Nicholas C. Foley

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 areas. We show that TWs appear robustly in microarray recordings in monkey frontal and parietal cortex and encode memory for recent rewards. While making saccades to obtain probabilistic rewards, monkeys were sensitive to the (statistically irrelevant) prior reward, which is consistent with behavioral biases produced by reward history. TWs in frontal and parietal areas were stronger in trials following a prior reward versus a lack of reward and, in the frontal lobe, correlated with the monkeys’ sensitivity to the prior reward. The findings suggest that neural communication across fronto-parietal areas, reflected by TWs, maintains default reward memories, while communication within the frontal lobe mediates the read out of the memories for prospective expectations.

Computing expectancy violations is essential for decision making and cognitive functions, but its neural mechanisms are incompletely understood. We describe a novel mechanism by which prefrontal and posterior parietal neurons encode reward prediction errors (RPEs) in their population but not single-neuron activity. Simultaneous recordings of neural populations showed that both areas co-activated information about experienced and expected rewards in a precise opponent organization. Neurons encoding expected rewards with positive (negative) scaling were reactivated simultaneously with those encoding experienced rewards with negative (positive) scaling. This opponent organization was mirrored in polarity-dependent noise correlations. Moreover, it extended to two types of expectancy information – based on task-relevant visual cues and statistically irrelevant reward history - allowing decoding of signed and unsigned RPE in two reference frames. Frontal and parietal areas implement canonical computations that facilitate contextual comparisons and the readout of multiple types of expectancy violations to flexibly serve behavioral goals.

Significance: We examine how the brain guides active sensing in awake, behaving primates using a paradigm in which information sampling is dissociated from reinforcement variables, such as cumulative future reward or reward prediction errors. We show that target selective cells in lateral intraparietal cortex encode decision variables based on expected gains in instrumental information—the extent to which a visual cue, when discriminated, is expected to reduce the uncertainty of a subsequent action.

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.

To serve as a robust internal circadian clock, the cell‐autonomous molecular and electrophysiological activities of the individual neurons of the mammalian suprachiasmatic nucleus (SCN) are coordinated in time and neuroanatomical space. Although the contributions of the chemical and electrical interconnections between neurons are essential to this circuit‐level orchestration, the features upon which they operate to confer robustness to the ensemble signal are not known. To address this, we applied several methods to deconstruct the interactions between the spatial and temporal organisation of circadian oscillations in organotypic slices from mice with circadian abnormalities. We studied the SCN of mice lacking Cryptochrome genes (Cry1 and Cry2), which are essential for cell‐autonomous oscillation, and the SCN of mice lacking the vasoactive intestinal peptide receptor 2 (VPAC2‐null), which is necessary for circuit‐level integration, in order to map biological mechanisms to the revealed oscillatory features. The SCN of wild‐type mice showed a strong link between the temporal rhythm of the bioluminescence profiles of PER2::LUC and regularly repeated spatially organised oscillation. The Cry‐null SCN had stable spatial organisation but lacked temporal organisation, whereas in VPAC2‐null SCN some specimens exhibited temporal organisation in the absence of spatial organisation. The results indicated that spatial and temporal organisation were separable, that they may have different mechanistic origins (cell‐autonomous vs. interneuronal signaling) and that both were necessary to maintain robust and organised circadian rhythms throughout the SCN. This study therefore provided evidence that the coherent emergent properties of the neuronal circuitry, revealed in the spatially organised clusters, were essential to the pacemaking function of the SCN.

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.

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.

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.

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.