Excitatory and Inhibitory Subnetworks Are Equally Selective during Decision-Making and Emerge Simultaneously during Learning

• Published in: Neuron (Cambridge, Mass.) Vol. 105; no. 1; pp. 165 - 179.e8
• Main Authors: Najafi, Farzaneh, Elsayed, Gamaleldin F., Cao, Robin, Pnevmatikakis, Eftychios, Latham, Peter E., Cunningham, John P., Churchland, Anne K.
• Format: Journal Article
• Language: English
• Published: United States Elsevier Inc 08.01.2020; Elsevier Limited
• Subjects: Animals; Brain slice preparation; Cortex (parietal); Cortex (temporal); Decision making; Decision Making - physiology; Glutamate Decarboxylase - genetics; Learning - physiology; Mice; Mice, Transgenic; Models, Neurological; Nerve Net - physiology; Neural Inhibition - physiology; Neural networks; Neurons; Neurons - physiology; Parietal Lobe - physiology; Sensory integration; Visual cortex; Visual pathways
• ISSN: 0896-6273; 1097-4199
• DOI: 10.1016/j.neuron.2019.09.045

Inhibitory neurons, which play a critical role in decision-making models, are often simplified as a single pool of non-selective neurons lacking connection specificity. This assumption is supported by observations in the primary visual cortex: inhibitory neurons are broadly tuned in vivo and show non-specific connectivity in slice. The selectivity of excitatory and inhibitory neurons within decision circuits and, hence, the validity of decision-making models are unknown. We simultaneously measured excitatory and inhibitory neurons in the posterior parietal cortex of mice judging multisensory stimuli. Surprisingly, excitatory and inhibitory neurons were equally selective for the animal’s choice, both at the single-cell and population level. Further, both cell types exhibited similar changes in selectivity and temporal dynamics during learning, paralleling behavioral improvements. These observations, combined with modeling, argue against circuit architectures assuming non-selective inhibitory neurons. Instead, they argue for selective subnetworks of inhibitory and excitatory neurons that are shaped by experience to support expert decision-making. [Display omitted] •Excitatory and inhibitory neurons are equally selective during decision-making•Selectivity of the two cell types increases in parallel during learning•Models and experiments reject decision circuits with non-selective inhibition•Selective subnetworks of neurons emerge during learning to support decision-making Najafi et al. studied selectivity of mouse excitatory and inhibitory neurons during decision-making. Selectivity is equally strong in the two cell types and emerges gradually during learning. These data, along with theoretical models, argue that selective subnetworks support decision-making.