Modelling the brain as an information-processing system.
10 topics · 17 curated works
No prior grounding assumed.
Simple Model of Spiking Neurons
Eugene Izhikevich · 2003
Presents a two-equation neuron model that reproduces the firing patterns of real cortical neurons at a fraction of the computational cost of a full…
Assumes you know the vocabulary.
The Impulses Produced by Sensory Nerve Endings
Edgar Adrian · 1926
Shows that a sensory nerve fibre signals stimulus intensity by its rate of firing rather than by any change in impulse size, establishing rate coding…
+3 more at this level
Primary sources and full treatments.
Impulses and Physiological States in Theoretical Models of Nerve Membrane
Richard FitzHugh · 1961
Reduces the Hodgkin-Huxley equations to a two-variable model whose phase-plane geometry explains excitability and repetitive firing without the full…
+11 more at this level
12 of 17 works
Eugene Izhikevich
Presents a two-equation neuron model that reproduces the firing patterns of real cortical neurons at a fraction of the computational cost of a full biophysical model.
link failing as of 17 Sept 2026Edgar Adrian
Shows that a sensory nerve fibre signals stimulus intensity by its rate of firing rather than by any change in impulse size, establishing rate coding as a basic principle of neural communication.
link checked 17 Sept 2026Donald Hebb
Proposes that a synapse strengthens when its presynaptic cell repeatedly helps fire the postsynaptic one, giving learning and memory a concrete cellular mechanism.
link checked 17 Sept 2026Carver Mead
Argues analogue circuits built to mimic neural computation can be more efficient than digital simulation, coining neuromorphic engineering as its own field.
link checked 17 Sept 2026David Knill & Alexandre Pouget
Argues the brain represents sensory uncertainty explicitly and combines cues by weighting each according to its reliability, as Bayesian inference would prescribe.
Richard FitzHugh
Reduces the Hodgkin-Huxley equations to a two-variable model whose phase-plane geometry explains excitability and repetitive firing without the full ionic detail.
link checked 17 Sept 2026Hugh Wilson & Jack Cowan
Derives equations for the average activity of interacting excitatory and inhibitory neuron populations, showing simple interactions alone can produce multistability and oscillation.
link checked 17 Sept 2026John Hopfield
Shows that a network of symmetrically connected binary neurons behaves as a content-addressable memory whose stored patterns are stable points of an energy function.
link checked 17 Sept 2026Daniel Amit
Develops the statistical mechanics of networks that store memories as stable attractor states, treating recall as convergence to one of these stored patterns.
Fred Rieke, David Warland, Rob de Ruyter van Steveninck & William Bialek
Argues neural spike trains should be analysed as a code to be decoded using information theory, rather than described only by an averaged firing rate.
Wolfgang Maass
Argues spiking neuron models that use precise timing are computationally more powerful than the rate-based units of earlier neural network generations.
link checked 17 Sept 2026Guo-Qiang Bi & Mu-Ming Poo
Demonstrates that whether a synapse strengthens or weakens depends on the precise millisecond timing between pre- and postsynaptic spikes, not just their correlated activity.
link checked 17 Sept 2026This subject genuinely sits in more than one domain. These fields approach the same ground with different methods.