A glossary of common terms: Glossary

A diagram of modeling concepts: Kinds of mathematical models

Some review / recap questions: Recap questions

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__A no-frills list of your reading materials__

Week 1: Aug 25

**Zombies and mirror neurons:**

Supplementary:

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Week 3: Sep 6

**Central Pattern Generators - part 1:**

OLM gamma - Appendix with equations

Respiratory rhythms in pre-Bot

Supplementary:

Locomotor circuits in spinal cord

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Week 4: Sep 13

**Large scale brain simulation:**

Supplementary:

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Sept 20

**Networks and epilepsy:**

Supplementary:

Emergent epileptiform activity

Comparing epileptiform behavior

Dynamics of large scale brain activity

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**Sep 29**

**Networks and pattern formation:**

Main reading:

Popular article on origin of hallucinations

The math gets hard in this next one but shows how pattern formation is studied with PDEs in neural networks:

PDE methods for nonlocal models

This one is more about the anatomy and the origin of the coordinate mapping from retina to V1 (written by Eric Schwartz!):

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**Oct 11**

**Obesity modeling:**

Main reading:

*Supplementary papers:*

This is a different model of similar things:

A math model of weight change with adaptation - Thomas et al - Math Biosci Eng 2009

This one gives an overview of the field and alerts us to other issues:

de Graaf et al - Nutritional systems biology modeling 2009

Here are two papers looking at aspects of relating heterogeneous models involving health (obesity in particular). These are quite technical from the computer science side of things, but look for the over-arching issues and goals, and how they try to go about them.

Here are three more broader perspectives on obesity modeling, especially the energy balance model:

Issues and misconceptions about obesity - Flatt - Obesity 2011

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**Nov 1**

**Multi-level modeling in biomechanics and neuromuscular control** (CPGs part 2)

Applet for coupled Fitzhugh-Nagumo oscillators: FHN applet

Phase resetting curves and phase oscillators in Chapter 10 (online only, not in his physical book) -- just 10.1:

Izhikevich book - Chs 1 and 10

Main reading:

Reflexes and preflexes - Proctor and Holmes - Biol Cybern 2010

There are good figures and good intro sections in this giant review too (see notes below):

*Notes about what to read in Holmes et al SIAM Review, 2005:*

Section 1: Figure 1, p. 5 - moving between levels of detail

Section 2.2, p. 12: Multiple realizability and reduced "template" models; Figure 4, p. 13; Figure 5, p. 17

Section 2.3, p. 16: Some math definitions of phase, isochrons, etc. but don't read in detail if you don't want to.

Section 2.4, p. 24: Much more important section about organizing functional control through "collapse of dimension" (degrees of freedom) and central pattern generators. Figure 7, p. 28

This approach can conceptually be hypothesized as relevant to understanding higher functions in the cortex:

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**Nov 15**

**Consolidation of concepts and techniques, reviews for future reference**

models and parameters in systems biology

Dynamical principles in neuroscience

methods for reducing complex models

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**Nov 29**

**Noise and stochastics**

Longtin - noise in neural systems

Technical slides - example with FHN model

Stochastic_dynamical_systems (mirror of Scholarpedia page)

Neuronal noise - scholarpedia (mirror of Scholarpedia page)