Bioeng 376 / Bioph 317 / Neuro 317 /Physl 317
Outline - Lecture 1
M. Nelson  Spring 2004

Basic Tools
A neural modeler needs to have a handy set of tools from math, physics, computer science, and neurobiology. Here's a review of a few of the things that should be in your basic toolbox.  If some of your tools are rusty, it's time to get them oiled up and ready to go.

trig functions
  • basic properties of sin, cos, tan, ...
  • relationship between degrees and radians (180deg = pi radians)
  • geometrical interpretation (e.g., cosine = adjacent/hypotenuse)
  • relationships: sin2 + cos2 = 1, tan(a) = sin(a)/cos(a), etc.
exponentials
&
logarithms
  • basic properties of exponentials, e0 = 1, e1 ~ 2.71818, etc.
  • sketch exponential decay curve, exponential charging curve
  • graphically identify time constant, 1/e ~ 37%
  • identify time constant from equation
  • properties of logs,  log(0) = -infinity, log(1) = 0, ln(e) = 1, etc.
  • choice of base-10, base-2, natural log, etc.
  • convert from one base to another
  • semilog, loglog plots
derivatives
integrals
vectors
&
matrices
ordinary
differential
equations
  • differential equations as models
  • temporal derivatives as rate-of-change
  • ability to integrate simple cases by hand
  • numerical integration, Euler's method
  • initial value specification (where to start)
  • steady-state solutions
    Euler's Method
basic
electrical
circuit
analysis
  • Kirchoff's current law (current conseration at nodes)
  • Kirchoff's voltage law (sum of voltage drops around a loop is zero)
  • Ohm's law: V = I R
  • Conductance is inverse resistance g = 1/R; Ohm's law: I = gV
  • Capacitance: q = CV
  • Capacitive current: I = dq/dt = C dV/dt
  • RC circuit, RC time constant
    Analysis of Resistive Circuits