Fall 2023 Featured Courses


GRS MA 665 A1 –Introduction to Modeling and Data Analysis in Neuroscience, Sept 5- Oct 24

Description: An introduction to the basic techniques of quantifying neural data and developing mathematical models of neural activity. Major focus on computational methods using computer software and graphical methods for model analysis. Prereq: (CASMA122 OR CASMA124) or equivalent, and graduate standing, or consent of instructor

Contact Information: Mark Kramer mak@math.bu.edu

Lecture: Tue/Thu,12:30pm-1:45 pm

GRS MA 666 A1-Advanced Modeling and Data Analysis in Neuroscience, Oct 26-Dec 12

Description: Advanced techniques to characterize neural voltage data and analyze mathematical models of neural activity. Major focus on computational methods using computer software and graphical methods for model analysis. Prereq:(CASMA226 OR CASMA231) or equivalent. Graduate standing required, or consent of instructor.

Contact Information: Mark Kramer mak@math.bu.edu

Lecture: Tue/Thu,12:30pm-1:45 pm           


GRS MA 681 A1 – Accelerated Introduction to Statistical Methods for Quantitative Research

Contact Information: TBD

Lecture: Tue/Thu, 9:30 am – 10:45 am

Discussion: GRS MA681 A2, AC Stat Methods, Monday, 1:25 pm – 2:15 pm          

Discussion: GRS MA681 A3, AC Stat Methods, Monday, 2:30 pm – 3:20 pm         

Description: Introduction to statistical methods relevant to research in the computational sciences. Core topics include probability theory, estimation theory, hypothesis testing, linear models, GLMs, and experimental design. Emphasis on developing a firm conceptual understanding of the statistical paradigm through data analyses. 4 cr

SPH BS 704 A1 – Introduction to Biostatistics

Contact Information: Dr. Sarah Van Ness Leavitt (sv1205@bu.edu)

Lecture: Monday, 6:00 pm – 8:20 pm

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

CAS BI 598 A1 – Neural Circuits

Contact Information: Dr. Alberto Cruz-Martin (acmartin@bu.edu)

Lecture: Tue/Thu, 9:00 am – 10:45 am

Description: Reviews modern techniques and toolsets that are capable of dissecting neural circuits, which are critical for understanding how coordinated patterns of neural activity lead to complex behavior. Recent literature on information processing, guided behavior and cognition is discussed. Also offered as CAS NE 598. 4 cr.

CAS CN 510 A1 – Principles and Methods of Cognitive and Neural Modeling

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

LEC:  Tue/Thu, 11:00 am – 12:15 pm


Description: Explores psychological, biological, mathematical, and computational foundations of behavioral and brain modeling. Topics include organizational principles, mechanisms, local circuits, network architectures, cooperative and competitive non-linear feedback systems, associative learning systems, and self-organizing code-compression systems. The adaptive resonance theory model unifies many course themes. CAS CN 510 and 520 may be taken concurrently. 4.0 credits.

SAR SH 523 A1 – Introduction to Speech Science

Contact: Cara Stepp cstepp@bu.edu

Lecture/discussion: Mon/Wed, 12:20 pm – 2:05 pm          

Location: Contact Cara Stepp

Description: Lecture, laboratory, and demonstrations. Introduction to the basic physics of sound, including the decibel scale, spectral analysis, and resonance. Includes speech production, speech perception and suprasegmental effects. 4 cr

Prereq: (SARSH221 & SARSH522)