Neural activity has been suggested to initially trigger ATP production by glycolysis, rather than oxidative phosphorylation, for three reasons: glycolytic enzymes are associated with ion pumps; neurons may increase their energy supply by activating glycolysis in astrocytes to generate lactate; and activity increases glucose uptake more than O 2 uptake. In rat hippocampal slices, neuronal activity rapidly decreased the levels of extracellular O 2 and intracellular NADH (reduced nicotinamide adenine dinucleotide), even with lactate dehydrogenase blocked to prevent lactate generation, or with only 20% superfused O 2 to mimic physiological O 2 levels. Pharmacological analysis revealed an energy budget in which 11% of O 2 use was on presynaptic action potentials, 17% was on presynaptic Ca 2ϩ entry and transmitter release, 46% was on postsynaptic glutamate receptors, and 26% was on postsynaptic action potentials, in approximate accord with theoretical brain energy budgets. Thus, the major mechanisms mediating brain information processing are all initially powered by oxidative phosphorylation, and an astrocyte-neuron lactate shuttle is not needed for this to occur.

SummaryAdaptive success in social animals depends on an ability to infer the likely actions of others. Little is known about the neural computations that underlie this capacity. Here, we show that the brain models the values and choices of others even when these values are currently irrelevant. These modeled choices use the same computations that underlie our own choices, but are resolved in a distinct neighboring medial prefrontal brain region. Crucially, however, when subjects choose on behalf of a partner instead of themselves, these regions exchange their functional roles. Hence, regions that represented values of the subject’s executed choices now represent the values of choices executed on behalf of the partner, and those that previously modeled the partner now model the subject. These data tie together neural computations underlying self-referential and social inference, and in so doing establish a new functional axis characterizing the medial wall of prefrontal cortex.

Integrating costs and benefits is crucial for optimal decision-making. Although much is known about decisions that involve outcomerelated costs (e.g., delay, risk), many of our choices are attached to actions and require an evaluation of the associated motor costs. Yet how the brain incorporates motor costs into choices remains largely unclear. We used human fMRI during choices involving monetary reward and physical effort to identify brain regions that serve as a choice comparator for effort-reward trade-offs. By independently varying both options' effort and reward levels, we were able to identify the neural signature of a comparator mechanism. A network involving supplementary motor area and the caudal portion of dorsal anterior cingulate cortex encoded the difference in reward (positively) and effort levels (negatively) between chosen and unchosen choice options. We next modeled effort-discounted subjective values using a novel behavioral model. This revealed that the same network of regions involving dorsal anterior cingulate cortex and supplementary motor area encoded the difference between the chosen and unchosen options' subjective values, and that activity was best described using a concave model of effort-discounting. In addition, this signal reflected how precisely value determined participants' choices. By contrast, separate signals in supplementary motor area and ventromedial prefrontal cortex correlated with participants' tendency to avoid effort and seek reward, respectively. This suggests that the critical neural signature of decision-making for choices involving motor costs is found in human cingulate cortex and not ventromedial prefrontal cortex as typically reported for outcome-based choice. Furthermore, distinct frontal circuits seem to drive behavior toward reward maximization and effort minimization.