Fundamentals of Computational Neuroscience (2nd Edition): Figures

The second edition of Fundamentals of Computational Neuroscience is now available at Oxford University Press and Amazon.ca.

Appendices

MATLABfirst.pdf
MATLABfirstColor.pdf
MatlabDesktop.pdf
MatlabDesktopColor.pdf
MatlabFigure.pdf
MatlabFigureColor.pdf
Octave.pdf
SciLab.pdf
appendix_math1.pdf
appendix_math2.pdf
appendix_numinte.pdf
appendix_numinte_color.pdf
comm_channel.pdf
dis_arbitrary.pdf
dis_binomial.pdf
dis_chisquare.pdf
dis_exponential.pdf
dis_lognormal.pdf
dis_poisson.pdf
dis_transformation.pdf
dis_uniform.pdf
figHisto.pdf
info_hand.pdf
info_hand2.pdf
info_it1.pdf
info_spiketrain.pdf
info_spiketrain2.pdf
info_surprise.pdf
sparseness.pdf

Chapter 1

Figures

anticipatingBrain1.pdf
deco2.pdf
levels_of_org2.pdf
model1.pdf
model2.pdf

Chapter 2

action_potential.pdf
circuit_hh.pdf
circuit_syn.pdf
compartment.pdf
hh1.pdf
hh2A.pdf
hh2B.pdf
hh_ion.pdf
ion_channels.pdf
matlab_hh.pdf
matlab_wilson.pdf
neuron.pdf
neuron_sim.pdf
neuron_sim2.pdf
synapse1.pdf
synapse2.pdf
wilson.pdf

Chapter 3

adrian.pdf
alpha1.pdf
alpha2.pdf
alpha2.pdf
buracas.pdf
decharms_merzenich.pdf
epsilon1.pdf
epsilon2.pdf
epsilon3.pdf
if_fast.pdf
if_gauss.pdf
if_isi.pdf
if_node.pdf
if_poisson.pdf
inte_coincidence.pdf
isi_hist.pdf
izhikevich_neuron.pdf
leaky_if.pdf
mean_firing_if.pdf
modulation.pdf
noise_models.pdf
phys_gain.pdf
rate_population.pdf
rate_temporal.pdf
table_transf.pdf
tuning.pdf

Chapter 4

Figures

asso2.pdf
associative_learning.pdf
associative_net.pdf
associative_node.pdf
calcium.pdf
f_prepost.pdf
f_prepost2.pdf
hebb1_distribution.pdf
hebb_stdp.pdf
if_STDP_Song.pdf
if_crosscorr.pdf
oja.pdf
oja_node.pdf
plasticity1.pdf
plasticity2.pdf
signaling.pdf

Chapter 5

Figures

abeles.pdf
asyn_gain.pdf
brain.pdf
cortex_column.pdf
cortex_layers.pdf
izhikevichNet.pdf
layers_schematic1.pdf
layers_schematic2.pdf
module_cortex.pdf
netlets.pdf
netlets2.pdf
thorpe.pdf

Chapter 6

A_binarization.pdf
A_letter.pdf
boolean.pdf
elman.pdf
gradient_descent.pdf
mlp.pdf
mlp_XOR.pdf
mlp_XOR2.pdf
mlp_comp.pdf
mlp_comp2.pdf
mlp_sine.pdf
node_creation.pdf
overfit.pdf
perceptronExample.pdf
rbfNet.pdf
rbfTrans.pdf
sigma_node2.pdf
surface1.pdf
svm1.pdf
svm1map.pdf
svm1nl.pdf
svm2.pdf
svm2Color.pdf

Chapter 7

DNFexamplePlaceField.pdf
DNFexampleWM.pdf
DNFexamples.pdf
DNFheadDirections.pdf
DNFpiModel.pdf
DNFpiSim2.pdf
DNFpiSim2.pdf
DNFpopulationDecoding.pdf
DNFweightkernel.pdf
DNFweightkernelSC.pdf
cann_drift.pdf
cann_sim1.pdf
cann_sim1b.pdf
cann_theory.pdf
cann_theory2.pdf
hd_model.pdf
pop_decoding.pdf
som_a1.pdf
som_model1.pdf
som_model2.pdf
som_sim1b.pdf
som_sim2b.pdf
tuningCurve.pdf
tuning_curve2.pdf

Chapter 8

GH_phasediagram.pdf
ann.pdf
ann_asym.pdf
ann_diluted.pdf
ann_retrieval.pdf
ann_sim.pdf
ann_sim_color.pdf
expansion_recoding.pdf
gradient_descent1.pdf
hippo.pdf
lorenz.pdf
memoryClassification.pdf
signoise.pdf
sparse1.pdf
sparse2.pdf

Chapter 9

DNFmemoryLimit.pdf
TDlearning.pdf
ann_sequence.pdf
basal_ganglia2.pdf
basal_ganglia2.pdf
basal_ganglia3.pdf
basal_ganglia4.pdf
cerebellum.pdf
conditioning.pdf
control_critic.pdf
control_forward.pdf
control_forward_inverse.pdf
control_inverse.pdf
control_negative.pdf
coupled_ann.pdf
coupled_ann2.pdf
experts.pdf
mixture_experts.pdf
modular_function.pdf
td.pdf
what_where.pdf
wm_limit.pdf
wm_randy.pdf

Chapter 10

ART.pdf
ARTletter.pdf
Boltzmann1.pdf
Boltzmann2.pdf
Boltzmann3.pdf
EM.pdf
EMcolor.pdf
FristonTT.pdf
Helmholtz.pdf
Hinton.pdf
HintonColour.pdf
bayesianNetworks2.pdf
bayesianNetworks2.pdf
deco_model.pdf
deco_res.pdf
deco_where_what.pdf
dehaene.pdf
dehaene2.pdf
rec_fields.pdf
stroop.pdf
visnet.pdf