Graduate Courses

Courses:

Principles of Neuroscience I

Course Leader(s):
Bryen Jordan 
Alberto Pereda 

Credits/Class Meetings: 6 credits; Summer-Fall, Aug 19th - Nov 19th, Tuesdays, Thursdays, Fridays, 2:00-4:00pm, 2 hrs per class

Course Description: Principles of Neuroscience I is a highly-interactive 13-week course required for students in the Department of Neuroscience. The course offers a multidisciplinary approach to the study of the nervous system from first principles with a focus on the molecular and cellular basis of brain function. Topics include fundamental principles underlying neuronal excitability, mechanisms of electrical and synaptic neurotransmission, the cells of the brain and their role in neurotransmission, and the architecture of the central nervous system. The class format consists of a combination of formal and informal lectures and student presentations with a major emphasis on interactive class discussion. The course requires active student participation during the class and offers review sessions if needed. This course uses the Canvas online discussion forum, where assignments are often given to expand on topics covered in class. In addition to normal course scheduled lectures, the course includes lab visits and students are also required to prepare and present at a symposium on a specific topic and to attend the weekly Neuroscience Seminar Series.

Prerequisites: None

Course Objectives: 

  • Understand the chemical and electrical principles that lead to neuronal excitability
  • Understand the principles that underlie neurotransmission, and understand how non-neuronal cells support this process
  • Understand the molecular and cellular mechanisms the give rise to neurotransmission, and how input leads to short and long-term changes in neuronal function

Suitability for 1st Year Students: Yes

Grading: Attendance and class participation, 25%; presentations 25%; final exam 50%. The Final Exam must be passed to pass the course. However, this is not sufficient. Active participation in class and well-prepared presentations will also be assessed and considered for passing. Students who are not sufficiently participating will be informed by the course leaders to provide them with the opportunity to increase their class participation.

 

Principles of Neuroscience II

Course Leader(s):
Adam Kohn 
Jose Pena 
Ruben Coen-Cagli 

Credits/Class Meetings: 6 credits; Fall-Spring, Nov 29th - Mar 8th, Tuesdays, Thursdays, Fridays, 2:00-4:00pm, 2 hrs per class

Course Description: Principles of Neuroscience II is a 13-week course required for students in the Department of Neuroscience. In this course, students will explore how complex neural systems integrate afferent information and direct efferent outflow. The overall goal will be to explore higher order functions, such as the structure and function of neural systems underlying sensation and movement, learning and memory at the sensory and motor levels, as well as higher-level cognitive processes including object perception and attention. Student knowledge in these areas will be built on a firm understanding of the underlying physiology and anatomical structure. Principal areas of interest will be on hierarchical neural systems, the plasticity of neural networks, serial and parallel neural processing, cognition and computational modeling.

Prerequisites: Principles of Neuroscience I

Suitability for 1st Year Students: Yes

Grading: Your grade in this course will be based on participation in class, the midterm grant proposal, the written critiques, and the final grant proposal.

 

Nanocourses:

Approaches to Study Neural Circuits in Behaving Animals

Course Leader(s):
Anita Autry 
Lucas Sjulson 

Credits/Class Meetings: Spring, Mar 17th - May 5th, Tuesdays, Thursdays, 2 hrs per class

Course Description: This course will introduce students to techniques for in vivo recording of neural activity and approaches to define connectivity and expression profiling of neurons. Emphasis on techniques, instrumentation, and data analysis (demos for analysis). We will introduce the basics of measurement and instrumentation for in vivo physiology, in vivo calcium imaging, and introduce methods for manipulation, anatomy, and expression profiling of neurons. A key motivation in going over the techniques will be to compare methods for recording and manipulation (i.e. physiology versus imaging, optogenetics versus chemogenetics) in terms both of the mechanisms at the level of individual neurons and how that manipulation will impact resulting data and interpretation of behavioral/activity outcomes. Course meetings will be lectures to go over the basic information as well as hands on demonstrations with equipment and example data analysis. Students will be evaluated based class participation and on a final presentation (around 15 minutes) of recent advances in the application or analysis of one of the techniques discussed in class.

Prerequisites: Principles of Neuroscience I and II

Course Objectives: 

  • understand principles of measurement and analysis
  • understand the advantages and limitation of specific approaches for neural recordings
  • get hands-on experience handling data sets from in vivo recording experiments
  • understand the advantages and limitations of methods for manipulating neurons 
  • become versed in visualizing and interpreting data from neural recording and neural manipulation experiments

Required Material(s): If students would like to follow along with data analysis demonstrations, a computer and free software (TBA) will be required. Demos will also be shown on-screen.

Suitability for 1st Year Students: Yes - Priority enrollment is given to graduate students, but postdocs and others are welcome if the maximum enrollment has not been reached.

Grading: Students will be assessed based on in-class participation and a final presentation (75% participation; 25% final presentation). Participation will be assessed by daily or weekly reflections on Canvas, that will include short summaries of the main points covered in that week, and assessment of lab notebook.

Attendance and Participation: No more than one unexcused absence will be allowed. All absences (excused or otherwise) must be “made-up” by completing the requisite work completed in class.

 

The Cellular, Molecular and Genetic Basis of Neurological and Psychiatric Disorders

Course Leader(s):
Herb Lachman 
 

Credits/Class Meetings: Summer, Jun 2nd - June 25th, Tuesdays, Thursdays, 2 hrs per class. Each session will begin with a didactic lecture lasting 1-1.5 hours, followed by students/lecturer questions and answers

Course Description: This block will be subdivided into four, weekly sessions devoted to neurological and psychiatric disorders, as follows: Psychiatric disorders (schizophrenia, bipolar disorder, addiction) Speech and hearing disorders; auditory processing Neurodegenerative disorders (e.g., Alzheimer Disease, Parkinson Disease, Huntington Disease) Neurological disorders (e.g., epilepsy, stroke) The lectures will combine a clinical description of the disorders with the modern approaches being used to understanding their molecular and genetic basis, for the purpose of developing novel therapies. The methods that will be discussed include genome wide association studies (GWAS), copy number variant (CNV) analysis, whole genome and exome sequencing, induced pluripotent stem cell disease-modeling, CRISPR-editing, high throughput drug screening using human neuronal cells, regenerative medicine, and gene therapy/antisense oligonucleotides.

Prerequisites: None

Course Objectives: Acquaint Ph.D. students with the clinical features of various neurological and psychiatric disorders, which are among the most disabling disorders in the world, and show how the tools of modern basic science research are being used to develop novel therapies.

Required Material(s): Suggested reading: Each lecture will be accompanied by one article; either a review or a relevant research paper related to that particular lecture.

Suitability for 1st Year Students: Yes - Priority enrollment is given to graduate students, but postdocs and others are welcome if the maximum enrollment has not been reached.

Grading: 40% of the final grade will be based on attendance and class participation. At the end of each class, the students are expected to upload a short (250 word) paragraph to canvas on what they have learned in class. 60% of the final grade will be based on a mock grant proposal on any topic related to neurological or psychiatric disorders. The mock grant proposal will be graded based on the writeup (50%) and on an oral 10-20 minute presentation of the proposals (duration of each presentation will depend on the number of students taking the course) (50%).

Attendance and Participation: No more than one unexcused absence will be allowed. All absences (excused or otherwise) must be “made-up” by completing the requisite work completed in class.

 

Data Analysis in Neuroscience

Course Leader(s):
Maria Gulinello 

Credits/Class Meetings: Summer, Jun 1st - June 26th, Mondays, Wednesdays, Fridays, 1.5 hrs per class

Course Description: Targeted to the needs of Neuroscience graduate students, this course compliments and expands on existing mathematical-based instruction with practical, “plain English” explanations in order to provide the skill requisite to applying and interpreting statistical concepts appropriately. Actual data sets (provided by neuroscience faculty, open data sources and the students) and hands-on data visualization and analyses in each session provide real-world examples of the typical and unique challenges faced in experimental neuroscience.

Prerequisites: None, though undergraduate statistics are recommended

Course Objectives: 

  1. Practical experience, through the use of actual data-sets (detailed below), in choosing appropriate data analysis tools and statistical models for typical data encountered in neuroscience studies. 
  2. Choosing the Correct Statistical Tests: Mastery of the implications, pros and cons, assumptions and limitations of various statistical models. Effective and transparent data visualization and illustration. 
  3. Application of statistical principles to pre-registration and experimental design (including power analysis). 
  4. Learning to correctly report statistical data – learning to interpret and understand statistical data reporting and identify errors and false assumptions in published and presented data. 
  5. Avoiding common pitfalls. 
  6. Application of these basic principles to complicated data sets for the greatest transparency and rigor.

Required Material(s): Computer (either Macintosh or Windows platform) – contact the course director if this is an issue. JMP (SAS) will be provided by the department.

Suitability for 1st Year Students: Yes - Priority enrollment is given to graduate students, but postdocs and others are welcome if the maximum enrollment has not been reached.

Grading: Weekly HW assignments – 20% of grade 2 take home exams 80% of grade (one mid, one final) Feedback given for each assignment and in class. Problem sets with feedback in class. Other formative assessments include – daily or weekly reflections on Canvass, short summaries of the main points covered in that week. Assignments may include webinar type instructional videos for how to use the software (although in class instruction is provided). 

  Objective Assessments: 

  • Summative assessments = 2 exams. 
  • Formative assessments - weekly HW and in class exercises in software use, data analysis and data management. 

   Subjective assessments: Will be assessed before and after the class. 

  • Familiarity with, and confidence in judging and evaluating the suitable models available for statistical analysis. 
  • Familiarity with and confidence in evaluating statistical data reported in seminal and relevant publications. 
  • Completes the worksheets, analysis in class correctly and demonstrates sufficient familiarity with software features 
  • Reflections will be requested weekly. 
   It should be noted here that despite the fact that many students have a decent rote understanding of the mathematical formulae and assumptions underlying basic statistics, they do not recognize these in the real world and express a profound (and accurate) lack of confidence about the application of these basic principles in their daily work.

Attendance and Participation: No more than one unexcused absence will be allowed. All absences (excused or otherwise) must be “made-up” by completing the requisite work. No more than 3 excused absences per session. The data sets and resulting analysis should have been completed during each class session, with appropriate guidance to a reasonable standard. Students will be required to upload these to Canvas.

 

Introduction to Developmental Neuroscience

Course Leader(s):
Şölen Gökhan
Mark Mehler 

Credits/Class Meetings: Spring, Mar 18th - April 24th, Mondays, Wednesdays, Fridays, 2 hrs per class

Course Description: The goals of the Developmental Neuroscience course are the study of:

  1. Central nervous system development with a focus on mammalian cerebral cortex development. 
  2. Neural stem cell mediated neuronal and glial cell type elaborations during development and adult brain. 
  3. Cellular and molecular processes regulating the elaboration of these neuronal and glial cell types. 
  4. Roles of non-neural cells, microglia during development and in the maintenance of homeostasis in adult central nervous system.

Prerequisites: None.

Course Objectives:   

  1. Understanding molecular processes giving rise to the three dimensional structure and cellular diversity of CNS.
  2. Utilization of this knowledge in devising new regenerative strategies including the utilization of iPSCs and organoids to understand ant treat neurodegenerative diseases. 

Required Material(s): Requisite readings will need to be completed prior to each class session.

Suitability for 1st Year Students: Yes - Priority enrollment is given to graduate students, but postdocs and others are welcome if the maximum enrollment has not been reached.

Grading: Class Participation: 50%. Essay format final exam: 50%.

Attendance and Participation: Participation will be assessed by weekly reflections on Canvas, that will include short summaries of the main points covered in that week. Students cannot miss more than 1 class and those who are at risk of failing will be notified as necessary.

 

Techniques in Human Neuroscience

Course Leader(s):
Sophie Molholm
Elyse Sussman 

Credits/Class Meetings: Spring, Apr 28th - May 21st, Tuesdays, Thursdays, 2 hrs per class

Course Description: This course will provide a survey of current methodologies used in the study of human neuroscience and behavior. These include functional magnetic resonance imaging (fMRI), diffusion tensor imaging (DTI), functional near-infrared spectroscopy (fNIRS), event-related brain potentials, mobile brain/body imaging (MOBI), and clinical assessments. Lectures will focus on the tools and techniques used to understand brain systems that enable memory, attention, language, scene perception, and executive functions, and the development of these processes across the lifespan.

Prerequisites: None.

Course Objectives: 

  1. Learn the range of methodologies used to investigate the brain basis of human cognition.
  2. Identify strengths and limitations in the study of complex brain functions.

Required Material(s): Suggested reading: The Cognitive Neurosciences, 5th Edition (2014). Eds: Michael S. Gazzaniga and George R. Mangun. MIT press, Cambridge MA

Suitability for 1st Year Students: Yes - Priority enrollment is given to graduate students, but postdocs and others are welcome if the maximum enrollment has not been reached.

Grading: Grades will be based on attendance (10%) class participation (30%) and presentation of a paper that includes the strengths and weaknesses of the technique for answering questions about human behavior (60%). Participation will be assessed by daily or weekly reflections on Canvas, that will include short summaries of the main points covered in that week.  

Attendance and Participation: Students cannot miss more than 1 class. All absences (excused or otherwise) must be "made-up" by completing the requisite work completed in class.