CSE 599E Introduction to Brain-Computer Interfacing

Similar documents
Restoring Communication and Mobility

An Overview of BMIs. Luca Rossini. Workshop on Brain Machine Interfaces for Space Applications

Bioscience in the 21st century

The Evolution of Neuroprosthetics

Introduction to Computational Neuroscience

A Brain Computer Interface System For Auto Piloting Wheelchair

Neurorobotics, and brain-machine interfaces. Oct. 10 th, 2006.

Simultaneous Real-Time Detection of Motor Imagery and Error-Related Potentials for Improved BCI Accuracy

Brain Computer Interface. Mina Mikhail

Design Considerations and Clinical Applications of Closed-Loop Neural Disorder Control SoCs

Implantable Microelectronic Devices

How we study the brain: a survey of methods used in neuroscience

Error Detection based on neural signals

Neurotherapy and Neurofeedback, as a research field and evidence-based practice in applied neurophysiology, are still unknown to Bulgarian population

Carnegie Mellon University Annual Progress Report: 2011 Formula Grant

International Journal of Engineering Science Invention Research & Development; Vol. III, Issue X, April e-issn:

EE 4BD4 Lecture 11. The Brain and EEG

Of Monkeys and. Nick Annetta

Introduction to Electrophysiology

ELEC ENG 4BD4 Lecture 1. Biomedical Instrumentation Instructor: Dr. Hubert de Bruin

Brain-computer interface to transform cortical activity to control signals for prosthetic arm

Mental State Sensing and the Goal of Circuit-Synapse Synergy

Efficient Feature Extraction and Classification Methods in Neural Interfaces

EEG BRAIN-COMPUTER INTERFACE AS AN ASSISTIVE TECHNOLOGY: ADAPTIVE CONTROL AND THERAPEUTIC INTERVENTION

Event Related Potentials: Significant Lobe Areas and Wave Forms for Picture Visual Stimulus

ERP Components and the Application in Brain-Computer Interface

Neuroimaging and Assessment Methods

PD233: Design of Biomedical Devices and Systems

Electroencephalogram (EEG) Hsiao-Lung Chan Dept Electrical Engineering Chang Gung University

Reach and grasp by people with tetraplegia using a neurally controlled robotic arm

ISSN: (Online) Volume 3, Issue 7, July 2015 International Journal of Advance Research in Computer Science and Management Studies

EEG, ECG, EMG. Mitesh Shrestha

Electroencephalography

CURRENT TRENDS IN GRAZ BRAIN-COMPUTER INTERFACE (BCI) RESEARCH

Electrocorticography-Based Brain Computer Interface The Seattle Experience

Neuromotor Rehabilitation by Neurofeedback

NEURAL CONTROL OF MOVEMENT: ENGINEERING THE RHYTHMS OF THE BRAIN

Oscillations: From Neuron to MEG

Detection and Plotting Real Time Brain Waves

Introduction to Computational Neuroscience

Hearing the Universal Language: Music and Cochlear Implants

BREATHE - LISTEN - THRIVE

Benjamin Blankertz Guido Dornhege Matthias Krauledat Klaus-Robert Müller Gabriel Curio

Event-Related Desynchronization/ Synchronization- Based Brain-Computer Interface towards Volitional Cursor Control in a 2D Center-Out Paradigm

EEG in the ICU: Part I

Decisions Have Consequences

Novel single trial movement classification based on temporal dynamics of EEG

Brain-Machine Interfaces and Sport

A Study of Smartphone Game Users through EEG Signal Feature Analysis

Development of a New Rehabilitation System Based on a Brain-Computer Interface Using Near-Infrared Spectroscopy

Welcome to CSE/NEUBEH 528: Computational Neuroscience

EEG Event-Related Desynchronization of patients with stroke during motor imagery of hand movement

Amy Kruse, Ph.D. Strategic Analysis, Inc. LCDR Dylan Schmorrow USN Defense Advanced Research Projects Agency

EEG-Based Brain Computer Interface System for Cursor Control Velocity Regression with Recurrent Neural Network

Classification of EEG signals in an Object Recognition task

Introduction to Computational Neuroscience

The prospects of brain computer interface applications in children

Toward a more accurate delimitation of the epileptic focus from a surgical perspective

Cortical Brain Computer Interface for Closed-Loop Deep Brain Stimulation

c Copyright 2018 Margaret C. Thompson

Physiology Unit 2 CONSCIOUSNESS, THE BRAIN AND BEHAVIOR

Research & Development of Rehabilitation Technology in Singapore

Brain Computer Interfaces, a Review

SOLUTIONS Homework #3. Introduction to Engineering in Medicine and Biology ECEN 1001 Due Tues. 9/30/03

Sixth International Conference on Emerging trends in Engineering and Technology (ICETET'16) ISSN: , pp.

Preliminary Study of EEG-based Brain Computer Interface Systems for Assisted Mobility Applications

BME 5030 ELECTRONIC BIOINSTRUMENTATION FINAL PAPER. ELECTROCORTICOGRAPHY (ECoG) BASED BRAIN COMPUTER INTERFACE FOR CEREBRAL PALSY PATIENTS

Towards natural human computer interaction in BCI

Emotion Detection from EEG signals with Continuous Wavelet Analyzing

WIRELESS PATIENT HEALTH MONITORING SYSTEM

Physiology Unit 2 CONSCIOUSNESS, THE BRAIN AND BEHAVIOR

Neurophysiology & EEG

From Spikes to Ripples: The Evolving and Expanding Role of Electroencephalography in the Diagnosis and Treatment of Epilepsy

Beyond Blind Averaging: Analyzing Event-Related Brain Dynamics. Scott Makeig. sccn.ucsd.edu

AdvAnced TMS. Research with PowerMAG Products and Application Booklet

Chapter 2 Brain Computer Interfaces

Synchronization in Nonlinear Systems and Networks

What is sound? Range of Human Hearing. Sound Waveforms. Speech Acoustics 5/14/2016. The Ear. Threshold of Hearing Weighting

Effects of Light Stimulus Frequency on Phase Characteristics of Brain Waves

Epilepsy & Functional Neurosurgery

Discrimination of EEG-Based Motor Imagery Tasks by Means of a Simple Phase Information Method

Speech, Language, and Hearing Sciences. Discovery with delivery as WE BUILD OUR FUTURE

BME 701 Examples of Biomedical Instrumentation. Hubert de Bruin Ph D, P Eng

BRAIN COMPUTER interfaces (BCIs) [1] attempt to provide

Multiscale Evidence of Multiscale Brain Communication

The neurolinguistic toolbox Jonathan R. Brennan. Introduction to Neurolinguistics, LSA2017 1

International Journal of Scientific & Engineering Research Volume 4, Issue 2, February ISSN THINKING CIRCUIT

Mental State Recognition by using Brain Waves

Hybrid BCI for people with Duchenne muscular dystrophy

Application of BCI in Mind Controlled Robotic Movements in Intelligent Rehabilitation

Brain-Computer Interfaces to Replace or Repair the Injured Central Nervous System

A note of compassion, and a note of skepticism

Saichiu Nelson Tong ALL RIGHTS RESERVED

What you re in for. Who are cochlear implants for? The bottom line. Speech processing schemes for

Kadi Sarva Vishwavidyalaya Gandhinagar

PSY 214 Lecture 16 (11/09/2011) (Sound, auditory system & pitch perception) Dr. Achtman PSY 214

What is NBS? Nextstim NBS System

Understand the New 2019 Neurostimulator Analysis-Programming CPT Coding Structure and Associated Relative Value Units

(U) USSOCOM. (U) Magnetic qeeg guided Resonance Therapy (MeRT)

Transcription:

CSE 599E Introduction to Brain-Computer Interfacing Instructor: Rajesh Rao TA: Sam Sudar

The Matrix (1999)

Firefox(1982) Brainstorm (1983) Spiderman 2 (2004) Hollywood fantasy apart, why would we want to engineer such devices?

Treating neurological conditions Can we build devices to help people with neurological disabilities?

The brain is comprised of networks of neurons (about 10 11 ) 40 m A Neuron Neurons Communicate through Electrical Activity Inputs Input Potentials Output spike (electrical pulse)

The Brain s Electrical Activity Can Be Measured EEG (scalp) Non-invasive ECoG (brain surface) Picture courtesy of Wadsworth Center Electrodes (inside the brain) Invasive Electrical nature of neural information processing allows us to record neural activity as well as stimulate parts of the brain

Example: Cochlear Implants for the Deaf Cochlear implants have improved hearing ability in about 190,000 deaf children and adults 1.Microphone 3. Sound processor 5. FM radio transmitter 6. Receiver & Stimulator 7. Electrode array From: http://www.deafblind.com/cochlear.html Example: Deep Brain Stimulation (DBS) for Parkinson s Disease Implanted device electrically stimulates parts of the brain to help reduce tremors, rigidity, and other symptoms Videos: Before DBS After DBS

Such devices are examples of brain-computer interfaces or BCIs This Course (CSE 599E) Goal: Provide an overview of the field of brain-computer interfacing Class web page: http://www.cs.washington.edu/599e The course will include: Introductory Lectures Invited Speakers Student-Led Discussion of Research Papers Who are we?

Syllabus Basic Neuroscience Recording/Stimulating the Brain Signal Processing Machine Learning Major Types of BCIs Invasive BCIs Semi-Invasive BCIs Non-Invasive BCIs Stimulating/Bidirectional BCIs BCI Applications Ethics of BCI Lectures Papers presented by student teams & discussion Lecture Workload No exams or homeworks Paper presentation: You and a selected colleague from class will work as a team to present 2-3 selected papers on an assigned day See schedule on website for list of papers Team members/days selected by staff (this week) Presentations should use slides and/or board Final project: You will work with 1-2 other colleagues on a mini-research project BCI experiment/bci data analysis/literature survey Project presentation on May 31 Project write-up due on June 3

Grading Credit/No Credit (CR/NC) only Grade based on: Student team presentation of assigned papers Final team project completion Participation in on-line/in-class discussions Enuff logistics, let s get started

BCI: What is involved? Record Classification or Regression Stimulate EEG (scalp) Non-invasive ECoG (brain surface) (Picture credit: Wadsworth Center) Electrodes (inside the brain) Invasive

INVASIVE BCI IN ANIMALS Movement direction can be predicted from motor cortex activity dˆ i r r pi rmax 0 i (Georgopoulos et al., 1988)

Monkey BCI Robot arm-hand control using motor cortical activity (Video from Schwartz lab, Pittsburgh) NON-INVASIVE BCI IN HUMANS

Non-Invasive BCIs: Electroenchephalography (EEG) EEG (recording from scalp) Picture courtesy of Wadsworth Center Rick Owens 2012 Collection

EEG is noisy but correlates with brain activity Beta waves (14-18 Hz): Associated with alertness and heightened mental activity (From Scientific American, 1996) Alpha waves (8-12 Hz): Associated with unfocusing attention (relaxation) (From Scientific American, 1996)

Delta waves (0.5-3 Hz): Associated with deep sleep (From Scientific American, 1996) Using EEG for BCI: Two Types of Responses Event Related Desynchronization or Synchronization (ERD/ERS): Change in power in specific frequency-bands Evoked Potentials (EPs) Stereotypical response caused by a stimulus (e.g., P300)

ERD ERS EP Event-Related Desynchronization (ERD) Suppression of oscillatory activity due to voluntary movement or imagery

Extract band power features (8-12Hz) Train a classifier to classify ERD for different imagined movements (e.g., left hand vs. foot movement) Use trained classifier to classify new data for moving a cursor or robot Using ERD for BCI Navigating a Virtual World using Imagined Movements (Scherer et al., 2008; Rao & Scherer, 2010)

Example: BCI based on Evoked Potentials P300: Characteristic mental aha signal caused by a discrete event Example P300 Response Target object Classifier can be used to classify EEG as containing P300 or not

Robotic Avatar based on P300 BCI Robot Objects Table Robotic Avatar based on P300 BCI (J. Neural Engineering, 2008)

INVASIVE BCI IN HUMANS Invasive BCIs: Electrocorticography (ECoG) ECoG (brain surface) (Picture credit: Wadsworth Center)

Patient Population and Setup Patients implanted for localization of seizure Experiments at bedside in 7-10 days between surgeries (photo courtesy Seattle Times) Electrocorticographic (ECoG) Recording 8x8 array or strip of platinum electrodes 1.2 to 2.3mm diameter Separated by 3mm to 1cm Several hundred thousand neurons beneath each electrode

Modulation of ECoG Activity during Movement Rest Period Hand movement Decrease in power in low frequency component Increase in power in high frequency component Power Spectral Changes in ECoG (Miller et al., J Neurosci, 2007) (Crone et al., Brain, 1998)

Basic ECoG Phenomena HFB changes are more functionally localized than LFB changes (Miller et al., J Neurosci, 2007) Imagined movements activate similar areas as actual movements Actual Hand Movement Imagined Hand Movement (Miller et al., PNAS, 2010) Activation for imagery is weaker than activation for actual movements. However

Using imagery to control a cursor Cursor Control using Imagined Speech

Brain learns to augment imagery-related activity in cursor control task (Miller et al., PNAS, 2010) What we will learn the rest of the quarter What brain responses and algorithms are used in: Invasive BCIs in animals and humans Semi-Invasive BCIs in humans Non-Invasive BCIs in humans Stimulating/Bidirectional BCIs in humans and animals What are some of the major BCI applications? What are the ethics of brain-computer interfacing?

Next Class: Primer on Neuroscience and Brain Recording/Stimulation To do: Browse class website Links to papers and notes for next class will be added on Schedule webpage