# Mixed Selectivity **Domain:** Systems Neuroscience / Neural Representation **Doc Type:** Technical Concept Node **Maturity:** Established research concept **Related:** [[Distributed Representation]], [[Superposition]], [[Synaptic Ensemble]], [[Effective Connectivity]] --- ## Definition **Mixed selectivity** describes neurons whose responses depend on combinations of task variables, cues, contexts, or internal states rather than on one fixed feature. A neuron can therefore participate in multiple functional ensembles. ## Architectural Significance Mixed selectivity increases representational capacity through combinatorial reuse of neural substrate. It also creates a control problem: overlapping potential networks must be recruited selectively for the present task. [[articles/Analog Cognition and the Architecture of Continuity|Analog Cognition and the Architecture of Continuity]] connects that problem to spatially and temporally organized wave dynamics. ## Sources / Provenance - Earl K. Miller, Scott L. Brincat, and Jefferson E. Roy, [Analog Cognition and Consciousness](https://doi.org/10.1523/JNEUROSCI.0711-26.2026), _The Journal of Neuroscience_ (2026)