Highlighted Spring Courses: 2023

*Note: The course information below has been provided to us by faculty members and we will update this page on a regular basis. If you are a student who would like additional courses highlighted for your colleagues please contact the GPN Administrative Coordinator Lavell Blackwell (lblackwe@bu.edu).

CAS PS 504 A1 – Trends in Contemporary Psychology

Contact Information:  Dr. Robert Wozniak (rwozniak@bu.edu)

Lecture/discussion:  Mon, 2:30 pm – 5:15 pm

Location: Contact Dr. Wozniak

Course description: This course will explore the molecular and neural circuit mechanisms responsible for driving movement and selecting actions to achieve goals.  We will examine how central nervous systems represent and control movement at multiple levels and how action plans are learned, selected, and executed on the basis of internal goals and changing sensory environments. Where appropriate, we will also discuss how neural disorders of motivation and movement, such as Parkinson’s Disease, arise from the disruption of different neural circuits.  There will be a heavy focus on primary scientific literature covering the latest advances in the field, so prior coursework in neurobiology is highly recommended. 4 credits

 

CAS PS 530 A1 – Neural Models of Memory Function

Contact Information: Dr. Michael Hasselmo (hasselmo@bu.edu)

Lecture/discussion: Thurs, 3:30 pm – 6:15 pm

Location: Contact Dr. Michael Hasselmo

Course description: Computational models of neurobiological mechanisms for memory function and spatial navigation, with a particular emphasis on cellular and circuit models of the hippocampus and related cortical structures. Also offered as CAS NE 530. 4 credits

Prereq: consent of instructor.

 

CAS CN 530 A1 – Neural and Computational Models of Vision

Contact Information:  Dr. Arash Yazdanbakhsh (yazdan@bu.edu)

Lecture/discussion:  Mon & Wed, 10:10 am – 11:55 am 

Location: Contact Dr. Yazdanbakhsh 

Course description: This course explores the psychological, biological, mathematical and computational foundations of visual perception. Lectures and readings combine with simulation and essay assignments to provide an intensive and self-contained examination of core issues in early and middle visual processing. Mathematically specified neural and computational models elucidate the structure and dynamics of the mammalian visual system. The course elucidates the psychophysics and physiology of mammalian vision, both as a means of better understanding our own human intelligence, and as a foundation for tomorrows machine vision architectures and algorithms. 4 credits

Prereq: (CASCN510) or consent of instructor.

 

GRS PS 704 B1Contemporary Trends in Psychology – Physics of the Mind

Contact Information: Dr. Marc Howard (marc777@bu.edu)

Lecture/discussion: Thurs, 3:30pm – 6:15 pm

Location: Contact Dr. Howard

Course description: Computational cognitive neuroscience: A modern perspective This course will start with a review of classic mathematical models, including temporal difference learning, short-term memory maintenance, and sequential sampling and the neurophysiological results they have inspired.  Following this introduction, we will attempt to unify these different models in a framework based on function representation utilizing the Laplace transform.  We review computational models for a range of behavioral tasks and the prospects for a unified theory of cognitive computation. Students should have at least some familiarity with differential equations and linear algebra. 4 credits

 

GRS NE 741 A1 – Neural Systems: Functional Circuit Analysis

Contact Information: Dr. Ian Davison (idavison@bu.edu)

Lecture/discussion:  LEC  Thursday, 12:30 pm – 3:15 pm,                            DIS  Friday, 10:10 am – 11:00 am

Location: Contact Dr. Davison

Course description: An in-depth survey of powerful new approaches for understanding nervous system function, linking neural activity to behavior. Topics include anatomical connectivity, behavioral methods, and both recording and manipulating the activity of neural populations. Required course for 2019 entering GPN class. 4 credits

 

GRS NE 742 A1 Neural Systems: Cognition and Behavior

Contact Information: Dr. Chantal Stern (chantal@bu.edu)

Lecture/discussion: Tues, 3:30 pm – 6:15 pm

Location: Contact Dr. Stern

Course description: Surveys current neuroscience research. The goal is to develop an understanding of nervous system function in animals and humans, linking cellular and systems level neural circuitry to cognition and behavior. 4 credits

Grad Prereq: graduate standing in Neuroscience, or Brain, Behavior, and Cognition,or Neurobiology; or consent of instructor.

 

SAR HS 582 A1 – Neuroanatomy and Neurophysiology

Contact Information:  Dr. Basilis Zikopoulos (zikopoul@bu.edu)

Lecture/discussion:  Tues & Thurs, 2:00 pm – 3:15 pm

Location: Contact Dr. Zikopoulos

Course description: Lecture and laboratory related to the detailed study of the development, morphology, internal configuration, functions, and pathological deficits of the peripheral and central nervous system in humans. Spring semester only. 4 credits

 

SAR HS 755 A1 – Readings in Neuroscience

Contact Information:  Dr. Helen Barbas (barbas@bu.edu)

Lecture/discussion:  Tues, 6:30 pm – 9:15 pm

Location: Contact Dr. Barbas

Course description: Review of basic principles of neuroscience at an intermediate level, followed by readings and discussion on topics from the current neurosciences research. 4 credits, 2nd semester every other year

Grad Prereq: Consent of instructor.

 

 SPH BS 704 A1 Introduction to Biostatistics

Contact Information: Dr. Sarah Leatherman (smkarl@bu.edu)

Lecture: Monday, 6:00 pm – 8:20 pm

Location: Contact Dr. Sarah Leatherman 

Description: This course provides an overview of biostatistical methods, and gives students the skills to perform, present, and interpret basic statistical analyses. Topics include the collection, classification, and presentation of descriptive data; the rationale of estimation and hypothesis testing; analysis of variance; analysis of contingency tables; correlation and regression analysis; multiple regression, logistic regression, and the statistical control of confounding; sample size and power considerations; survival analysis. Special attention is directed to the ability to recognize and interpret statistical procedures in articles from the current literature. Students will use the R statistical package to analyze public health related data. 3 cr

 

GMS PM 820 A1 – Behavioral Pharmacology

Contact Information:  Dr. Valentina Sabino (vsabino@bu.edu)

Lecture/discussion:  Fri. 3:00 pm – 4:50 pm

Location: Contact Dr. Sabino (MED Campus)

Course description: This course examines the interaction between behavior and classes of drugs that affect the central nervous system. Emphasis is given to how behavioral studies assist understanding of mental disorders, including addictions, pain syndromes, depression and dementia. Faculty overview of a topic is followed by student- led discussion of an assigned research paper. 2 credits

 

GRS MA 765 A1 – Time Series Analysis for Neuroscience Research

Contact Information: Dr. Emily P. Stephen (estephen@bu.edu)

Lecture/Discussion: Tues/Thurs 9:30-10:45am

Course description: Provides an overview of statistical time-series modeling for neuroscience applications. Topics include regression and generalized linear modeling, state space modeling, and parametric and nonparametric spectral analysis. Special emphasis on reading and discussing applications in recent literature. 4 cr

Prereq:  CAS MA 213 or GRS MA 681CAS MA 242CAS MA665/MA666; or consent of instructor.

 

Karin SchonGMS AN 811 A1 – Cognitive Neuroscience      Robert Joseph

Contact Information: Dr. Karin Schon (kschon@bu.edu), Dr. Robert Joseph (rcjoseph@bu.edu)

Lecture/Discussion: Mon 10:30am-12:20pm/Thurs 3:30-5:30pm

Course Description: Cognitive neuroscience seeks to understand the brain basis of cognition. This course will cover topics in the various domains of higher cognitive function, including attention, language, visuospatial abilities, memory, and executive function/cognitive control. It will also cover topics in social cognition, including unconscious bias, emotion, sensation and perception, methods of cognitive neuroscience, and disorders of cognition. In addition, we will explore the broader impact of cognitive neuroscience on society. 4 cr