KRIGOLSON TEACHING
  • NEUROSCIENCE
    • NEUROSCIENCE 100 >
      • NEURO 100 INTRODUCTION
      • NEURO 101 ADVANCED
      • NEURO 102 AGING
      • NEURO 103 MEMORY
      • NEURO 104 DECISION MAKING
      • NEURO 105 LEARNING
      • Research Statistics
    • NRSC 500B / MEDS 470
  • Kinesiology
    • EPHE 245 >
      • LABORATORY
      • PRACTICUM
    • EPHE 357
  • STATISTICS
    • LECTURE >
      • INTRODUCTION TO R
      • DESCRIPTIVE STATISTICS
      • VISUALIZING DATA
      • Correlation and Regression
      • MULTIPLE REGRESSION
      • LOGIC OF NHST
      • T TESTS
      • ANOVA
      • POST HOC ANALYSIS
      • NON PARAMETRIC STATISTICS
      • FACTORIAL ANOVA
      • Repeated Measures ANOVA
      • Mixed ANOVA
      • MULTIVARIATE ANOVA
      • THE NEW STATISTICS
      • Bayesian Methods
    • ASSIGNMENTS >
      • Introduction to R >
        • INTRODUCTION TO R
        • LOADING DATA
        • DATA TABLES
      • Descriptive Statistics >
        • Mean, Median, and Mode
        • VARIANCE
        • CONFIDENCE INTERVALS
        • SHORTCUTS
      • Visualizing Data >
        • PLOTTING BASICS
        • BAR GRAPHS
        • BOXPLOTS
        • HISTOGRAMS
        • USING GGPLOT I
        • USING GGPLOT II
        • USING GGPLOT III
      • Correlation and Regression >
        • CORRELATION
        • REGRESSION
      • MULTIPLE REGRESSION >
        • MULTIPLE REGRESSION
      • Logic of NHST >
        • Sample Size and Variance
        • DISTRIBUTIONS
        • TESTING DISTRIBUTIONS
      • T-Tests >
        • Single Sample TTests
        • Paired Sample TTests
        • Independent Sample TTests
      • ANOVA >
        • ANOVA ASSUMPTIONS
        • ANOVA
      • POST HOC ANALYSIS >
        • POSTHOC ANALYSIS
      • NON PARAMETRIC STATISTICS >
        • WILCOXON TEST
        • WILCOXON SIGNED TEST
        • MULTIPLE GROUPS
      • FACTORIAL ANOVA
      • REPEATED MEASURES ANOVA >
        • RM ANOVA
        • TREND ANALYSIS
      • MIXED ANOVA
      • MULTIVARIATE ANOVA
      • THE NEW STATISTICS
      • BAYESIAN TTESTS
    • RESOURCES
    • R TIPS
  • Directed Studies
    • Advanced Topics in Motor Control A
    • Advanced Topics in Motor Control B
    • An Introduction to EEG
    • Advanced EEG and ERP Methods
    • Neural Correlates of Human Reward Processing
    • Independent Research Project
  • MATLAB
    • THE BASICS >
      • Hello World
      • BASIC MATHEMATICS
      • VARIABLES
      • Matrices
      • Writing Scripts
      • PATHS AND DIRECTORIES
      • USER INPUT
      • FOR LOOPS
      • WHILE LOOPS
      • IF STATEMENTS
      • RANDOM NUMBERS
    • STATISTICS >
      • LOADING DATA
      • DESCRIPTIVE STATISTICS
      • MAKING FUNCTIONS
      • BAR GRAPHS
      • LINE GRAPHS
      • TTESTS
    • EXPERIMENTS: THE BASICS >
      • DRAWING A CIRCLE
      • DRAWING MULTIPLE OBJECTS
      • DRAWING TEXT
      • DRAWING AN IMAGE
      • PLAYING A TONE
      • KEYBOARD INPUT
      • BUILDING A TRIAL
      • BUILDING TRIALS
      • NESTED LOOPS
      • RIGHT OR WRONG
      • SAVING DATA
    • EXPERIMENTS: ADVANCED >
      • STROOP
      • N BACK
      • Oddball
      • Animation
      • VIDEO
    • EEG and ERP Analysis >
      • ERP Analysis
  • RESOURCES
    • EXCEL
    • HOW TO READ A RESEARCH PAPER
    • HOW TO WRITE A RESEARCH PAPER
  • Workshops
    • Iowa State EEG Workshop 2018
  • Python
    • The Basics >
      • Setting Up Python
      • Hello, world!
      • Basic Math & Using Import
      • Variables
      • Matrices
      • Scripts
      • User Input
      • For Loops

Additional Material

Please note that all of the material here is "additional" - it is not required course content - it is here to improve your understanding of course material, improve the depth of your understanding, and to help those in search of the elusive "A+".
Administrative Material
EPHE 245 Exam One Two Grading Rubric
EPHE 245 Final Exam Grading Rubric
Sample Long Answer (NOTE: This is not for one of your three questions, this is for a question from a previous year. However, examine the QUANTITY, the use of diagrams and examples, and importantly how research was integrated into the answer).

Introduction
Paper: Vint, 2010
Watch: The Real Reason for Brains
Learning in the News: The Case for Banning Laptops in the Classroom
For Humour: How Not to Email a Professor

INTRODUCTORY MATERIAL

1. Repetition and Expertise
Paper: Ericcson, Krampe, and Tesch-Roemer, 1993
Paper: Deliberate Practice in Sport
Opinion: The Problem with Repetition
Video: Michael Jordan on Expertise

2. Feedback
Paper: The Benefits of a Reduced Feedback Schedule (Winstein & Schmidt 1990)
Video: The Stages of Motor Learning
Paper: Using Feedback to Enhance Learning
Paper: Inside the Brain of an Elite Athlete
TED Talk: The Importance of Feedback for Learning

3. Human Memory
Webpage: Explicit and Implicit Memories
Webpage: Human Memory
Research Paper: Procedural Memory Consolidation
Research Paper: Sleep and Motor Memory

4. Motor Programs
Paper: Current Status of Motor Programs (Summers and Anson, 2009) 
Website: The Schwartz Laboratory
Book: Motor Program Theory
Video: GMP Theory
Research Article: Generalized Motor Programs

5. Distributed Practice and Random Practice

Paper: The Benefits of Distributed Practice (Baddeley and Longman, 1978)
Paper: Review of Massed and Distributed Practice (Murray and Udermann, 2003)
Sport Canada: Guide for the Use of Massed and Distributed Practice

Video: Why Distributed Practice Works​
Article: Practice Scheduling and Surgery
Paper: The Use of Random Practice in Baseball (Hall et al., 1994)
​Article: A Critique on RP and KR

6. Variable and Part Practice
Volleyball Canada: Guide to Using Part versus Whole Practice
Video: 
Variable Practice and Practice Specificity
Research Article: Variable Practice and Tennis
Research Article: Why Variable Practice Works
Website: Schema Theory and Motor Programs
Research Article: Hansen et al. 2005
Book Chapter: Part versus Whole Practice
Research Article: Park 2002
Video: Types of Practice

INTERMEDIATE MATERIAL

1. Reinforcement and Supervised Learning

Supplementary Reading: Cockburn et al. 2017
Reinforcement Learning Example: Robot Learns to Flip Pancakes
​Learning Styles: Examples of Different Learning Styles

Research Paper: Prediction Errors in the Human Brain Garrison et al. 2013
Website: Observational Learning
Video: Thorndike's Law of Effect
Research Article: Prediction Errors


2. Observational Learning and Mirror Neurons
YouTube: Observational Learning (Classic)
Research Paper: Bellebaum
YouTube: Mirror Neurons
Research Paper: Mirror Neurons
​
Research Paper: Mirror Neuron Review Paper

3. Schema Theory
Website: Schema Theory

Review Paper: Sherwood 2003

4. Neural Basis of Motor Skills
Video: The Basal Ganglia and Movement
Review Paper: Willingham 1999
Review Paper: Brown 2006
Website: How Do You Move?

5. Specificity of Practice
Paper: Specificity of Practice (Krigolson & Tremblay, 2009)
Research Article: Specificity of Practice

6. Mental Imagery
Research Article: Mental Imagery and Motor Learning
​
Research Article: Wei 2010
​
Article: The Power of Mental Imagery

Video: Mental Imagery

ADVANCED MATERIAL

1. LTP and Neural Plasticity
Video: LTP
​
Website: LTP
Video: LTP
Article: Hebbian Learning and Decision Making
Article: Hebbian Learning and Development

Website: Introduction to Hebb's Law
The Man: Donald Hebb
Article: Hebbian Learning
Article: Lucas et al. 2015
Video: Synaptic Plasticity


2. Dopamine
Article: Neural Coding of Prediction Errors
Article: Dopamine and RL
​
Video: Dopamine and Reward
​
Article: Schultz, Dayan, and Montague 1997
Article: Synaptic Degradation
Article: Understanding Dopamine and Prediction Errors
Article: Review of Prediction Error Findings
​
Website: Mouse Party - How Drugs Mess With Your Reward System
Article: Dopamine, Aging, and Prediction Errors

3. Neural Representations and Motor Primitives

Website: Motor Primitives in Robotics
Research Paper: Motor Primitives

4. Forward and Inverse Models
Research Paper: Forward and Inverse Models
Research Article: Wolpert Internal Models
​
Research Article: Desmurget 2000
Research Article: Forward and Inverse Models
​
5. Sleep
Video: The Benefits of Sleep
Website: The Walker Sleep Laboratory
Paper: Walker et al. 2002, Sleep and Motor Skill Learning
Paper: Walker et al. 2003, Sleep and the Time Course of Motor Learning

6. Aging, Nutrition, and Other Factors

Research Article: Liu 2013
Research Article: Caffeine
Review Paper: Cramer 2015
  • NEUROSCIENCE
    • NEUROSCIENCE 100 >
      • NEURO 100 INTRODUCTION
      • NEURO 101 ADVANCED
      • NEURO 102 AGING
      • NEURO 103 MEMORY
      • NEURO 104 DECISION MAKING
      • NEURO 105 LEARNING
      • Research Statistics
    • NRSC 500B / MEDS 470
  • Kinesiology
    • EPHE 245 >
      • LABORATORY
      • PRACTICUM
    • EPHE 357
  • STATISTICS
    • LECTURE >
      • INTRODUCTION TO R
      • DESCRIPTIVE STATISTICS
      • VISUALIZING DATA
      • Correlation and Regression
      • MULTIPLE REGRESSION
      • LOGIC OF NHST
      • T TESTS
      • ANOVA
      • POST HOC ANALYSIS
      • NON PARAMETRIC STATISTICS
      • FACTORIAL ANOVA
      • Repeated Measures ANOVA
      • Mixed ANOVA
      • MULTIVARIATE ANOVA
      • THE NEW STATISTICS
      • Bayesian Methods
    • ASSIGNMENTS >
      • Introduction to R >
        • INTRODUCTION TO R
        • LOADING DATA
        • DATA TABLES
      • Descriptive Statistics >
        • Mean, Median, and Mode
        • VARIANCE
        • CONFIDENCE INTERVALS
        • SHORTCUTS
      • Visualizing Data >
        • PLOTTING BASICS
        • BAR GRAPHS
        • BOXPLOTS
        • HISTOGRAMS
        • USING GGPLOT I
        • USING GGPLOT II
        • USING GGPLOT III
      • Correlation and Regression >
        • CORRELATION
        • REGRESSION
      • MULTIPLE REGRESSION >
        • MULTIPLE REGRESSION
      • Logic of NHST >
        • Sample Size and Variance
        • DISTRIBUTIONS
        • TESTING DISTRIBUTIONS
      • T-Tests >
        • Single Sample TTests
        • Paired Sample TTests
        • Independent Sample TTests
      • ANOVA >
        • ANOVA ASSUMPTIONS
        • ANOVA
      • POST HOC ANALYSIS >
        • POSTHOC ANALYSIS
      • NON PARAMETRIC STATISTICS >
        • WILCOXON TEST
        • WILCOXON SIGNED TEST
        • MULTIPLE GROUPS
      • FACTORIAL ANOVA
      • REPEATED MEASURES ANOVA >
        • RM ANOVA
        • TREND ANALYSIS
      • MIXED ANOVA
      • MULTIVARIATE ANOVA
      • THE NEW STATISTICS
      • BAYESIAN TTESTS
    • RESOURCES
    • R TIPS
  • Directed Studies
    • Advanced Topics in Motor Control A
    • Advanced Topics in Motor Control B
    • An Introduction to EEG
    • Advanced EEG and ERP Methods
    • Neural Correlates of Human Reward Processing
    • Independent Research Project
  • MATLAB
    • THE BASICS >
      • Hello World
      • BASIC MATHEMATICS
      • VARIABLES
      • Matrices
      • Writing Scripts
      • PATHS AND DIRECTORIES
      • USER INPUT
      • FOR LOOPS
      • WHILE LOOPS
      • IF STATEMENTS
      • RANDOM NUMBERS
    • STATISTICS >
      • LOADING DATA
      • DESCRIPTIVE STATISTICS
      • MAKING FUNCTIONS
      • BAR GRAPHS
      • LINE GRAPHS
      • TTESTS
    • EXPERIMENTS: THE BASICS >
      • DRAWING A CIRCLE
      • DRAWING MULTIPLE OBJECTS
      • DRAWING TEXT
      • DRAWING AN IMAGE
      • PLAYING A TONE
      • KEYBOARD INPUT
      • BUILDING A TRIAL
      • BUILDING TRIALS
      • NESTED LOOPS
      • RIGHT OR WRONG
      • SAVING DATA
    • EXPERIMENTS: ADVANCED >
      • STROOP
      • N BACK
      • Oddball
      • Animation
      • VIDEO
    • EEG and ERP Analysis >
      • ERP Analysis
  • RESOURCES
    • EXCEL
    • HOW TO READ A RESEARCH PAPER
    • HOW TO WRITE A RESEARCH PAPER
  • Workshops
    • Iowa State EEG Workshop 2018
  • Python
    • The Basics >
      • Setting Up Python
      • Hello, world!
      • Basic Math & Using Import
      • Variables
      • Matrices
      • Scripts
      • User Input
      • For Loops