Ketamine, an NMDA receptor antagonist and experimental model for schizophrenia, produces decision-making deficits in monkeys, which are predicted by a lowering of cortical excitation-inhibition balance in a spiking circuit model.

Local disinhibition provides a biologically plausible mechanism for flexible top-down control of network states that integrates normalized value coding, winner-take-all choice, and persistent activity in a single circuit of decision-making.

Computational modeling offers an explanation for why animals learn more quickly or slowly when their environment becomes more variable or stable.

A review of a neuronal circuit architecture that helps us to learn about rewarding events and then to use that information to support adaptive decision making.

Chronic alcohol exposure results in a long-lasting, enhanced endocannabinoid signalling at orbitostriatal synapses that is expressed in a projection-, synapse-, and behaviorally computation-specific manner.

Neural processes for perception and confidence can be separated thanks to computational electroencephalography, thus revealing a neural circuit specific to metacognition.

Adaptive decision-making critically depends on antiparallel flows conveying distinct information within thalamocortical circuits, highlighting directionality of functional exchanges as a neural principle potentially at play in virtually any brain circuit with reciprocal projections.

Disruption of the disease-associated synaptic adhesion molecule Neurexin1a in cortical excitatory neurons perturbs decision making and disrupts value-associated neural activity in downstream striatal circuits.

WaveMAP is a novel approach that combines nonlinear dimensionality reduction with graph clustering on extracellular waveforms to reveal previously obscured cell type diversity in monkey cortex.

A first principles, neuro-computational framework proposes a path for the experimental dissection of neural circuit mechanisms of competitive selection across brain areas and animal species.