Neuroscience

Neuroscience studies how the nervous system produces perception, movement, memory and thought, and it does so by working across scales — from a single ion channel opening in a cell membrane to millions of neurons synchronising into the rhythms an EEG cap picks up on your scalp. This hub gathers every interactive neuroscience simulation on mysimulator.uk into one guided starting point, so instead of memorising a differential equation from a textbook, you can inject a current, tune a coupling strength, and watch the same mathematics that governs real neurons play out in your browser.

The foundation of the whole field is the action potential, and the Hodgkin-Huxley neuron simulation reproduces the exact conductance-based equations that Alan Hodgkin and Andrew Huxley used to win the 1963 Nobel Prize. Inject current into the simulated squid giant axon and you'll see voltage-gated sodium channels open explosively, driving a rapid depolarisation, followed by potassium channels opening more slowly to repolarise the membrane and enforce a refractory period during which the neuron cannot fire again. Every spike in every other simulation on this page — however abstracted — ultimately traces back to this mechanism.

A spike is useless until it reaches another cell, and the synapse simulation shows what happens at that handoff: the arriving action potential triggers calcium influx, calcium triggers vesicle release, neurotransmitter diffuses across the synaptic cleft, and receptor binding produces either an excitatory postsynaptic potential (EPSP) that nudges the next neuron toward firing, or an inhibitory one (IPSP) that pushes it away. The synaptic plasticity and long-term potentiation simulations show that this connection isn't fixed — the precise timing between a presynaptic spike and a postsynaptic spike determines whether the synapse strengthens or weakens, a rule called spike-timing-dependent plasticity (STDP) that is widely believed to be the cellular substrate of learning and memory. The BCM rule formalises a related idea with a sliding modification threshold that adapts to recent activity, keeping learning stable rather than runaway.

Individual neurons rarely act alone; the central pattern generator simulation shows how a small circuit of mutually inhibiting neurons can produce rhythmic motor output — the alternating leg movements of walking, the beat of breathing — entirely on its own, without needing a repeating signal from the brain or sensory feedback. Scale up further and populations of neurons synchronise the way any coupled oscillators do: the Kuramoto synchronization simulation demonstrates the general mathematics (also used to describe fireflies flashing in unison and power-grid generators locking to a common frequency), and the neural oscillators and brainwave EEG simulations apply that same coupled-oscillator mathematics to real cortical rhythms — the alpha waves of relaxed wakefulness, the beta waves of active concentration, and the slower theta and delta waves associated with drowsiness and deep sleep.

The spiking neural network simulations pull individual neurons together into small networks of leaky integrate-and-fire units, complete with excitatory and inhibitory populations and STDP synapses, and let you watch a raster plot shift between disorganised, asynchronous firing and tightly synchronised bursts as you change connectivity and the excitation/inhibition balance — the same balance implicated in conditions like epilepsy when it tips too far toward synchrony. At the other end of the scale, neurovascular coupling and the BOLD signal simulation connect neural activity to something measurable from outside the skull: firing neurons trigger local blood vessel dilation via nitric oxide, and the resulting change in blood oxygenation is exactly the signal an fMRI scanner detects — the link between a spike in a single cell and a coloured blob on a brain scan.

Together these simulations trace the topic's full arc, from a single voltage-gated ion channel to the population rhythms that define conscious states and the blood-flow signals that let us watch a living brain think. Every model here is a genuine numerical integration of the underlying equations — Hodgkin-Huxley's four coupled differential equations, the Kuramoto phase-coupling model, the leaky integrate-and-fire spiking equations — not a pre-rendered animation, so changing a parameter changes the actual dynamics, not just the picture. That makes this hub useful whether you're a student building intuition before a neuroscience exam, an educator looking for a single adjustable demonstration, or simply curious how three pounds of electrochemical tissue produces everything you experience.