Neuromodulatory Control of Cortical Function: Cell-Type Specific Regulation of Neuronal Information Transfer

Neuromodulatory systems such as dopamine and acetylcholine enable cortical circuits to rapidly shift between behavioral states, yet it remains unclear how receptor-specific signaling reshapes what single neurons compute. Here, we combined whole-cell recordings from excitatory and inhibitory neurons in layer 2/3 of mouse somatosensory cortex with information-theoretic analyses under frozen-noise stimulation. We quantified stimulus-to-spike information transfer and profiled each neuron across four functional domains: passive membrane biophysics, action potential dynamics, intrinsic adaptation currents, and input feature selectivity captured by spike-triggered averages. Activation of D1, D2, or M1 receptors produced cell-type and receptor-specific changes in fractional information and firing output, demonstrating that neuromodulators regulate encoding beyond simple gain control. Unsupervised clustering revealed that receptor activation reshapes neuronal functional identities, consistent with a dynamic computational phenotype. To identify the organizing principle underlying these transitions, we applied multi-set correlation and factor analysis and found that neuromodulation systematically reorganizes covariance among functional domains. In excitatory neurons, dopaminergic activation led to decreased coordination between input feature selectivity and other functional properties while strengthening coordination among response-based features such as spike dynamics and adaptation. Inhibitory neurons, by contrast, generally exhibited increased coordination across domains. These findings identify neuromodulation as a reconfiguration signal that reshapes not only individual cellular properties but also the architecture linking them, thereby dynamically expanding the computational repertoire of cortical circuits.