585.781.81 - Frontiers in Neuroengineering

Applied Biomedical Engineering

Spring 2024

Description

Neuroscientists and neuroengineers are using state-of-the-art tools for understanding the mysteries of the brain. A suite of new approaches is allowing researchers to tap into the brain activity and to measure the electrical, molecular, cellular, and structural changes that underlie complex behaviors as well as neurological disorders such as Alzheimer’s and Parkinson’s disease. This technological burst, spurred by the recent BRAIN (Brain Research for Advancing Innovative Neurotechnologies) Initiative by the US government, affords a unique educational opportunity at Johns Hopkins-especially with the recently inaugurated Kavli Neuroscience Discovery Institute. This multi-instructor course will give students an opportunity to learn the latest advances in the field of neuroengineering from the best experts on campus who are currently contributing their pioneering research in this field.Prerequisite(s): Written permission from the instructor is required. Completion of all required core courses, as well as the core courses for your chosen focus area, is strongly recommended.

Expanded Course Description

Neuroscientists and Neuroengineers are using state-of-the-art tools for understanding the mysteries of the brain. A plethora of new problems addressed with new approaches is allowing researchers to tap into the brain activity and to measure the electrical, molecular, cellular, and structural changes that underlie complex behaviors as well as neurological disorders such as Alzheimer’s and Parkinson’s disease. This scientific and technological burst, spurred by the recent BRAIN (Brain Research for Advancing Innovative Neuroethologies) Initiative by the US government affords a unique educational opportunity at Hopkins, especially with the recently inaugurated Kavli Neuroscience Discovery Institute.

This multi-instructor course will give the students an opportunity to learn the latest advances in the field of Neuroengineering from the best experts from JHU who are currently contributing with their pioneering research in this field.

Prerequisites/Co-requisites

Required

A written permission from the instructor.

Strongly Recommended

- 602—Physiology for Applied Biomedical Engineering II
- 732—Advanced Signal Processing for Biomedical Engineers
- A good knowledge of MATLAB

All the required core courses and your specific focus area core course should be completed before taking this course.

Instructors

Course Structure

The course is divided into 14 modules. Each module will run for one week from Wednesday through Tuesday. This will be referred to as the Module Week. In what follows, these days will be referred to as Day 1 (Wed) to Day 7 (next Tue) respectively.

The Modules can be accessed by clicking Course Modules on the left menu in Blackboard. A module will have several sections including the Overview, Content, Readings, Discussions and Assignments. Students are encouraged to preview all sections of the module on Day 1 of each module.

Students should regularly check the Calendar and/or Announcements for assignment Due Dates.

Course Topics

Module Title & Topics
Cell and Tissue Models for Neuroscience & Neuroengineering · Introduction to Cell Models · Introduction to Tissue Models · Example Tissue Models in Neuroscience & Neuroengineering
Animal Models for Neuroscience & Neuroengineering · Introduction to Animal Models · Selection of an Animal Model · Example Animal Models in Neuroscience & Neuroengineering
Models for Investigating Traumatic Brain Injury · Model Factors for Investigating Neurotrauma · Animal Models of TBI · Tissue Models of TBI
Hypoxic/Ischemic Brain Injury – Bench to Bedside · Animal Models · EEG for monitoring injury/therapy · Hypothermia
Models of Spinal Cord Injury · SCI in Humans · Animal Models · Evoked Potentials Monitoring · Signal Processing for EPs
Introduction to the brain Optical Imaging · Optical Imaging of the Brain Blood Flow, Oxygenation and Metabolism · Brain: Structure and Functions · Introduction to the Brain Basic Functions
Intrinsic Optical Imaging (IOS) · Main sources of activity-dependent intrinsic signal · Experimental setup · Approaching of the IOS in animal experiments and in clinical practice.

Module Title & Topics

Cell and Tissue Models for Neuroscience & Neuroengineering

· Introduction to Cell Models

· Introduction to Tissue Models

· Example Tissue Models in Neuroscience & Neuroengineering

Animal Models for Neuroscience & Neuroengineering

· Introduction to Animal Models

· Selection of an Animal Model

· Example Animal Models in Neuroscience & Neuroengineering

Models for Investigating Traumatic Brain Injury

· Model Factors for Investigating Neurotrauma

· Animal Models of TBI

· Tissue Models of TBI

Hypoxic/Ischemic Brain Injury – Bench to Bedside

· Animal Models

· EEG for monitoring injury/therapy

· Hypothermia

Models of Spinal Cord Injury

· SCI in Humans

· Animal Models

· Evoked Potentials Monitoring

· Signal Processing for EPs

Introduction to the brain Optical Imaging

· Optical Imaging of the Brain Blood Flow, Oxygenation and Metabolism

· Brain: Structure and Functions

· Introduction to the Brain Basic Functions

Intrinsic Optical Imaging (IOS)

· Main sources of activity-dependent intrinsic signal

· Experimental setup

· Approaching of the IOS in animal experiments and in clinical practice.

Extrinsic Optical Imaging

· Voltage-sensitive dye optical imaging (VSDi)

· Calcium-sensitive dye optical imaging

· Genetically encoded indicator of the neural activity

Introduction to Connectomics

· Overall challenge

· Macroscale Connectomics

· Mesoscale Connectomics

· Nanoscale Connectomics

Nanoscale Connectomics Tools and Methods

· Large-Scale Storage

· Reproducible Pipelines

· Data Science

Nanoscale Connectomics Algorithms and Applications

· Machine Learning

· Algorithmic Approaches

· Graph Theory and Applications

Temporal Dynamics of Information Processing in the Human Brain

· Temporal Dynamics of Visual Object Recognition

· RSVP and the Attentional Blink

· EEG-based BCI: state classification and signal dimensionality

Semantic Decoding and “Mind Reading”

· Neural Representations of Concepts

· Semantic Feature Spaces

· Representational Similarity Analysis

Speech Encoding in Neural Systems

· Auditory feature encoding in cortex (comprehension)

· Cortical organization for speech articulation (production)

· Frequency Following Response

Course Goals

To familiarize with the some of the latest frontline research topics in the fast growing field of Neuroengineering.
To develop basic everyday skills required for researching the field of Neuroengineering, for example, reading, exploring, synthesizing, reproducing and critiquing a specific research topic in Neuroengineering
Identifying key methodologies in modern; actively researched scientific problems related with Neuroengineering and related technological advances.

Course Learning Outcomes (CLOs)

By the end of this course, you will be able to: • Identify some key elements in select frontline research issues in neuro-engineering • Explain the mostly incremental nature of scientific progress made in specific scientific publications • Explore, Read, Analyze, Review, and plausibly reproduce specific scientific works in Neuroengineering • Establish a scientific understanding of a few frontline topics in Neuroengineering research that are currently active at Hopkins.

Textbooks

Textbooks:

None Required. Module Instructors will provide reading material, notes etc.

Required Software

Technical Requirements

MATLAB: You will need access to a recent version of MATLAB. A license is provided at no cost to you, through JHU. Visit the JHU IT Services Portal. Log in with your JHED ID and type “MATLAB” in the search bar. Click on “MATLAB for Students” in the search results and follow the instructions provided.

You should refer to Help & Support on the course menu for a general listing of all the course technical requirements.

Student Coursework Requirements

Grading

Student assignments are due according to the dates in the Calendar and Assignments items in the corresponding modules. Dr. Maybhate will post grades one week after assignment due dates.

We generally do not directly grade spelling and grammar. However, egregious violations of the rules of the English language will be noted without comment. Consistently poor performance in either spelling or grammar is taken as an indication of poor written communication ability and carelessness that may impact your subsequent grade.

For written assignments (homework’s, project check-in, and project plan), late submissions will be reduced by one letter grade (e.g. A+ to A, A to A-, etc.) for each day late (No exceptions without prior coordination with the instructors).

A grade of A indicates achievement of consistent excellence and distinction throughout the course—that is, conspicuous excellence in all aspects of assignments and discussion in every week.

A grade of B indicates work that meets all course requirements on a level appropriate for graduate academic work. These criteria apply to both undergraduates and graduate students taking the course.

EP uses a “+/-“ grading system (see “Grading System”, Graduate Programs catalog, p. 10). 100-98 = A+; 97-94 = A; 93-90 = A−; 89-87 = B+; 86-83 = B; 82-80 = B−; 79-77 = C+; 76-73 = C; 72-70 = C−; 69-67 = D+; 66-63 = D; <63 = F. This course will use the same grading system.

Final grades will be determined by the following weighting:

Item	% of Grade	Details of % Distribution
Preparation and Participation - Office Hours Journal Club - Discussion Forum	10%	Journal Club and Office Hours Discussion; Discussion Forum Participation
Homework Assignments	45%	9 assignments with 5% weightage for each.
Multiple Choice Tests	45%	5 Multiple Choice Exams at the end of each respective instructor’s last module. (Module 3, 5, 8, 11, 14)

Grading Policy

EP uses a “+/-“ grading system (see “Grading System”, Graduate Programs catalog, p. 10). 100-98 = A+; 97-94 = A; 93-90 = A−; 89-87 = B+; 86-83 = B; 82-80 = B−; 79-77 = C+; 76-73 = C; 72-70 = C−; 69-67 = D+; 66-63 = D; <63 = F. This course will use the same grading system.

Academic Policies

Deadlines for Adding, Dropping and Withdrawing from Courses

Students may add a course up to one week after the start of the term for that particular course. Students may drop courses according to the drop deadlines outlined in the EP academic calendar (https://ep.jhu.edu/student-services/academic-calendar/). Between the 6th week of the class and prior to the final withdrawal deadline, a student may withdraw from a course with a W on their academic record. A record of the course will remain on the academic record with a W appearing in the grade column to indicate that the student registered and withdrew from the course.

Academic Misconduct Policy

All students are required to read, know, and comply with the Johns Hopkins University Krieger School of Arts and Sciences (KSAS) / Whiting School of Engineering (WSE) Procedures for Handling Allegations of Misconduct by Full-Time and Part-Time Graduate Students.

This policy prohibits academic misconduct, including but not limited to the following: cheating or facilitating cheating; plagiarism; reuse of assignments; unauthorized collaboration; alteration of graded assignments; and unfair competition. Course materials (old assignments, texts, or examinations, etc.) should not be shared unless authorized by the course instructor. Any questions related to this policy should be directed to EP’s academic integrity officer at ep-academic-integrity@jhu.edu.

Students with Disabilities - Accommodations and Accessibility

Johns Hopkins University values diversity and inclusion. We are committed to providing welcoming, equitable, and accessible educational experiences for all students. Students with disabilities (including those with psychological conditions, medical conditions and temporary disabilities) can request accommodations for this course by providing an Accommodation Letter issued by Student Disability Services (SDS). Please request accommodations for this course as early as possible to provide time for effective communication and arrangements.

For further information or to start the process of requesting accommodations, please contact Student Disability Services at Engineering for Professionals, ep-disability-svcs@jhu.edu.

Student Conduct Code

The fundamental purpose of the JHU regulation of student conduct is to promote and to protect the health, safety, welfare, property, and rights of all members of the University community as well as to promote the orderly operation of the University and to safeguard its property and facilities. As members of the University community, students accept certain responsibilities which support the educational mission and create an environment in which all students are afforded the same opportunity to succeed academically.

For a full description of the code please visit the following website: https://studentaffairs.jhu.edu/policies-guidelines/student-code/

Classroom Climate

JHU is committed to creating a classroom environment that values the diversity of experiences and perspectives that all students bring. Everyone has the right to be treated with dignity and respect. Fostering an inclusive climate is important. Research and experience show that students who interact with peers who are different from themselves learn new things and experience tangible educational outcomes. At no time in this learning process should someone be singled out or treated unequally on the basis of any seen or unseen part of their identity.

If you have concerns in this course about harassment, discrimination, or any unequal treatment, or if you seek accommodations or resources, please reach out to the course instructor directly. Reporting will never impact your course grade. You may also share concerns with your program chair, the Assistant Dean for Diversity and Inclusion, or the Office of Institutional Equity. In handling reports, people will protect your privacy as much as possible, but faculty and staff are required to officially report information for some cases (e.g. sexual harassment).

Course Auditing

When a student enrolls in an EP course with “audit” status, the student must reach an understanding with the instructor as to what is required to earn the “audit.” If the student does not meet those expectations, the instructor must notify the EP Registration Team [EP-Registration@exchange.johnshopkins.edu] in order for the student to be retroactively dropped or withdrawn from the course (depending on when the "audit" was requested and in accordance with EP registration deadlines). All lecture content will remain accessible to auditing students, but access to all other course material is left to the discretion of the instructor.