurosurgery, Stanford University, Stanford, CA 94305, USA 096701 3 Ophthalmology, Stanford University, Stanford, CA 94305, USA E-mail: [email protected] and [email protected] G A Goetz and D V Palanker Received 11 November 2014, revised 11 April 2016 Accepted for publication 23 May 2016 Electronic approaches to restoration of sight Published 9 August 2016 Abstract Printed in the UK Retinal prostheses are a promising means for restoring sight to patients blinded by the gradual atrophy of photoreceptors due to retinal degeneration. They are designed to reintroduce ROP information into the visual system by electrically stimulating surviving neurons in the retina. This review outlines the concepts and technologies behind two major approaches to retinal prosthetics: epiretinal and subretinal.
    [Show full text]
  • Cortical Responses to Vagus Nerve Stimulation Are Modulated by Brain State in Nonhuman Primates Irene Rembado1, Weiguo Song2, David K
    Cerebral Cortex, 2021;00: 1–19 https://doi.org/10.1093/cercor/bhab158 Original Article ORIGINAL ARTICLE Downloaded from https://academic.oup.com/cercor/advance-article/doi/10.1093/cercor/bhab158/6306501 by guest on 06 July 2021 Cortical Responses to Vagus Nerve Stimulation Are Modulated by Brain State in Nonhuman Primates Irene Rembado1, Weiguo Song2, David K. Su3, Ariel Levari4, Larry E. Shupe4, Steve Perlmutter4, Eberhard Fetz4 and Stavros Zanos2 1MindScope Program, Allen Institute, 615 Westlake Ave N., Seattle, WA 98103, USA, 2Institute of Bioelectronic Medicine, Feinstein Institutes for Medical Research, Manhasset NY 11030, USA, 3Providence Regional Medical Center Cranial Joint and Spine Clinic, Everett, WA 98201, USA and 4Department of Physiology & Biophysics, University of Washington, Seattle, WA 98195, USA Address correspondence to Irene Rembado, MindScope Program at the Allen Institute, 615 Westlake Ave N., Seattle, WA 98103, USA. Email: [email protected]; Stavros Zanos, Institute of Bioelectronic Medicine, Feinstein Institutes for Medical Research, 350 Community Drive, Manhasset NY 11030, USA. Email: [email protected] Abstract Vagus nerve stimulation (VNS) has been tested as therapy for several brain disorders and as a means to modulate cortical excitability and brain plasticity. Cortical effects of VNS, manifesting as vagal-evoked potentials (VEPs), are thought to arise from activation of ascending cholinergic and noradrenergic systems. However, it is unknown whether those effects are modulated by brain state at the time of stimulation. In 2 freely behaving macaque monkeys, we delivered short trains of 5 pulses to the left cervical vagus nerve at different frequencies (5-300 Hz) while recording local field potentials (LFPs) from sites in contralateral prefrontal, sensorimotor and parietal cortical areas.
    [Show full text]
  • Revolutionizing Prosthetics—Phase 3
    Revolutionizing Prosthetics—Phase 3 Alan D. Ravitz, Michael P. McLoughlin, James D. Beaty, Francesco V. Tenore, Matthew S. Johannes, Scott A. Swetz, John B. Helder, Kapil D. Katyal, Matthew P. Para, Kenneth M. Fischer, Timothy C. Gion, and Brock A. Wester n early 2006, APL was awarded a contract to start the first phase of the Revolutionizing Prosthetics 2009 program, a multiyear, multimillion-dollar effort to develop an advanced upper-extremity prosthetic limb, the Modular Prosthetic Limb (MPL). This program’s goal is to develop an advanced limb that would allow a prosthetic wearer to button a shirt, tune a radio, and feel the warmth of a loved one’s hand; such a limb might even provide the warfighter with the opportunity to return to active duty. Currently in the third phase of Revolutionizing Prosthetics, APL is leading the Defense Advanced Research Projects Agency’s effort to provide upper- extremity functionality to people who have no ability to control their native arms, such as amputees and those with high spinal cord injury or neurodegenerative diseases such as amyotrophic lateral sclerosis. Phase 3 of the program involves significant focus on clinical activities including maturing the MPL’s robustness, submitting regulatory filings, designing and executing preclinical and clinical activities, and advancing cortical implant technology. Initial clinical activities during this third year of Phase 3 have involved a sub- ject with tetraplegia using a brain computer interface to control the MPL. Further trials with this subject continue as the program team prepares for four additional subjects during Phase 3. INTRODUCTION Throughout history, the battlefield loss of limbs and/ injuries resulting from recent military operations, in or motor function has been the major driving force for addition to individuals in the general public with simi- technological progress in the field of prosthetics.
    [Show full text]
  • A Neural Interface for a Cortical Vision Prosthesis
    View metadata, citation and similar papers at core.ac.uk brought to you by CORE provided by Elsevier - Publisher Connector Vision Research 39 (1999) 2577–2587 A neural interface for a cortical vision prosthesis Richard A. Normann *, Edwin M. Maynard, Patrick J. Rousche, David J. Warren Department of Bioengineering, Uni6ersity of Utah, 2840 Merrill Engineering Building, Salt Lake City, UT 84112, USA Received 11 August 1998; received in revised form 7 December 1998 Abstract The development of a cortically based vision prosthesis has been hampered by a lack of basic experiments on phosphene psychophysics. This basic research has been hampered by the lack of a means to safely stimulate large numbers of cortical neurons. Recently, a number of laboratories have developed arrays of silicon microelectrodes that could enable such basic studies on phosphene psychophysics. This paper describes one such array, the Utah electrode array, and summarizes neurosurgical, physiological and histological experiments that suggest that such an array could be implanted safely in visual cortex. We also summarize a series of chronic behavioral experiments that show that modest levels of electrical currents passed into cortex via this array can evoke sensory percepts. Pending the successful outcome of biocompatibility studies using such arrays, high count arrays of penetrating microelectrodes similar to this design could provide a useful tool for studies of the psychophysics of phosphene perception in human volunteers. Such studies could provide a proof-of-concept for cortically based artificial vision. © 1999 Published by Elsevier Science Ltd. All rights reserved. Keywords: Neuroprosthetics; Artificial vision; Electrode arrays; Multielectrode recordings; Biocompatibility 1. Introduction with an array of electrodes implanted subdurally over its surface.
    [Show full text]
  • Mechanically Adaptive Intracortical Implants Improve the Proximity of Neuronal Cell Bodies
    Home Search Collections Journals About Contact us My IOPscience Mechanically adaptive intracortical implants improve the proximity of neuronal cell bodies This content has been downloaded from IOPscience. Please scroll down to see the full text. 2011 J. Neural Eng. 8 066011 (http://iopscience.iop.org/1741-2552/8/6/066011) View the table of contents for this issue, or go to the journal homepage for more Download details: IP Address: 137.99.31.134 This content was downloaded on 22/05/2015 at 14:26 Please note that terms and conditions apply. IOP PUBLISHING JOURNAL OF NEURAL ENGINEERING J. Neural Eng. 8 (2011) 066011 (13pp) doi:10.1088/1741-2560/8/6/066011 Mechanically adaptive intracortical implants improve the proximity of neuronal cell bodies J P Harris1,2, J R Capadona1,2, R H Miller3,BCHealy4,5, K Shanmuganathan6, S J Rowan1,2,6, C Weder6,7 and D J Tyler1,2,8 1 Department of Biomedical Engineering, CWRU, 2071 Martin Luther King Jr Drive, Wickenden Bldg, Cleveland, OH 44106, USA 2 Rehabilitation Research and Development, L Stokes Cleveland VA Medical Center, 10701 East Blvd Mail Stop 151 AW/APT, Cleveland, OH 44106-1702, USA 3 Department of Neurosciences, CWRU, 2109 Adelbert Road, Cleveland, OH 44106, USA 4 Department of Neurology, Brigham and Women’s Hospital, Partners MS Center, Harvard Medical School, 1 Brookline Place West, Suite 225, Boston, MA 02445, USA 5 Biostatistics Center, Massachusetts General Hospital, 50 Staniford St Suite 560, Boston, MA 02114, USA 6 Department of Macromolecular Science and Engineering, 2100 Adelbert Road, Kent Hale Smith Bldg, CWRU, Cleveland, OH 44106, USA 7 Adolphe Merkle Institute and Fribourg Center for Nanomaterials, University of Fribourg, Rte de l’Ancienne Papeterie/PO Box 209, CH-1723 Marly 1, Switzerland E-mail: [email protected] Received 6 March 2011 Accepted for publication 27 September 2011 Published 2 November 2011 Online at stacks.iop.org/JNE/8/066011 Abstract The hypothesis is that the mechanical mismatch between brain tissue and microelectrodes influences the inflammatory response.
    [Show full text]
  • "Visual Prostheses"
    530 VISUAL PROSTHESES VISUAL PROSTHESES JEAN DELBEKE CLAUDE VERAART Catholic University of Louvain Brussels, Belgium INTRODUCTION Minute electrical stimuli delivered to the retina, the optic nerve, or the occipital cortex can induce light perceptions called phosphenes. The visual prosthesis aims at exploiting these phosphenes to restore a form of vision in some cases of blindness. Very schematically, a camera or a picture capturing device transforms images into electrical signals that are then adapted and passed on to some still functional part of the visual pathways, thus bridging the defective structures. The system has at least some parts implanted, including electrodes and their stimulator circuits. A photo- sensitive array in the eye could provide the necessary image input, but most approaches use an external minia- ture camera. Typically, the visual data handling requires an external processor and the power supply as well as the data are provided to the implant by a transcutaneous transmission system. Despite a first pioneering attempt by Brindley and Lewin as early as 1968 (1) only very few experimental visual prostheses have been implanted in humans so far. The limited accessibility of the involved anatomical struc- tures, the poorly understood neural encoding, and the huge amount of information handled by the visual nervous system have clearly hampered a development that can not yet be compared with the far more advanced evolution of cochlear implants (see article on Cochlear Implants in this encyclopedia). The visual prosthesis is still at a very Encyclopedia of Medical Devices and Instrumentation, Second Edition, edited by John G. Webster Copyright # 2006 John Wiley & Sons, Inc.
    [Show full text]
  • Injectable Hydrogel Enables Local and Sustained Co-Delivery to the Brain
    Biomaterials 235 (2020) 119794 Contents lists available at ScienceDirect Biomaterials journal homepage: www.elsevier.com/locate/biomaterials Injectable hydrogel enables local and sustained co-delivery to the brain: Two clinically approved biomolecules, cyclosporine and erythropoietin, T accelerate functional recovery in rat model of stroke Anup Tuladhara,f, Jaclyn M. Obermeyera,b,f, Samantha L. Paynea,b,f, Ricky C.W. Siub, ∗ Sohrab Zandc, Cindi M. Morsheada,e,f, Molly S. Shoicheta,b,d,e, a Institute of Biomaterials and Biomedical Engineering, University of Toronto, 164 College Street, Toronto, ON, M5S 3G9, Canada b Department of Chemical Engineering and Applied Chemistry, University of Toronto, 200 College Street, Toronto, ON, M5S 3E5, Canada c Department of Human Biology, University of Toronto, 300 Huron Street, Toronto, ON, M5S 3E5, Canada d Department of Chemistry, University of Toronto, 80 St. George Street, Toronto, ON, M5S 3H6, Canada e Department of Surgery, University of Toronto, 149 College Street, Toronto, ON, M5S 3E1, Canada f Donnelly Centre for Cellular and Biomolecular Research, University of Toronto, 160 College Street, Toronto, ON, M5S 3E1, Canada ARTICLE INFO ABSTRACT Keywords: Therapeutic delivery to the brain is limited by the blood-brain barrier and is exacerbated by off-target effects Hyaluronan associated with systemic delivery, thereby precluding many potential therapies from even being tested. Given Methyl cellulose the systemic side effects of cyclosporine and erythropoietin, systemic administration would be precluded in the Drug delivery context of stroke, leaving only the possibility of local delivery. We wondered if direct delivery to the brain would Cyclosporine allow new reparative therapeutics, such as these, to be identified for stroke.
    [Show full text]
  • Hardware-Software Co-Design for Brain-Computer Interfaces
    Hardware-Software Co-Design for Brain-Computer Interfaces Ioannis Karageorgos* Karthik Sriram* Jan´ Vesely*´ Michael Wu Dept of Electrical Engineering Dept of Computer Science Dept of Computer Science Dept of Computer Science Arts & Sciences Arts & Sciences Arts & Sciences Arts & Sciences Yale University Yale University Rutgers & Yale Universities Rutgers University [email protected] [email protected] [email protected] [email protected] Marc Powell David Borton Rajit Manohar Abhishek Bhattacharjee School of Engineering School of Engineering Dept of Electrical Engineering Dept of Computer Science Carney Institute for Brain Science Carney Institute for Brain Science Arts & Sciences Arts & Sciences Brown University Brown University Yale University Yale University marc [email protected] david [email protected] [email protected] [email protected] Abstract—Brain-computer interfaces (BCIs) offer avenues to the skull from biological neurons to deduce brain activ- treat neurological disorders, shed light on brain function, and ity [42, 54, 77]. While these devices do not require surgi- interface the brain with the digital world. Their wider adoption cal deployment, the signals they collect are noisy and low- rests, however, on achieving adequate real-time performance, meeting stringent power constraints, and adhering to FDA- resolution, making them less ideal as a source of control mandated safety requirements for chronic implantation. BCIs signal for forward-looking BCI applications [34, 41, 74, 86]. have, to date, been designed as custom ASICs for specific diseases In these cases, a better alternative—and the focus of our or for specific tasks in specific brain regions. General-purpose study—is to surgically embed BCIs directly on, around [111], architectures that can be used to treat multiple diseases and and in the brain tissue [15].
    [Show full text]
  • The Generation and Propagation of the Human Alpha Rhythm Milan Halgren, Orrin Devinsky, Werner K
    bioRxiv preprint first posted online Nov. 18, 2017; doi: http://dx.doi.org/10.1101/202564. The copyright holder for this preprint (which was not peer-reviewed) is the author/funder. It is made available under a CC-BY-NC 4.0 International license. The Generation and Propagation of the Human Alpha Rhythm Milan Halgren, Orrin Devinsky, Werner K. Doyle, Hélène Bastuji, Marc Rey, Rachel Mak- McCully, Patrick Chauvel, István Ulbert, Dániel Fabó, Lorand Erőss, Lucia Wittner, Gary Heit, Emad Eskandar, Arnold Mandell, Sydney S. Cash Contact: [email protected] Introduction The alpha rhythm (7-13 Hz) is the longest studied brain oscillation and has been theorized to play a key role in cognition. Still, substantial uncertainty remains over its physiology. In this study, we used micro and macro electrodes in patients undergoing surgery for epilepsy to measure the intracortical and thalamic generators of the human alpha rhythm. We first found that alpha propagates from higher-order anterosuperior cortex towards the lower- order occipital poles, consistent with alpha effecting top-down processing. This cortical alpha drives thalamic alpha, reversing prevailing theories of a thalamic alpha pacemaker. Finally, alpha is dominated by currents and firing in supragranular cortex, contravening the popular conception of alpha as an infragranular rhythm. Together, these results demonstrate that the alpha rhythm reflects short-range supragranular feedback which propagates from higher-order to lower order cortex and cortex to thalamus. These physiological insights explain how alpha could mediate feedback throughout the thalamocortical system. bioRxiv preprint first posted online Nov. 18, 2017; doi: http://dx.doi.org/10.1101/202564.
    [Show full text]
  • Totally Implantable Bidirectional Neural Prostheses: a Flexible Platform for Innovation in Neuromodulation
    MINI REVIEW published: 07 September 2018 doi: 10.3389/fnins.2018.00619 Totally Implantable Bidirectional Neural Prostheses: A Flexible Platform for Innovation in Neuromodulation Philip A. Starr* Professor of Neurological Surgery, University of California, San Francisco, San Francisco, CA, United States Implantable neural prostheses are in widespread use for treating a variety of brain disorders. Until recently, most implantable brain devices have been unidirectional, either delivering neurostimulation without brain sensing, or sensing brain activity to drive external effectors without a stimulation component. Further, many neural interfaces that incorporate a sensing function have relied on hardwired connections, such that subjects are tethered to external computers and cannot move freely. A new generation of neural prostheses has become available, that are both bidirectional (stimulate as well as Edited by: record brain activity) and totally implantable (no externalized connections). These devices Andre Machado, Cleveland Clinic Lerner College of provide an opportunity for discovering the circuit basis for neuropsychiatric disorders, Medicine, United States and to prototype personalized neuromodulation therapies that selectively interrupt neural Reviewed by: activity underlying specific signs and symptoms. David Borton, Brown University, United States Keywords: neural prostheses, brain-computer interface, deep brain stimulation, bidirectional interface, oscillatory J. Luis Lujan, brain activity, electrocorticography, local field potential, brain sensing Mayo Clinic College of Medicine & Science, United States *Correspondence: INTRODUCTION Philip A. Starr [email protected] Implantable bidirectional neural prostheses are devices that combine neurostimulation with neural sensing. These may be implanted in the central or peripheral nervous system. Here, we focus on Specialty section: bidirectional interfaces that are implanted in the central nervous system (CNS).
    [Show full text]