Neuroniteorian

Neuroniteorian is a theoretical framework in neuroscience that describes how information is processed in neural systems through multi-scale dynamics that combine individual neuron activity with network-wide patterns. Proponents describe it as a shift from purely rate-based descriptions toward models that integrate temporal coding, cross-network interactions, and glial contributions to signaling and plasticity. The theory emphasizes that information is carried not only by average firing rates but by the timing of spikes, synchrony across oscillations, and context-dependent modulation of circuits.

The term emerged in theoretical discussions during the late 20th and early 21st centuries as researchers debated the limits of single-neuron models and purely feedforward networks. It is not tied to a single laboratory but to a family of ideas advocating cross-scale integration.

Key concepts include temporal coding and precise spike timing, cross-frequency coupling, phase relationships, spike-timing-dependent plasticity, glial signaling, neuromodulatory state affecting network routing, and energy constraints shaping network states.

Reception and critique have highlighted its comprehensive scope while criticizing insufficient experimental validation and operational definitions, which makes it difficult to test in a single experiment. Some researchers view the concept as a useful umbrella that unites multiple findings rather than a single testable theory.

Related topics include neural coding, spike-timing-dependent plasticity, cross-frequency coupling, glia in neuroscience, and predictive coding.