
Neural Data Science
A Primer with MATLAB® and Python™
Resources
Description
Key Features
- Includes discussions of both MATLAB and Python in parallel
- Introduces the canonical data analysis cascade, standardizing the data analysis flow
- Presents tactics that strategically, tactically, and algorithmically help improve the organization of code
Readership
Students, researchers and instructors in Systems, Cognitive and Behavioral Neuroscience, and Cognitive Psychology
Table of Contents
Part I: Foundations
Chapter 1. Philosophy
- Abstract
- What Is Data Science?
- What Is Neural Data Science?
- How Is Neural Data Science Different From Computational Neuroscience?
- Data as Seen by Data Scientists Versus Data Seen by Neural Data Scientists
- What Is a Neural Data Scientist?
- Why Do I Need to be Able to Write Computer Code?
- What Is Neural Data?
- Can We Just Add “Neuro” to the Front of Anything?
- Why Python?
- Why MATLAB?
- Why Not C/C++/R/Julia/Haskill/Java/Javascript/OCaml/Perl/Pascal/Fortran/Ruby/Groovy/Scala/etc.?
- What Is Industrial Data Science? How Is It Different From Engineering?
Chapter 2. From 0 to 0.01
- Abstract
- What Is the Goal of This Chapter?
- How Do I Get Started Coding?
- What’s the Command Line? What’s the Environment?
- How Are Python and MATLAB Different?
- How Do I Display Something on the Screen?
- How Do I Do Arithmetic in Python or MATLAB?
- How Do I Input Exponents in Python and MATLAB?
- What Is the Role of Blank Space in Writing Code, If Any?
- What Is the Order of Operations in Python and MATLAB?
- What Are Functions?
- What Are Python Packages? What Are MATLAB Toolboxes? Are These Different From Libraries?
- How Do I Get Help?
- What Are Variables?
- How Can I Access or Display What Is Contained in a Given Variable?
- What Is “ans” in MATLAB?
- What Can We Call Our Variables?
- What Is a Vector? How Do I Store a Vector in POM?
- How Do I Calculate the Sum and Mean of All Values in a Vector?
- We Need to Talk About the Echo
- How Do I Calculate the Length of a Vector?
- What Are Matrices, What Are Arrays?
- Back to Vectors: How to Vectorize a Matrix?
- What Can We Do With All of This?
- The Find Function
- Adding Matrices and Dealing With Holes in Arrays
- What Is a Normal Distribution? How Do We Draw From One, How Do We Plot One With POM?
- How Do I Plot Something More Meaningful?
- How Do I Save What I’m Working On so That I Can Load It Again Later?
Part II: Neural Data Analysis
Chapter 3. Wrangling Spike Trains
- Abstract
- Questions We Did Not Address
Chapter 4. Correlating Spike Trains
- Abstract
Chapter 5. Analog Signals
- Abstract
Chapter 6. Biophysical Modeling
- Abstract
- Biophysical Properties of Neurons
- Modeling
- Why Use Simulations?
- Why Object-Oriented Programming?
- Python Is Inherently Object-Oriented: How Does MATLAB Implement These Things?
- Creating theclass Neuron
- Modeling the Response Properties of This Neuron
Part III: Going Beyond the Data
Chapter 7. Regression
- Abstract
- Describing the Relation Between Synaptic Potentials and Spikes
Chapter 8. Dimensionality Reduction
- Abstract
- Calculating the Covariance Matrix Between Variables
- Factor Extraction as an Axis Rotation
- Determining the Number of Factors
- Interpreting the Meaning of Factors
- Determining the Factor Values of the Original Variables
Chapter 9. Classification and Clustering
- Abstract
- Predictions, Validation, and Crossvalidation
- Clustering
Chapter 10. Web Scraping
- Abstract
- What Lies Beyond 1?
Appendix A. MATLAB to Python (Table of Equivalences)
- Comments
- Blankspace
- Loops
- Exponents
- Lists and Cells
- Indexing
- Importing Packages Versus Default Packages
- Random Number Generation
- Numerical Types
Appendix B. Frequently Made Mistakes
Appendix C. Practical Considerations, Technical Issues, Tips and Tricks
- Package Installation
- Python List Comprehensions
- Python Lists Versus Numpy Arrays
- Text Editors, The Command Line, How to Go between Sublime and the Terminal
- Python on Windows
- Jupyter: Using It and Its Great Functions
- The Biggest Differences Between Python 2 and 3
- Conventions in Python
- MATLAB Tips and Tricks
- Vectorization
- Practical Considerations
Glossary (Including Additional Python and MATLAB Packages and Examples)
Product details
- No. of pages: 368
- Language: English
- Copyright: © Academic Press 2017
- Published: February 24, 2017
- Imprint: Academic Press
- eBook ISBN: 9780128040980
- Paperback ISBN: 9780128040430
About the Authors
Erik Nylen
Affiliations and Expertise
Pascal Wallisch
