Computational Neuroscience Meets Optogenetics: Unlocking the Brain’S Secrets

Total Page:16

File Type:pdf, Size:1020Kb

Computational Neuroscience Meets Optogenetics: Unlocking the Brain’S Secrets Health & Medicine ︱ Prof Simon Schultz and Dr Konstantin Nikolic Computational neuroscience meets optogenetics: Unlocking the brain’s secrets Working at the interface omposed of billions of specialised responsible for perception, action Simplified models allow researchers to study how the geometry of a neuron’s “dendritic tree” affects its ability to process information. between engineering and nerve cells (called neurons) wired and memory. But this is changing. neuroscience, Professor Simon C together in complex, intricate Schultz and Dr Konstantin webs, the brain is inherently challenging LET THERE BE LIGHT Nikolic at Imperial College to study. Neurons communicate with A powerful new tool (invented by Boyden of Neurotechnology and Director of SHEDDING LIGHT ON THE BRAIN AN INSIGHT INTO NEURONAL GAIN London are developing tools each other by transmitting electrical and and Deisseroth just a little over a decade the Imperial Centre of Excellence in Their innovative approach uses Using two biophysical models of to help us understand the chemical signals along neural circuits: ago) allows researchers to map the brain’s Neurotechnology, Dr Konstantin Nikolic, sophisticated two-photon microscopy, neurons, genetically-modified to include intricate workings of the brain. signals that vary both in space and time. connections, giving unprecedented Associate Professor in the Department optogenetics and electrophysiology two distinct light-sensitive proteins Combining a revolutionary Until now, technical limitations in the access to the workings of the brain. Its of Electrical and Electronic Engineering, to measure (and disturb) patterns of (called opsins): channelrhodopsin-2 technology – optogenetics available research methods to study the impressive resolution enables precise and Dr Sarah Jarvis are taking a unique neuronal activity in vivo (in living tissue). (ChR2) or halorhodopsin (NpHP), Prof – with computational approach: combining optogenetics with Combining these experiments with Schultz and team could either induce neuroscience, the team are computational modelling. Although theoretical work allows the team to or inhibit the connections between developing powerful tools to A powerful new tool allows researchers optogenetics has been applied to the tease apart and understand the data neurons (their synaptic activity). Using study the real-time physiology field of neuroscience, computational that they generate. On the theoretical light to probe the cells, the researchers of individual neurons and their to map the brain’s connections, giving modelling of the brain has not taken side, the team develops algorithms explored the extent to which a neuron’s function. Their work is unlocking this new tool onboard. With this for analysing the data and models shape (its morphology) affects the level the complex secrets of the unprecedented access to the workings truly multidisciplinary approach, the to help interpret it. to which its gain can be controlled. circuitry of the brain and has Imperial researchers have developed a significance for debilitating of the brain. sophisticated computational optogenetic In a recently published study, the team Most nerve cells have branched neural disorders such as Alzheimer’s disease. brain has meant that we are a long way measurement of neural circuitry of living tool. Prof Schultz is widely known for his explored one of the basic principles extensions called dendrites (rather from understanding how information is brain circuits in real-time. The technology, work on neural coding, which explores the of information processing in neural like branches of a tree) that propagate represented and processed named optogenetics, makes use of light core principles that underlie information (or cortical) circuits, called ‘neural the electrochemical messages from by neural circuits (optics) together with genetics (neurons processing in other cells to the that have been genetically sensitised to biological nervous cell body (soma). light). By shining a light on the genetically systems. The key This ground-breaking research In their study, by modified cells that are light-sensitive, aspect to their measuring the effect researchers can switch them on or off. For current study is that is helping refine our understanding that different ratios the first time, the messages that neurons for the first time of the excitatory and send to each other can be manipulated in computational of the modulation of individual nerve inhibitory opsins have with a sophistication that mimics naturally neuroscience, cells and how this may relate to when experimentally occurring neural activity. By disturbing the models of opsins placed in different activity of individual neurons, their effect are incorporated different aspects of neural circuits. parts of the neuron, on the system can be studied – something with detailed the team were able that could not have been envisaged multi-compartment models of neurons: gain control.’ Specifically, they were to directly investigate the effect that several decades ago. This revolutionary in essence, ‘reverse engineering’ the interested in ways that the gain (slope) the cell’s shape has on gain. The team methodology enables researchers to information processing architecture of of a neuron’s input-output function investigated four common types of establish causal relationships between the brain. Using optogenetic tools, the can be modulated. Neural gain can dendritic shape and demonstrated that nerve-circuit activity and function, rather team can test the predictions made be thought of as an amplifier of neural the arrangement of the dendrites is than merely observing correlations by their models directly, rather than communication. When gain is increased, an important factor in controlling gain between the two. indirectly. They are particularly interested excited neurons become even more (either naturally, by neuromodulation, in changes in cortical circuit properties active; conversely, when gain is inhibited or artificially, using optogenetics). OPTOGENETICS MEETS during dementias such as Alzheimer’s neurons become less active. As Prof The symmetry of the dendrites relative COMPUTATIONAL NEUROSCIENCE disease. Prof Schultz explains: ‘I believe Schultz explains: ‘an important property to the soma (cell body) was also Charting new territories in neuroscience, that understanding the functional of a neuron is, using engineering found to be important. The Imperial researchers at Imperial College London principles of cortical circuits is crucial to terminology, its ‘gain’. That is, the slope researchers thus showed that the are taking this revolutionary technology understanding, and treating, the effects of its input/output function, or the structure of an individual neuron is key a step further. Simon Schultz, Professor of brain disorders’. extent to which it amplifies its inputs’. to its functional role within the network. www.researchfeatures.com www.researchfeatures.com Behind the Research Professor Dr Konstantin Simon Schultz Nikolic E: [email protected] W: www.schultzlab.org E: [email protected] W: www.imperial.ac.uk/bio-modelling/ Research Objectives References Prof Schultz and Dr Nikolic combine the relatively new Jarvis S, Nikolic K, Schultz S. (2018) Neuronal gain modulability field of optogenetics with computational neuroscience is determined by dendritic morphology: A computational to understand how the ‘gain’ of a neuron’s input/output optogenetic study. PLoS Comput Biol 14(3): e1006027. system is modulated. https://doi.org/10.1371/journal.pcbi.1006027 Grossman N, Simiaki V, Martinet C, et al., (2013) The spatial pattern of light determines the kinetics and modulates Detail backpropagation of optogenetic action potentials, Journal of Computational Neuroscience, Vol:34, ISSN:0929-5313, Prof Simon Schultz Pages:477-488. Dept of Bioengineering Imperial College London Nikolic K, Grossman N, Grubb M, Burrone J, Toumazou C, South Kensington Campus Degenaar P. (2009) Photocycles of Channelrhodopsin-2. London SW7 2AZ Photochemistry and Photobiology, 85: 400–411. The shape of the cell’s arms or ‘dendrites’ affects the neuronal gain. UK Evans B D, Jarvis S, Schultz S R, Nikolic K. (2016) “PyRhO: Dr Konstantin Nikolic A Multiscale Optogenetics Simulation Platform”, Frontiers The researchers showed that one Institute of Biomedical Engineering in Neuroinformatics, 10 (8). doi:10.3389/fninf.2016.00008 common cell type in particular – the For the first time in computational Imperial College London pyramidal cell – is highly modulable. South Kensington Campus Their finding reinforces our current neuroscience, models of opsins are London SW7 2AZ Personal Response understanding that the role of pyramidal UK cells within neural circuits is to act not only incorporated with detailed multi- as the primary excitatory neuron but also compartment models of neurons. Bio Your research holds promise for unravelling as a key element for setting the gain of Simon Schultz is Professor of Neurotechnology and Director the complexities behind disorders of the brain and to develop new treatments. How far are the circuit. Other cell types investigated of the Centre for Neurotechnology at Imperial College we from achieving this? by Prof Schultz and his team were found of neuroprosthetics – devices that connect rather than over-writing neural activity with London. to be less modulable. This suggests that to brain cells to deliver information that new information. Progress on understanding and treating brain
Recommended publications
  • Neural Dust: Ultrasonic Biological Interface
    Neural Dust: Ultrasonic Biological Interface Dongjin (DJ) Seo Electrical Engineering and Computer Sciences University of California at Berkeley Technical Report No. UCB/EECS-2018-146 http://www2.eecs.berkeley.edu/Pubs/TechRpts/2018/EECS-2018-146.html December 1, 2018 Copyright © 2018, by the author(s). All rights reserved. Permission to make digital or hard copies of all or part of this work for personal or classroom use is granted without fee provided that copies are not made or distributed for profit or commercial advantage and that copies bear this notice and the full citation on the first page. To copy otherwise, to republish, to post on servers or to redistribute to lists, requires prior specific permission. Neural Dust: Ultrasonic Biological Interface by Dongjin Seo A dissertation submitted in partial satisfaction of the requirements for the degree of Doctor of Philosophy in Engineering - Electrical Engineering and Computer Sciences in the Graduate Division of the University of California, Berkeley Committee in charge: Professor Michel M. Maharbiz, Chair Professor Elad Alon Professor John Ngai Fall 2016 Neural Dust: Ultrasonic Biological Interface Copyright 2016 by Dongjin Seo 1 Abstract Neural Dust: Ultrasonic Biological Interface by Dongjin Seo Doctor of Philosophy in Engineering - Electrical Engineering and Computer Sciences University of California, Berkeley Professor Michel M. Maharbiz, Chair A seamless, high density, chronic interface to the nervous system is essential to enable clinically relevant applications such as electroceuticals or brain-machine interfaces (BMI). Currently, a major hurdle in neurotechnology is the lack of an implantable neural interface system that remains viable for a patient's lifetime due to the development of biological response near the implant.
    [Show full text]
  • Perceiving Invisible Light Through a Somatosensory Cortical Prosthesis
    ARTICLE Received 24 Aug 2012 | Accepted 15 Jan 2013 | Published 12 Feb 2013 DOI: 10.1038/ncomms2497 Perceiving invisible light through a somatosensory cortical prosthesis Eric E. Thomson1,2, Rafael Carra1,w & Miguel A.L. Nicolelis1,2,3,4,5 Sensory neuroprostheses show great potential for alleviating major sensory deficits. It is not known, however, whether such devices can augment the subject’s normal perceptual range. Here we show that adult rats can learn to perceive otherwise invisible infrared light through a neuroprosthesis that couples the output of a head-mounted infrared sensor to their soma- tosensory cortex (S1) via intracortical microstimulation. Rats readily learn to use this new information source, and generate active exploratory strategies to discriminate among infrared signals in their environment. S1 neurons in these infrared-perceiving rats respond to both whisker deflection and intracortical microstimulation, suggesting that the infrared repre- sentation does not displace the original tactile representation. Hence, sensory cortical prostheses, in addition to restoring normal neurological functions, may serve to expand natural perceptual capabilities in mammals. 1 Department of Neurobiology, Duke University, Box 3209, 311 Research Drive, Bryan Research, Durham, North Carolina 27710, USA. 2 Edmond and Lily Safra International Institute for Neuroscience of Natal (ELS-IINN), Natal 01257050, Brazil. 3 Department of Biomedical Engineering, Duke University, Durham, North Carolina 27710, USA. 4 Department of Psychology and Neuroscience, Duke University, Durham, North Carolina 27710, USA. 5 Center for Neuroengineering, Duke University, Durham, North Carolina 27710, USA. w Present address: University of Sao Paulo School of Medicine, Sao Paulo 01246-000, Brazil. Correspondence and requests for materials should be addressed to M.A.L.N.
    [Show full text]
  • Optogenetics Controlling Neurons with Photons
    Valerie C. Coffey Optogenetics Controlling Neurons with Photons An advancing field of neuroscience uses light to understand how the brain works and to create new tools to treat disease. Wireless optogenetics tools like these tiny implants in live mice are enabling scientists to map the stimulation of certain neurons of the brain to specific responses. J. Rogers/Northwestern Univ. 24 OPTICS & PHOTONICS NEWS APRIL 2018 APRIL 2018 OPTICS & PHOTONICS NEWS 25 In just over a decade, the discovery of numerous opsins with different specializations has allowed scientists and engineers to make rapid progress in mapping brain activity. wo thousand years ago, ancient Egyptians halorhodopsin can silence the neurons in the hypo- knew that the electrical shocks of torpedo thalamus, inducing sleep in living mice. fish, applied to the body, could offer pain In just over a decade, the discovery of numerous relief. Two hundred years ago, physicians opsins with different specializations has allowed scien- understood that electrical stimulation of a tists and engineers to make rapid progress in mapping Tfrog’s spine could control muscle contraction. Today, brain activity, motivated by the hope of solving intrac- electrical therapy underlies many treatments, from table neurological conditions. And it doesn’t hurt that pacemakers to pain control. investment in neuroscience research has grown at the But neuroscience has long awaited a more precise same time. tool for controlling specific types of neurons. Electrical In 2013, the Obama administration announced a stimulation (e-stim) approaches stimulate a large area collaborative public-private effort, the Brain Research without precise spatial control, and can’t distinguish through Advancing Innovative Neurotechnologies between different cell types.
    [Show full text]
  • Mousecircuits.Org: an Online Repository to Guide the Circuit Era of Disordered Affect
    bioRxiv preprint doi: https://doi.org/10.1101/2020.02.16.951608; this version posted February 17, 2020. The copyright holder for this preprint (which was not certified by peer review) is the author/funder, who has granted bioRxiv a license to display the preprint in perpetuity. It is made available under aCC-BY-NC-ND 4.0 International license. MouseCircuits.org: An online repository to guide the circuit era of disordered affect Kristin R. Anderson ID 1,2 and Dani Dumitriu ID 1,2 1Columbia University, Departments of Pediatrics and Psychiatry, New York State Psychiatric Institute, 1051 Riverside Drive, New York, NY 10032 2Columbia University, Zuckerman Institute, 3227 Broadway, New York, NY 10027 Affective disorders rank amongst the most disruptive and tem and the gut microbiome (2,3). However, the mysteries of prevalent psychiatric diseases, resulting in enormous societal the brain, a structure with idiosyncratic and interconnected and economic burden, and immeasurable personal costs. Novel architecture, are unlikely to be revealed solely on the basis of therapies are urgently needed but have remained elusive. The this type of sledgehammer approach. era of circuit-mapping in rodent models of disordered affect, ushered in by recent technological advancements allowing for Enter the era of circuit dissection. In the last precise and specific neural control, has reenergized the hope for decade, groundbreaking technological advances have al- precision psychiatry. Here, we present a novel whole-brain cu- lowed neuroscientists to take control of neural firing with mulative network and critically access the progress made to- impressive precision and specificity (Figure 1) (4–7).
    [Show full text]
  • An Embedded Real-Time Processing Platform for Optogenetic Neuroprosthetic Applications
    IEEE TRANSACTIONS ON NEURAL SYSTEMS AND REHABILITATION ENGINEERING, VOL. 26, NO. 1, JANUARY 2018 233 An Embedded Real-Time Processing Platform for Optogenetic Neuroprosthetic Applications Boyuan Yan and Sheila Nirenberg Abstract— Optogenetics offers a powerful new approach temporal resolution. Since these proteins require bright for controlling neural circuits. It has numerous applica- light [23], [24], standard high resolution devices such as LCD tions in both basic and clinical science. These applications monitors are ineffective. While laser or LED-based illumi- require stimulating devices with small processors that can perform real-time neural signal processing, deliver high- nation systems can meet the requirements of light intensity, intensity light with high spatial and temporal resolution, they are not readily suitable for providing spatially-patterned and do not consume a lot of power. In this paper, we stimuli. Digital light processing (DLP) projectors, however demonstrate the implementation of neuronal models in a can achieve this: the key component, a chip called Digital platform consisting of an embedded system module and Micromirror Device (DMD) [25], consists of an array of a portable digital light processing projector. As a replace- ment for damaged neural circuitry, the embedded module several hundred thousand micromirrors, which can change processes neural signals and then directs the projector to position at kHz frequencies. These offer the most flexibility in optogenetically activate a downstream neural pathway. We terms of the spatial and temporal modulation of the activating present a design in the context of stimulating circuits in the light. visual system, but the approach is feasible for a broad range In addition to an effective stimulator, the other essential of biomedical applications.
    [Show full text]
  • Implantable Microelectrodes on Soft Substrate with Nanostructured Active Surface for Stimulation and Recording of Brain Activities Valentina Castagnola
    Implantable microelectrodes on soft substrate with nanostructured active surface for stimulation and recording of brain activities Valentina Castagnola To cite this version: Valentina Castagnola. Implantable microelectrodes on soft substrate with nanostructured active sur- face for stimulation and recording of brain activities. Micro and nanotechnologies/Microelectronics. Universite Toulouse III Paul Sabatier, 2014. English. tel-01137352 HAL Id: tel-01137352 https://hal.archives-ouvertes.fr/tel-01137352 Submitted on 31 Mar 2015 HAL is a multi-disciplinary open access L’archive ouverte pluridisciplinaire HAL, est archive for the deposit and dissemination of sci- destinée au dépôt et à la diffusion de documents entific research documents, whether they are pub- scientifiques de niveau recherche, publiés ou non, lished or not. The documents may come from émanant des établissements d’enseignement et de teaching and research institutions in France or recherche français ou étrangers, des laboratoires abroad, or from public or private research centers. publics ou privés. THÈSETHÈSE En vue de l’obtention du DOCTORAT DE L’UNIVERSITÉ DE TOULOUSE Délivré par : l’Université Toulouse 3 Paul Sabatier (UT3 Paul Sabatier) Présentée et soutenue le 18/12/2014 par : Valentina CASTAGNOLA Implantable Microelectrodes on Soft Substrate with Nanostructured Active Surface for Stimulation and Recording of Brain Activities JURY M. Frédéric MORANCHO Professeur d’Université Président de jury M. Blaise YVERT Directeur de recherche Rapporteur Mme Yael HANEIN Professeur d’Université Rapporteur M. Pascal MAILLEY Directeur de recherche Examinateur M. Christian BERGAUD Directeur de recherche Directeur de thèse Mme Emeline DESCAMPS Chargée de Recherche Directeur de thèse École doctorale et spécialité : GEET : Micro et Nanosystèmes Unité de Recherche : Laboratoire d’Analyse et d’Architecture des Systèmes (UPR 8001) Directeur(s) de Thèse : M.
    [Show full text]
  • ECE 5070: Neuroengineering and Neuroprosthetics
    ECE 5070: Neuroengineering and Neuroprosthetics Course Description An overview of the broad field of Neuroengineering for graduate and senior undergraduate students with engineering or neuroscience backgrounds. Focusing on neural interfaces and prostheses, this course covers from basic neurophysiology and computational neuronal models to advanced neural interfaces and prostheses currently being actively developed in the field. Transcript Abbreviation: Neur Eng & Prosth Grading Plan: Letter Grade Course Deliveries: Classroom Course Levels: Undergrad, Graduate Student Ranks: Junior, Senior, Masters, Doctoral Course Offerings: Autumn Flex Scheduled Course: Never Course Frequency: Even Years Course Length: 14 Week Credits: 3.0 Repeatable: No Time Distribution: 3.0 hr Lec Expected out-of-class hours per week: 6.0 Graded Component: Lecture Credit by Examination: No Admission Condition: No Off Campus: Never Campus Locations: Columbus Prerequisites and Co-requisites: Prereq: 3050 or BME 3703; or Neurosc 3010; or Grad standing in Engineering or Neurosc. Exclusions: Not open to students with credit for 5194.03 or Neurosc 5070. Cross-Listings: Cross-listed in Neurosc. Course Rationale: Introduce students a vibrant, interdisciplinary field which integrates engineering and neuroscience principles for treating neurological disorders. The course is required for this unit's degrees, majors, and/or minors: No The course is a GEC: No The course is an elective (for this or other units) or is a service course for other units: Yes Subject/CIP Code: 14.1001 Subsidy Level: Doctoral Course Programs Abbreviation Description CpE Computer Engineering EE Electrical Engineering Course Goals Master principles of neural interfaces. Be competent with computational neural models. Be competent with design of common neuroprostheses.
    [Show full text]
  • New Technologies for Human Robot Interaction and Neuroprosthetics
    University of Plymouth PEARL https://pearl.plymouth.ac.uk Faculty of Science and Engineering School of Engineering, Computing and Mathematics 2017-07-01 Human-Robot Interaction and Neuroprosthetics: A review of new technologies Cangelosi, A http://hdl.handle.net/10026.1/9872 10.1109/MCE.2016.2614423 IEEE Consumer Electronics Magazine All content in PEARL is protected by copyright law. Author manuscripts are made available in accordance with publisher policies. Please cite only the published version using the details provided on the item record or document. In the absence of an open licence (e.g. Creative Commons), permissions for further reuse of content should be sought from the publisher or author. CEMAG-OA-0004-Mar-2016.R3 1 New Technologies for Human Robot Interaction and Neuroprosthetics Angelo Cangelosi, Sara Invitto Abstract—New technologies in the field of neuroprosthetics and These developments in neuroprosthetics are closely linked to robotics are leading to the development of innovative commercial the recent significant investment and progress in research on products based on user-centered, functional processes of cognitive neural networks and deep learning approaches to robotics and neuroscience and perceptron studies. The aim of this review is to autonomous systems [2][3]. Specifically, one key area of analyze this innovative path through the description of some of the development has been that of cognitive robots for human-robot latest neuroprosthetics and human-robot interaction applications, in particular the Brain Computer Interface linked to haptic interaction and assistive robotics. This concerns the design of systems, interactive robotics and autonomous systems. These robot companions for the elderly, social robots for children with issues will be addressed by analyzing developmental robotics and disabilities such as Autism Spectrum Disorders, and robot examples of neurorobotics research.
    [Show full text]
  • Brain-Machine Interface: from Neurophysiology to Clinical
    Neurophysiology of Brain-Machine Interface Rehabilitation Matija Milosevic, Osaka University - Graduate School of Engineering Science - Japan. Abstract— Long-lasting cortical re-organization or II. METHODS neuroplasticity depends on the ability to synchronize the descending (voluntary) commands and the successful execution Stimulation of muscles with FES was delivered using a of the task using a neuroprosthetic. This talk will discuss the constant current biphasic waveform with a 300μs pulse width neurophysiological mechanisms of brain-machine interface at 50 Hz frequency via surface electrodes. First, repetitive (BMI) controlled neuroprosthetics with the aim to provide transcranial magnetic stimulation (rTMS) intermittent theta implications for development of technologies for rehabilitation. burst protocol (iTBS) was used to induce cortical facilitation. iTBS protocol consists of pulses delivered intermittently at a I. INTRODUCTION frequency of 50 Hz and 5 Hz for a total of 200 seconds. Functional electrical stimulation (FES) neuroprosthetics Moreover, motor imagery protocol was used to display a can be used to applying short electric impulses over the virtual reality hand opening and closing sequence of muscles or the nerves to generate hand muscle contractions movements (hand flexion/extension) while subject’s hands and functional movements such as reaching and grasping. remained at rest and out of the visual field. Our work has shown that recruitment of muscles using FES goes beyond simple contractions, with evidence suggesting III. RESULTS re-organization of the spinal reflex networks and cortical- Our first results showed that motor imagery can affect level changes after the stimulating period [1,2]. However, a major challenge remains in achieving precise temporal corticospinal facilitation in a phase-dependent manner, i.e., synchronization of voluntary commands and activation of the hand flexor muscles during hand closing and extensor muscles [3].
    [Show full text]
  • Practical and Ethical Issues at the Intersection of Brain Science and Society
    Emerging Neurotechnologies: Practical and Ethical Issues at the Intersection of Brain Science and Society James Giordano PhD Departments of Neurology and Biochemistry Neuroethics Studies Program, Pellegrino Center for Clinical Bioethics Georgetown University Medical Center Washington, DC, USA and EU-Human Brain Project SP-12 Uppsala University, Sweden Neuroscience… • Huge leaps using technology to study and understand how nervous systems and brains are structured and function. Allowed understanding at certain levels of causality: – Formal: Overall “workings” of biological systems – Material: Structure and functional roles of neurons, glia But not at others… – Efficient: How “grey stuff” actually makes “great stuff” – Final: For what? To what “ends”? Core Questions... What do we do with the information and capability we have? What do we do about the information and capability we don’t? Questions toward Innovation • Tools to Theory • Theory to Tools... ...to Theory AISC Approach Brain Science on the World Stage • EU Human Brain Project • US BRAIN initiative • China Brain Project • Japan Brain Project • Global NeuroS/T Economic Predictions 2025 – Asia – US/Western Europe – South America Neuroscience and Technologies (NeuroS/T) • Assessment – Biomarkers – Genetics/genomics – Imaging – Brain modeling/mapping • Interventional – Technopharmaceutics – P-Stim – Neurofeedback – Transcranial Modulation – Deep Brain Stimulation – BCI – Neuroprosthetics • Derivative – -Artificial neural networks – -AI technologies A-3: Actual Ability to Assess...Access...Affect To What Effect(s) and Ends? Neuroimaging – PET – CT – MR – fMR – DTI – MEG/qEEG Can we Scan the Brain to Depict Consciousness and/or “Read” Minds? text copyright, J. Giordano, 2014 Neurogenetics – Genotyping – Phenotyping – Proteomics – Genetic Intervention(s) Can we “Predict” or “Create” Present and Future “Selves”? text copyright, J.
    [Show full text]
  • Neuroprosthetics Session Abstract-FINAL
    NEUROPROTHETICS Session co-chairs: Justin Williams, University of Wisconsin, Tim Denison, Medtronic The brain has always been attractive to engineers. Neurons and their connections, like tiny circuit elements, process and transmit information in a dramatic way that is intimately curious to researchers in the computer science and engineering fields. Neurons are amazing computational devices capable of both robust response to widely varied inputs and adaptability to changing conditions. Our most advanced computing systems are still dwarfed by the computational power of the human brain. Even small groups of neurons are capable of intricate interactions that produce basic mechanisms of learning and memory, highly parallel processing and exquisite sensing capabilities. Science has made great strides in the past few decades toward uncovering the basic principles underlying the brain’s ability to receive sensation and control movement. These discoveries, along with revolutionary advances in computing power and microelectronics technology, have led to an emerging view that neural prosthetics, or electronic interfaces with the brain for restoration or augmentation of physiological function, may one day be possible. While the creation of a “six million dollar man" may still be far into the future, neural prostheses are rapidly becoming real potential treatments for a broad range of patients with injury or disease of the nervous system. This session will focus on the types of engineering technology that we use to interface with the nervous system. This includes technology for stimulating the nervous system for restoration of sensory function as well as methods for extracting motor intention from the brain for use in artificial prostheses.
    [Show full text]
  • Optogenetics Inspired Transition Metal Dichalcogenide Neuristors for In-Memory Deep Recurrent Neural Networks
    ARTICLE https://doi.org/10.1038/s41467-020-16985-0 OPEN Optogenetics inspired transition metal dichalcogenide neuristors for in-memory deep recurrent neural networks Rohit Abraham John 1, Jyotibdha Acharya2,3, Chao Zhu 1, Abhijith Surendran2, Sumon Kumar Bose 2, Apoorva Chaturvedi1, Nidhi Tiwari4, Yang Gao1, Yongmin He 1, Keke K. Zhang1, Manzhang Xu 1, ✉ ✉ Wei Lin Leong 2, Zheng Liu 1, Arindam Basu 2 & Nripan Mathews 1,4 1234567890():,; Shallow feed-forward networks are incapable of addressing complex tasks such as natural language processing that require learning of temporal signals. To address these require- ments, we need deep neuromorphic architectures with recurrent connections such as deep recurrent neural networks. However, the training of such networks demand very high pre- cision of weights, excellent conductance linearity and low write-noise- not satisfied by current memristive implementations. Inspired from optogenetics, here we report a neuromorphic computing platform comprised of photo-excitable neuristors capable of in-memory compu- tations across 980 addressable states with a high signal-to-noise ratio of 77. The large linear dynamic range, low write noise and selective excitability allows high fidelity opto-electronic transfer of weights with a two-shot write scheme, while electrical in-memory inference provides energy efficiency. This method enables implementing a memristive deep recurrent neural network with twelve trainable layers with more than a million parameters to recognize spoken commands with >90% accuracy. 1 School of Materials Science and Engineering, Nanyang Technological University, 50 Nanyang Avenue, Singapore 639798, Singapore. 2 School of Electrical and Electronic Engineering, Nanyang Technological University, 50 Nanyang Avenue, Singapore 639798, Singapore.
    [Show full text]