Human dreaming occurs during rapid eye movement (REM) sleep. To investigate the structure of neural activity during REM sleep, we simultaneously recorded the activity of multiple neurons in the rat hippocampus during both sleep and awake behavior. We show that temporally sequenced ensemble firing rate patterns reflecting tens of seconds to minutes of behavioral experience are reproduced during REM episodes at an equivalent timescale. Furthermore, within such REM episodes behavior-dependent modulation of the subcortically driven theta rhythm is also reproduced. These results demonstrate that long temporal sequences of patterned multineuronal activity suggestive of episodic memory traces are reactivated during REM sleep. Such reactivation may be important for memory processing and provides a basis for the electrophysiological examination of the content of dream states.

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Understanding the neural code is critical to linking brain and behavior. In sensory systems, divisive normalization seems to be a canonical neural computation, observed in areas ranging from retina to cortex and mediating processes including contrast adaptation, surround suppression, visual attention, and multisensory integration. Recent electrophysiological studies have extended these insights beyond the sensory domain, demonstrating an analogous algorithm for the value signals that guide decision making, but the effects of normalization on choice behavior are unknown. Here, we show that choice models using normalization generate significant (and classically irrational) choice phenomena driven by either the value or number of alternative options. In value-guided choice experiments, both monkey and human choosers show novel context-dependent behavior consistent with normalization. These findings suggest that the neural mechanism of value coding critically influences stochastic choice behavior and provide a generalizable quantitative framework for examining context effects in decision making.fundamental question in neuroscience is how the brain represents behaviorally relevant variables. Neural coding is governed by a small number of canonical computations implemented in diverse circuits and mechanisms, a prominent example being divisive normalization, in which the initial inputdriven activity of a neuron is divided by the summed activity of a large pool of neighboring neurons. Originally proposed to explain nonlinear responses in primary visual cortex (1), divisive normalization has been widely observed in sensory systems and characterizes responses including contrast gain control in the retina and thalamus (2, 3), surround suppression in the middle temporal area (4, 5), ventral stream responses to multiple objects (6), and gain control in auditory cortex (7). Normalization also explains neural activity underlying higher-order processes such as multisensory integration (8) and visual attention (9). This ubiquity may reflect the role of normalization in generating normative coding efficiency via processes such as gain control, feature invariance, and redundancy reduction (10-12).Recent neurophysiological evidence shows that such normalization processes extend beyond sensory areas to higherorder cortical areas involved in decision making. In parietal and premotor cortex, neurons specifying individual actions are strongly modulated by the value of those actions (13-16). Importantly, this value representation is encoded in a normalized form: Firing rates are increased by increases in the value of the represented action and suppressed by increases in the value of alternative actions (17-19). Such normalization, however, introduces an inherent context dependence in neural coding. In the visual system, normalization underlies contextual modulation of activity by extrareceptive field stimuli, for example surround suppression in visual cortical neurons (12,20). In decision-related areas, normalization produces an analogo...

SUMMARY The representation of value is a critical component of decision-making. Rational choice theory assumes that options are assigned absolute values, independent of the value or existence of other alternatives. However, context-dependent choice behavior in both animals and humans violates this assumption, suggesting that biological decision processes rely on comparative evaluation. Here we show that neurons in the monkey lateral intraparietal cortex (LIP) encode a relative form of saccadic value, explicitly dependent on the values of the other available alternatives. Analogous to extra-classical receptive field effects in visual cortex, this relative representation incorporates target values outside the response field and is observed in both stimulus-driven activity and baseline firing rates. This context-dependent modulation is precisely described by divisive normalization, indicating that this standard form of sensory gain control may be a general mechanism of cortical computation. Such normalization in decision circuits effectively implements an adaptive gain control for value coding and provides a possible mechanistic basis for behavioral context-dependent violations of rationality.