L&S 88 Data Science for Cognitive Neuroscience

A Spring 2017 Data Science Connector Course

CCN:34414 | Fatma (Imamoglu) Deniz, Leila Wehbe, Mark Lescroart | Tuesday 1:00-3:00 PM | Evans B6 | Units: 2

Information

Welcome to Data Science for Cognitive Neuroscience! This page will contain links to course materials and to the bCourses website. The latest syllabus is below.

• Install the latest neurods package
• A Description of Our Datasets
• bCourses site

Calendar
Date	Module	Lecture Slides/Notebooks	Lab	Notes
1/24	Introduction to Cognitive Neuroscience	Slides01		Notepad01
1/31	Introduction to functional magnetic resonance imaging (fMRI)	Lecture02 Lecture02 with breakout sessions	Lab02 Lab02 solution	Notepad02
2/07	Data manipulation in 3D	Lecture03 Lecture03 with breakout sessions	Lab03 Lab03 solution	Notepad03
2/14	Data normalization, logical indexing, surface visualization	Lecture04 Lecture04 with breakout sessions	Lab04 Lab04 solution	Notepad04
2/21	Masking and Event-related averages	Lecture05 Lecture05 with breakout sessions	Lab05 Lab05 solution	Notepad05
2/28	EEG introduction, event-related averages in EEG	Lecture06 Lecture06 with breakout sessions	Lab06 Lab06 solution	Notepad06
3/7	Data interpretation	Lecture07 Lecture07 with breakout sessions	(No HW this week)	Notepad07
3/14	Midterm	Midterm Exam	(No HW this week)	(No notepad this week)
3/21	Hemodynamic response function and convolution	Lecture08 Lecture08 with breakout sessions	Lab08 Lab08 Solution	Notepad08
4/4	Correlation, Regression and Modeling	Lecture09	Lab09 Lab09 solution	Notepad09
4/11	Multiple Regression and Hypothesis Testing	Lecture10 Lecture10 breakout	Lab10 Lab10 solution	Notepad10
4/18	Encoding Models Using Complex Stimuli	Lecture11 Lecture11 with breakout sessions	Lab11 Lab11 Solution	Notepad11
4/25	Encoding Models Using Complex Stimuli	Lecture12 Lecture12 breakout	Final Review (w/ potential extra credit) Final Review Hints Final Cheat Sheet Final Review solutions	Notepad12
5/11	Final	Final Exam	(No HW this week)	(No notepad this week)

Course Description

The human brain is a complex information processing system and is currently the topic of multiple fascinating branches of research. Understanding how it works is a very challenging scientific task. In recent decades, multiple techniques for imaging the activity of the brain at work have been invented, which has allowed the field of cognitive neuroscience to flourish. Cognitive neuroscience is concerned with studying the neural mechanisms underlying various aspects of cognition, by relating the activity in the brain to the tasks being performed by it. This typically requires exciting collaborations with other disciplines (e.g. psychology, biology, physics, computer science).

You should take this course if you’re interested in how the brain works and how you can use cutting edge brain imaging and data analysis tools to study it. During this course, you will learn tools based on the python programming language to understand, manipulate, and explore human brain recordings (such as ECoG, EEG, MEG and fMRI). You will learn to formulate hypotheses about how the brain represents information and then test these hypotheses using real world data. You will learn useful analysis methods to help you derive conclusions from brain recording data.

By giving you first hand experience in data analysis of brain data, this course will provide you an insight into the experiments and data used in the cognitive neuroscience field. It will allow you to build a better understanding of the current cutting edge research in cognitive neuroscience. Hence, you will be able to keep up with recent advances in this field and/or will be able to apply your knowledge by doing research here at Berkeley. Additionally, the data analysis techniques and the investigation approaches that you will learn will be easily transferable to research in other disciplines.