Beta traveling waves in monkey frontal and parietal areas encode recent reward history.

Brain function depends on neural communication, but the mechanisms of this communication are not well understood. Recent studies suggest that one form of neural communication is through traveling waves (TWs)-patterns of neural oscillations that propagate within and between brain areas. We show that TWs are robust in microarray recordings in frontal and parietal cortex and encode recent reward history. Two adult male monkeys made saccades to obtain probabilistic rewards and were sensitive to the (statistically irrelevant) reward on the previous trial. TWs in frontal and parietal areas were stronger in trials that followed a prior reward versus a lack of reward and, in the frontal lobe, correlated with the monkeys' behavioral sensitivity to the prior reward. The findings suggest that neural communication mediated by TWs within the frontal and parietal lobes contribute to maintaining information about recent reward history and mediating the impact of this history on the monkeys' expectations.

Uncertainty modulates visual maps during noninstrumental information demand.

Animals are intrinsically motivated to obtain information independently of instrumental incentives. This motivation depends on two factors: a desire to resolve uncertainty by gathering accurate information and a desire to obtain positively-valenced observations, which predict favorable rather than unfavorable outcomes. To understand the neural mechanisms, we recorded parietal cortical activity implicated in prioritizing stimuli for spatial attention and gaze, in a task in which monkeys were free (but not trained) to obtain information about probabilistic non-contingent rewards. We show that valence and uncertainty independently modulated parietal neuronal activity, and uncertainty but not reward-related enhancement consistently correlated with behavioral sensitivity. The findings suggest uncertainty-driven and valence-driven information demand depend on partially distinct pathways, with the former being consistently related to parietal responses and the latter depending on additional mechanisms implemented in downstream structures.

Reward uncertainty asymmetrically affects information transmission within the monkey fronto-parietal network.

A central hypothesis in research on executive function is that controlled information processing is costly and is allocated according to the behavioral benefits it brings. However, while computational theories predict that the benefits of new information depend on prior uncertainty, the cellular effects of uncertainty on the executive network are incompletely understood. Using simultaneous recordings in monkeys, we describe several mechanisms by which the fronto-parietal network reacts to uncertainty. We show that the variance of expected rewards, independently of the value of the rewards, was encoded in single neuron and population spiking activity and local field potential (LFP) oscillations, and, importantly, asymmetrically affected fronto-parietal information transmission (measured through the coherence between spikes and LFPs). Higher uncertainty selectively enhanced information transmission from the parietal to the frontal lobe and suppressed it in the opposite direction, consistent with Bayesian principles that prioritize sensory information according to a decision maker's prior uncertainty.

Parietal neurons encode expected gains in instrumental information.

In natural behavior, animals have access to multiple sources of information, but only a few of these sources are relevant for learning and actions. Beyond choosing an appropriate action, making good decisions entails the ability to choose the relevant information, but fundamental questions remain about the brain's information sampling policies. Recent studies described the neural correlates of seeking information about a reward, but it remains unknown whether, and how, neurons encode choices of instrumental information, in contexts in which the information guides subsequent actions. Here we show that parietal cortical neurons involved in oculomotor decisions encode, before an information sampling saccade, the reduction in uncertainty that the saccade is expected to bring for a subsequent action. These responses were distinct from the neurons' visual and saccadic modulations and from signals of expected reward or reward prediction errors. Therefore, even in an instrumental context when information and reward gains are closely correlated, individual cells encode decision variables that are based on informational factors and can guide the active sampling of action-relevant cues.

Novelty enhances visual salience independently of reward in the parietal lobe.

Novelty modulates sensory and reward processes, but it remains unknown how these effects interact, i.e., how the visual effects of novelty are related to its motivational effects. A widespread hypothesis, based on findings that novelty activates reward-related structures, is that all the effects of novelty are explained in terms of reward. According to this idea, a novel stimulus is by default assigned high reward value and hence high salience, but this salience rapidly decreases if the stimulus signals a negative outcome. Here we show that, contrary to this idea, novelty affects visual salience in the monkey lateral intraparietal area (LIP) in ways that are independent of expected reward. Monkeys viewed peripheral visual cues that were novel or familiar (received few or many exposures) and predicted whether the trial will have a positive or a negative outcome--i.e., end in a reward or a lack of reward. We used a saccade-based assay to detect whether the cues automatically attracted or repelled attention from their visual field location. We show that salience--measured in saccades and LIP responses--was enhanced by both novelty and positive reward associations, but these factors were dissociable and habituated on different timescales. The monkeys rapidly recognized that a novel stimulus signaled a negative outcome (and withheld anticipatory licking within the first few presentations), but the salience of that stimulus remained high for multiple subsequent presentations. Therefore, novelty can provide an intrinsic bonus for attention that extends beyond the first presentation and is independent of physical rewards.

The object advantage can be eliminated under equiluminant conditions.

A key phenomenon supporting the existence of object-based attention is the object advantage, in which responses are faster for within-object, relative to equidistant between-object, shifts of attention. The origins of this effect have been variously ascribed to low-level "bottom-up" sensory processing and to a cognitive "top-down" strategy of within-object attention prioritization. The degree to which the object advantage depends on lower-level sensory processing was examined by differentially stimulating the magnocellular (M) and parvocellular (P) retino-geniculo-cortical visual pathways by using equiluminant and nonequiluminant conditions. We found that the object advantage can be eliminated when M activity is reduced using psychophysically equiluminant stimuli. This novel result in normal observers suggests that the origin of the object advantage is found in lower-level sensory processing rather than a general cognitive process, which should not be so sensitive to differential activation of the bottom-up P and M pathways. Eliminating the object advantage while maintaining a spatial-cueing advantage with reduced M activity suggests that the notion of independent M-driven spatial attention and P-driven object attention requires revision.

Neural correlates of temporal credit assignment in the parietal lobe.

Empirical studies of decision making have typically assumed that value learning is governed by time, such that a reward prediction error arising at a specific time triggers temporally-discounted learning for all preceding actions. However, in natural behavior, goals must be acquired through multiple actions, and each action can have different significance for the final outcome. As is recognized in computational research, carrying out multi-step actions requires the use of credit assignment mechanisms that focus learning on specific steps, but little is known about the neural correlates of these mechanisms. To investigate this question we recorded neurons in the monkey lateral intraparietal area (LIP) during a serial decision task where two consecutive eye movement decisions led to a final reward. The underlying decision trees were structured such that the two decisions had different relationships with the final reward, and the optimal strategy was to learn based on the final reward at one of the steps (the "F" step) but ignore changes in this reward at the remaining step (the "I" step). In two distinct contexts, the F step was either the first or the second in the sequence, controlling for effects of temporal discounting. We show that LIP neurons had the strongest value learning and strongest post-decision responses during the transition after the F step regardless of the serial position of this step. Thus, the neurons encode correlates of temporal credit assignment mechanisms that allocate learning to specific steps independently of temporal discounting.

Neural dynamics of object-based multifocal visual spatial attention and priming: object cueing, useful-field-of-view, and crowding.

How are spatial and object attention coordinated to achieve rapid object learning and recognition during eye movement search? How do prefrontal priming and parietal spatial mechanisms interact to determine the reaction time costs of intra-object attention shifts, inter-object attention shifts, and shifts between visible objects and covertly cued locations? What factors underlie individual differences in the timing and frequency of such attentional shifts? How do transient and sustained spatial attentional mechanisms work and interact? How can volition, mediated via the basal ganglia, influence the span of spatial attention? A neural model is developed of how spatial attention in the where cortical stream coordinates view-invariant object category learning in the what cortical stream under free viewing conditions. The model simulates psychological data about the dynamics of covert attention priming and switching requiring multifocal attention without eye movements. The model predicts how "attentional shrouds" are formed when surface representations in cortical area V4 resonate with spatial attention in posterior parietal cortex (PPC) and prefrontal cortex (PFC), while shrouds compete among themselves for dominance. Winning shrouds support invariant object category learning, and active surface-shroud resonances support conscious surface perception and recognition. Attentive competition between multiple objects and cues simulates reaction-time data from the two-object cueing paradigm. The relative strength of sustained surface-driven and fast-transient motion-driven spatial attention controls individual differences in reaction time for invalid cues. Competition between surface-driven attentional shrouds controls individual differences in detection rate of peripheral targets in useful-field-of-view tasks. The model proposes how the strength of competition can be mediated, though learning or momentary changes in volition, by the basal ganglia. A new explanation of crowding shows how the cortical magnification factor, among other variables, can cause multiple object surfaces to share a single surface-shroud resonance, thereby preventing recognition of the individual objects.

Characterization of orderly spatiotemporal patterns of clock gene activation in mammalian suprachiasmatic nucleus.

Because we can observe oscillation within individual cells and in the tissue as a whole, the suprachiasmatic nucleus (SCN) presents a unique system in the mammalian brain for the analysis of individual cells and the networks of which they are a part. While dispersed cells of the SCN sustain circadian oscillations in isolation, they are unstable oscillators that require network interactions for robust cycling. Using cluster analysis to assess bioluminescence in acute brain slices from PERIOD2::Luciferase (PER2::LUC) knockin mice, and immunochemistry of SCN from animals harvested at various circadian times, we assessed the spatiotemporal activation patterns of PER2 to explore the emergence of a coherent oscillation at the tissue level. The results indicate that circadian oscillation is characterized by a stable daily cycle of PER2 expression involving orderly serial activation of specific SCN subregions, followed by a silent interval, with substantial symmetry between the left and right side of the SCN. The biological significance of the clusters identified in living slices was confirmed by co-expression of LUC and PER2 in fixed, immunochemically stained brain sections, with the spatiotemporal pattern of LUC expression resembling that revealed in the cluster analysis of bioluminescent slices. We conclude that the precise timing of PER2 expression within individual neurons is dependent on their location within the nucleus, and that small groups of neurons within the SCN give rise to distinctive and identifiable subregions. We propose that serial activation of these subregions is the basis of robustness and resilience of the daily rhythm of the SCN.

Modeling the behavior of coupled cellular circadian oscillators in the suprachiasmatic nucleus.

The suprachiasmatic nucleus (SCN) in the hypothalamus is the site of the master circadian clock in mammals, a complex tissue composed of multiple, coupled, single-cell circadian oscillators. Mathematical modeling is now providing insights on how individual SCN cells might interact and assemble to create an integrated pacemaker that governs the circadian behavior of whole animals. In this article, we will discuss the neurobiological constraints for modeling SCN behavior, system precision, implications of cellular heterogeneity, and analysis of heterogeneously coupled oscillator networks. Mathematical approaches will be critical for better understanding intercellular interactions within the SCN.

Gates and oscillators II: zeitgebers and the network model of the brain clock.

Circadian rhythms in physiology and behavior are regulated by the SCN. When assessed by expression of clock genes, at least 2 distinct functional cell types are discernible within the SCN: nonrhythmic, light-inducible, retinorecipient cells and rhythmic autonomous oscillator cells that are not directly retinorecipient. To predict the responses of the circadian system, the authors have proposed a model based on these biological properties. In this model, output of rhythmic oscillator cells regulates the activity of the gate cells. The gate cells provide a daily organizing signal that maintains phase coherence among the oscillator cells. In the absence of external stimuli, this arrangement yields a multicomponent system capable of producing a self-sustained consensus rhythm. This follow-up study considers how the system responds when the gate cells are activated by an external stimulus, simulating a response to an entraining (or phase-setting) signal. In this model, the authors find that the system can be entrained to periods within the circadian range, that the free-running system can be phase shifted by timed activation of the gate, and that the phase response curve for activation is similar to that observed when animals are exposed to a light pulse. Finally, exogenous triggering of the gate over a number of days can organize an arrhythmic system, simulating the light-dependent reappearance of rhythmicity in a population of disorganized, independent oscillators. The model demonstrates that a single mechanism (i.e., the output of gate cells) can account for not only free-running and entrained rhythmicity but also other circadian phenomena, including limits of entrainment, a PRC with both delay and advance zones, and the light-dependent reappearance of rhythmicity in an arrhythmic animal.

Two antiphase oscillations occur in each suprachiasmatic nucleus of behaviorally split hamsters.

The suprachiasmatic nuclei (SCNs) control circadian rhythms of numerous behavioral and physiological responses. In hamsters, constant light causes "splitting" of circadian rhythms, such that a single daily bout of activity separates into two components, 12 h apart, with antiphase circadian oscillations in the left and right SCN. Given the phenotypic and functional heterogeneity of the SCN, in which ventrolateral but not dorsomedial neurons are retinorecipient, we asked how these two compartments respond to the constant lighting conditions that produce splitting, using three different phase markers of neuronal activity: PER1 (Period 1), c-FOS, and pERK (phosphorylated extracellular signal-regulated kinase). We report the emergence of a coherent novel network in which each side of the SCN exhibits two antiphase oscillating subregions, here termed "core-like" and "shell-like," in addition to the known antiphase oscillation between the right and left SCN. The novel SCN response entails a coherent rhythm in a core-like region of the SCN, which otherwise is not cycling. A mathematical model is presented, and this model interprets the observed changes in the proportion of in-phase and antiphase populations of SCN oscillators and suggests novel testable hypotheses. Finally, the functional significance of this network was explored by investigating the adjacent hypothalamus. Activation of the paraventricular nucleus is in-phase with the ipsilateral core-like SCN, whereas activation of the lateral subparaventricular zone is in-phase with the ipsilateral shell-like SCN, pointing to a multiplicity of SCN output signals. These results suggest a neural basis for internal coincidence of SCN oscillators, and a novel mechanism of plasticity in SCN neural networks and outputs.

Gates and oscillators: a network model of the brain clock.

The suprachiasmatic nuclei (SCN) control circadian oscillations of physiology and behavior. Measurements of electrical activity and of gene expression indicate that these heterogeneous structures are composed of both rhythmic and nonrhythmic cells. A fundamental question with regard to the organization of the circadian system is how the SCN achieve a coherent output while their constituent independent cellular oscillators express a wide range of periods. Previously, the consensus output of individual oscillators had been attributed to coupling among cells. The authors propose a model that incorporates nonrhythmic "gate" cells and rhythmic oscillator cells with a wide range of periods, that neither requires nor excludes a role for interoscillator coupling. The gate provides daily input to oscillator cells and is in turn regulated (directly or indirectly) by the oscillator cells. In the authors' model, individual oscillators with initial random phases are able to self-assemble so as to maintain cohesive rhythmic output. In this view, SCN circuits are important for self-sustained oscillation, and their network properties distinguish these nuclei from other tissues that rhythmically express clock genes. The model explains how individual SCN cells oscillate independently and yet work together to produce a coherent rhythm.