Reading directions for reading material (kursbunten)
1=chapter of fundamental character/highest importance, 2=chapter of intermediate importance, 3=chapter with additional information.


F0 Background for those who have not completed DD2401/HL1009/7E1201 Neuroscience.
CellularNeuroBackground.pdf   Skip the text about Cystic fibrosis. (can be found under lecture notes)
NeuroscienceOverview.pdf    (can be found under lecture notes)
NumericsBackgroundDeSchutter1.pdf    (can be found under lecture notes)
http://www.biology-online.org/8/1_nervous_system.htm
http://www.acm.uiuc.edu/sigbio/project/nervous/index.html

See also:
http://thalamus.wustl.edu/course/
http://normandy.sandhills.cc.nc.us/psy150/nervsys.html
http://www.uta.edu/biology/restricted/3452nerv.htm
http://www.educypedia.be/education/nervoussystem.htm

F1
Introduction	Bower & Bolouri, Computational modeling of genetic and biochemical networks, MIT Press
   Level 3

Chapter 10 The network within	Bower & Beeman, The Book of Genesis, Internet edition
   If you have not completed DD2400/HL1008/7E1200 Cell and molecular
   biology or some other course in biochemistry, I reccomend that you
   read this on Level 2.

F2
Physical biochemistry	Westermark, del 1
   1    Level 1
   2    Level 1 (exept 2.2.1 Level 3)
   3.1  Level 1 (exept 3.1.1 Level 2)
   3.2  Level 1
   4    Level 3

F3
Physical biochemistry	Westermark, del 2
   1 1.1 and 1.2 Level 1 but 1.2.2 Level 3
   2 Level 3

F4
Chapter 2 Compartmental modeling	Bower & Beeman, The Book of Genesis, Internet edition
   2.1 Modeling neurons, Level 2
   2.1.1 Detailed Compartemental Models, Level 1
   2.1.2 Equivalent Cylinder Models, Level 1
   2.1.3 Single and Few Compartment Models, Level 1
   2.2 Equivalent circuit of a single compartment, Level 1
   2.3 Axonal connections, synapses, and networks, Level 2
   2.4 Simulation accuracy, Level 2
   2.4.1 Choise of Numerical Integration Technique, Level 3
   2.4.2 Integration Time Step, Level 3

Chapter 5.1-5.4 Cell membranes and ion movement     Petersen, Basic Biophysics and cellular modeling, class notes
Chapter 7.1 Cell membranes and ion movement     Petersen, Basic Biophysics and cellular modeling, class notes
Chapter 8.1-8.4 Cell membranes and ion movement     Petersen, Basic Biophysics and cellular modeling, class notes
   Level for ch 5,7,8 is Level 1, to understand, know the
   prerequisites and be able to use:
   a) Nernst-Planck I eq
   b) Nernst eq
   c) Donnan rule
   d) GHK I eq
   e) GHK V eq

F5
Chapter 4 The Hodgkin-Huxley model	Bower & Beeman, The Book of Genesis, Internet edition
   4.1, 4.2    Level 3
   hela 4.3    Level 1
   4.4         Level 2

F6
Chapter 5 Cable and compartmental models of dendritic trees	Bower & Beeman, The Book of Genesis, Internet edition
   5.1 Introduction, Level 2
   5.2 Background, Level 2
   5.2.1 Dendritic Trees: Anatomy, Physiology, and Synaptology, Level 3
   5.3 The one-dimensional cable equation, Level 1
   5.3.1 Basic Concepts and Assumptions, Level 2
   5.3.2 The Cable Equation, Level 2
   5.4 Solution of the cable equation for several cases, Level 2
   5.4.1 Steady-state Voltage Attenuation with Distance, Level 2
   5.4.2 Voltage Decay with Time, Level 2
   5.4.3 Functional Significance of Lambda and Tau_m, Level 2
   5.4.4 The Input Resistance Rin and "Trees Equivalent to a Cylinder", Level 1
   5.5 Compartementalmodeling approach, Level 1
   5.6 Compartementalmodeling experiments, Level 2
   5.7 Main insights for passive dendrites with synapses, Level 1
   5.8 Biophysics of excitable dendrites, Level 1
   5.9 Computational function of dendrites, Level 1


F7
Chapter 6 Calcium dynamics in large neuronal models	Koch & Segev, Methods in neuronal modeling 2ed, MIT press
   6.2.1       Level 1
   6.3.1       Level 1
   6.3.2       Level 1
   all 6.4     Level 1
   all 6.6     Level 1
   rest        Level 3


You can also read the following on the web: chapter 3 in
Gerstner and Kistler, Spiking Neuron Models. Single Neurons,
Populations, Plasticity, Cambridge University Press, 2002
http://diwww.epfl.ch/~gerstner/SPNM/SPNM.html


Models of development	Sandberg    (can be found under lecture notes)
   Level 3

F8
1 Modeling the activity of single genes		Bower & Bolouri, Computational modeling of genetic and biochemical networks, MIT Press
   1.1   1
   1.2   3
   1.3   2
   1.4   1
   1.5   1

Computational studies of gene regulatory networks	Hasty & Co, Nature
   Level 3

Simulation of prokaryotic genetic circuits		McAdams & Arkin, Annu Rev Biophys Biomol Struct
   Level 3

   Understand lab3b, Level 1

F9 (only for D2435)
Chapter 1 Kinetic models of synaptic transmission	Koch & Segev, Methods in neuronal modeling 2ed, MIT press
   ch 1      1
   ch 2      2
   ch 3      2
   ch 4      1
   ch 5      1
   Appendix   3

Synaptic plasticity	Abbott & Nelson, Nature
   Level 3

Natural patterns of activity and long-term synaptic plasticity	Paulsen & Sejnowski, Curr opinion neurobiol
   Level 3

You can also read the following on the web: chapter 10, 10.1 in
Gerstner and Kistler, Spiking Neuron Models. Single Neurons,
Populations, Plasticity, Cambridge University Press, 2002
http://diwww.epfl.ch/~gerstner/SPNM/SPNM.html

F10 (only for D2435)
Chapter 8 Central pattern generators	Bower & Beeman, The Book of Genesis, Internet edition
   8.1    1
   8.2    1
   8.2.1  1
   8.2.2  3
   8.2.3  2
   8.2.4  2
   8.2.5  3
   8.3    3

Computational models of association cortex    Gisiger & Co, Curr opinion neurobiol
   Introduction, första paragrafen		  1
   Introduction, resten			  2
   From cortical organization to perception  2
   The gensiss of cortical maps		  2
   Re-entrance and the binding problem	  3
   Binoculatity and perception		  3
   Cognitive learnign			  2
   Reward-motivated learning, sid 253	  2
   Reward-motivated learning, sid 254	  3
   Auto-evalluation and hierarcical ...	  3
   The problem of consciousness		  3
   Dynamic core model			  3
   Global workspace model	          3
   Conclusions				  1


You can also read the following on the web: chapter 6, 6.1 in
Gerstner and Kistler, Spiking Neuron Models. Single Neurons,
Populations, Plasticity, Cambridge University Press, 2002
http://diwww.epfl.ch/~gerstner/SPNM/SPNM.html