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To provide a neurobiological basis for understanding decision-making and decision confidence, we describe and analyze a neuronal spiking attractor-based model of decision-making that makes predictions about synaptic and neuronal activity, the fMRI BOLD response, and behavioral choice as a function of the easiness of the decision, and thus decision confidence. The spiking network model predicts probabilistic decision-making with faster and larger neuronal responses on easy versus difficult choices, that is as the discriminability DeltaI between the choices increases, and these and the synaptic currents in turn predict larger BOLD responses as the discriminability increases. Confidence, which increases with discriminability, thus emerges from the firing rates of the decision-making neurons in the choice attractor network. In two fMRI studies, we confirm these predictions by showing that brain areas such as medial prefrontal cortex area 10 implicated in choice decision-making between pleasant stimuli have BOLD activations linearly related to the easiness of both olfactory and warm pleasantness choices. Further, this signature is not found in orbitofrontal cortex areas that represent on a continuous scale the value of the stimuli, but are not implicated in the choice itself. This provides a unifying and fundamental approach to decision-making and decision confidence, and to how spiking-related noise in the brain affects choice, confidence, synaptic and neuronal activity, and fMRI signals.

Original publication




Journal article



Publication Date





694 - 706


Brain, Choice Behavior, Decision Making, Electrophysiological Phenomena, Hot Temperature, Humans, Magnetic Resonance Imaging, Models, Neurological, N-Methylaspartate, Neural Networks, Computer, Oxygen, Prefrontal Cortex, Psychomotor Performance, Reaction Time, Reward, Smell, Synapses, alpha-Amino-3-hydroxy-5-methyl-4-isoxazolepropionic Acid, gamma-Aminobutyric Acid