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Math 490N/Biol 595N:Math 490N/Biol 595N:Introduction to Computational Introduction to Computational NeuroscienceNeuroscience

Course Organization

Introduction

Mathematical Models

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Goals of the CourseGoals of the Course

Experience working in a multi-disciplinary team of scientists

Increase tolerance to cognitive discomfort in learning/working situation

Learn basics of neurophysiology, differential equations, dynamical systems, and some related computer tools

Become familiar with some classical models of neural systems

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Different Kind of CourseDifferent Kind of Course

First time course offered…an experiment We in the course have very different kinds

of backgrounds Our backgrounds do not prepare us for

the course material Instructor doesn’t know much about the

subject

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OrganizationOrganization

Math 490N vs Biol 595N

Work in groups Homework Report on paper from the literature Midterm and Final Exam

Academic adjustments

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Who are we?Who are we?

Name Course: Math 490N, Biol 595N, or “audit” Status at Purdue: “junior”, “1st yr grad”, “postdoc” Scientific background/major College level biology courses taken College level math courses taken Other interesting information

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IntroductionIntroduction

Rita Colwell (NSF): “We're not near the fulfillment of biotechnology's promise. We're just on the cusp of it…”

19th Century Biology: descriptive 20th Century Biology: biochemical 21st Century Biology: quantitative/mathematical Eric Lander (Whitehead Inst): “The 21st Century

Biologist must be, at least in part, a mathematician.”

NSF and NIH are concerned that there are not enough people trained to join hands across the disciplinary boundary between biology and math

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Why?Why?

Flooded with data -- need some way to organize it!

Efficiency: mathematical models can do “virtual experiments” faster, more cheaply, and in more difficult conditions than in a wet lab.

Simplifications: mathematics can hide the complexity of a situation behind an organizing concept

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Mathematical ModelsMathematical Models

Life is one big story problem!

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Mathematical ModelsMathematical Models

Life is one big story problem! Create a mathematical description of

experimental data that can be used to extend, interpolate, or manipulate the data

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Mathematical ModelsMathematical Models

Life is one big story problem! Create a mathematical description of

experimental data that can be used to extend, interpolate, or manipulate the data

A simple example: Population model