Thinking·OS

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Action potential explains Hodgkin–Huxley model. Activate to inspect this relation.Action potential is a Membrane potential. Activate to inspect this relation.Action potential requires Ion channel. Activate to inspect this relation.Action potential is part of Neuron. Activate to inspect this relation.Brain–computer interface applies to Neuron. Activate to inspect this relation.Brain–computer interface depends on Machine learning. Activate to inspect this relation.Brain atlas requires Neural data standard. Activate to inspect this relation.Brain–computer interface requires Neural decoding. Activate to inspect this relation.Connectome applies to Computational neuroscience. Activate to inspect this relation.Connectome depends on Brain atlas. Activate to inspect this relation.Connectome applies to Network. Activate to inspect this relation.Connectome is part of Neuroinformatics. Activate to inspect this relation.Default mode network is part of Connectome. Activate to inspect this relation.Electrophysiology recording enables Neural decoding. Activate to inspect this relation.Electrophysiology recording measures Action potential. Activate to inspect this relation.Hodgkin–Huxley model is part of Computational neuroscience. Activate to inspect this relation.Membrane transport enables Action potential. Activate to inspect this relation.Myelination enables Action potential. Activate to inspect this relation.Neural data standard applies to Electrophysiology recording. Activate to inspect this relation.Neural decoding depends on Neural encoding. Activate to inspect this relation.Neural encoding is part of Computational neuroscience. Activate to inspect this relation.Neuromorphic computing is derived from Spiking neural network. Activate to inspect this relation.Spiking neural network models Action potential. Activate to inspect this relation.Spiking neural network is part of Computational neuroscience. Activate to inspect this relation.Synaptic plasticity influences Spiking neural network. Activate to inspect this relation.Electrophysiology recordingNeural decodingAction potentialNeural data standardNeural encodingBrain–computer interfaceHodgkin–Huxley modelMembrane potentialIon channelNeuronMembrane transportMyelinationSpiking neural networkBrain atlasComputational neuroscienceMachine learningNeuromorphic computingSynaptic plasticityConnectomeNetworkNeuroinformaticsDefault mode network
Relationship types

14 concepts viewed through this lens. Bridge concepts connect this view to Anthropology, Artificial Intelligence, Biology, Biophysics….

Legend
  • Focused concept
  • Connected concept
  • Bridge concept (just outside the lens)
  • Arrow points from cause / source to effect / target
  • A line with no arrow is a two-way relationship
  • Node colour marks the concept’s primary discipline
22 concepts25 relationships17 disciplines5 relation families

Electrophysiology recording

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At a glance

Electrophysiology recording measures the electrical activity of neurons to capture their signalling in real time.

Disciplines
Neuroinformatics
Role in the graph
Cross-disciplinary bridge — reaches Biophysics, Neuroscience
Relationships
3 · 3 relation families

What am I looking at?

In this lens (14)

Bridge concepts (10)

Just outside the lens — they connect it to other context.

Insights from this view

Structural observations about the concepts shown here — descriptions of this graph, not claims about the world.

  • This view connects 17 disciplines: Anthropology, Artificial Intelligence, Biology, Biophysics, Biotechnology, Cell Biology, Computer Science, Discrete Mathematics, Linear Algebra, Machine Learning, Mathematics, Network Science, Neuroinformatics, Neuroscience, Sociology, Statistics, Urban Planning.
  • Action potential is a bridge concept — viewed here through Biophysics, Neuroinformatics, Neuroscience.
  • The connections here span 5 relation families.
  • Networks explains 2 concepts in this view (Anthropology, Biology, Discrete Mathematics, Linear Algebra, Mathematics, Network Science, Neuroscience, Sociology, Urban Planning).

Relationships as a list

The focused concept’s relationships. Pick another concept in the graph above to update this list.

Explore through a different lens

A lens is a deterministic projection of the graph. Pick a discipline, thinking pattern or journey to reframe the whole view.

By discipline

ChemistryBiologyPhysicsMathematicsComputer ScienceGeologyMineralogyEconomics

By thinking pattern

Bayesian updatingCause and effectCompoundingConservationConstraintsDefense in depthDiffusion & spreadEmergenceEnergy transformationEntropy & irreversibilityEquilibriumFeedback loopIncentivesInformationLevels & hierarchyModularityNetworksOptimizationOscillationProbabilityRecursion & self-similarityScaleSignal vs noiseSource–pathway–receptorStocks and flowsSymmetry & invarianceThresholds & tipping pointsTrade-offsTriangulationVariation & selectionWaves

By journey

From a Leaf to the ClimateWhy Music Moves UsHow Machines LearnReasoning about a Leaf and the Climate

Concept collections

Concept collections are curated lenses onto the fabric — themed sets of ideas that recur across disciplines. They are not journeys; they are a way to read the graph.

About this view

What this is

Start from one concept and expand outward. The view never shows everything at once — click a node to refocus, filter by relationship type, or switch to an accessible list.

One fabric

3750 concepts and 5051 typed relations form one connected component — no isolated silo.

How to read it

Focus a concept, or apply a lens (discipline, mental model, journey) to see only the threads that matter.