Delta Rhythm Orchestrates the Neural Activity Underlying the Resting State BOLD Signal via Phase-amplitude Coupling.

Spontaneous ongoing neuronal activity is a prominent feature of the mammalian brain. Temporal and spatial patterns of such ongoing activity have been exploited to examine large-scale brain network organization and function. However, the neurophysiological basis of this spontaneous brain activity as detected by resting-state functional Magnetic Resonance Imaging (fMRI) remains poorly understood. To this end, multi-site local field potentials (LFP) and blood oxygenation level-dependent (BOLD) fMRI were simultaneously recorded in the rat striatum along with local pharmacological manipulation of striatal activity. Results demonstrate that delta (δ) band LFP power negatively, while beta (ß) and gamma (γ) band LFPs positively correlated with BOLD fluctuation. Furthermore, there was strong cross-frequency phase-amplitude coupling (PAC), with the phase of δ LFPs significantly modulating the amplitude of the high frequency signal. Enhancing dopaminergic neuronal activity significantly reduced ventral striatal functional connectivity, δ LFP-BOLD correlation, and the PAC effect. These data suggest that different frequency bands of the LFP contribute distinctively to BOLD spontaneous fluctuation and that PAC is the organizing mechanism through which low frequency LFPs orchestrate neural activity that underlies resting state functional connectivity.

The Behavioral Relevance of Cortical Neural Ensemble Responses Emerges Suddenly.

Whereas many laboratory-studied decisions involve a highly trained animal identifying an ambiguous stimulus, many naturalistic decisions do not. Consumption decisions, for instance, involve determining whether to eject or consume an already identified stimulus in the mouth and are decisions that can be made without training. By standard analyses, rodent cortical single-neuron taste responses come to predict such consumption decisions across the 500 ms preceding the consumption or rejection itself; decision-related firing emerges well after stimulus identification. Analyzing single-trial ensemble activity using hidden Markov models, we show these decision-related cortical responses to be part of a reliable sequence of states (each defined by the firing rates within the ensemble) separated by brief state-to-state transitions, the latencies of which vary widely between trials. When we aligned data to the onset of the (late-appearing) state that dominates during the time period in which single-neuron firing is correlated to taste palatability, the apparent ramp in stimulus-aligned choice-related firing was shown to be a much more precipitous coherent jump. This jump in choice-related firing resembled a step function more than it did the output of a standard (ramping) decision-making model, and provided a robust prediction of decision latency in single trials. Together, these results demonstrate that activity related to naturalistic consumption decisions emerges nearly instantaneously in cortical ensembles. Significance statement: This paper provides a description of how the brain makes evaluative decisions. The majority of work on the neurobiology of decision making deals with "what is it?" decisions; out of this work has emerged a model whereby neurons accumulate information about the stimulus in the form of slowly increasing firing rates and reach a decision when those firing rates reach a threshold. Here, we study a different kind of more naturalistic decision--a decision to evaluate "what shall I do with it?" after the identity of a taste in the mouth has been identified--and show that this decision is not made through the gradual increasing of stimulus-related firing, but rather that this decision appears to be made in a sudden moment of "insight."

Medial Orbitofrontal Neurons Preferentially Signal Cues Predicting Changes in Reward during Unblocking.

UNLABELLED: The orbitofrontal cortex (OFC) has been broadly implicated in the ability to use the current value of expected outcomes to guide behavior. Although value correlates have been prominently reported in lateral OFC, they are more often associated with more medial areas. Further, recent studies in primates have suggested a dissociation in which the lateral OFC is involved in credit assignment and representation of reward identity and more medial areas are critical to representing value. Previously, we used unblocking to test more specifically what information about outcomes is represented by OFC neurons in rats; consistent with the proposed dichotomy between the lateral and medial OFC, we found relatively little linear value coding in the lateral OFC (Lopatina et al., 2015). Here we have repeated this experiment, recording in the medial OFC, to test whether such value signals might be found there. Neurons were recorded in an unblocking task as rats learned about cues that signaled either more, less, or the same amount of reward. We found that medial OFC neurons acquired responses to these cues; however, these responses did not signal different reward values across cues. Surprisingly, we found that cells developed responses to cues predicting a change, particularly a decrease, in reward value. This is consistent with a special role for medial OFC in representing current value to support devaluation/revaluation sensitive changes in behavior. SIGNIFICANCE STATEMENT: This study uniquely examines encoding in rodent mOFC at the single-unit level in response to cues that predict more, less, or no change in reward in rats during training in a Pavlovian unblocking task, finding more cells responding to change-predictive cues and stronger activity in response to cues predictive of less reward.

Sodium concentration coding gives way to evaluative coding in cortex and amygdala.

Typically, stimulus batteries used to characterize sensory neural coding span physical parameter spaces (e.g., concentration: from low to high). For awake animals, however, psychological variables (e.g., pleasantness/palatability) with complicated relationships to the physical often dominate neural responses. Here we pit physical and psychological axes against one another, presenting awake rats with a stimulus set including 4 NaCl concentrations (0.01, 0.1, 0.3, and 1.0 m) plus palatable (0.3 m sucrose) and aversive (0.001 m quinine) benchmarks, while recording the activity of neurons in two sites vital for NaCl taste processing, gustatory cortex (GC) and central amygdala (CeA). Since NaCl palatability (i.e., preference) follows a non-monotonic, "inverted-U-shaped" curve while concentration increases monotonically, this stimulus battery allowed us to test whether GC and CeA responses better reflect external or internal variables. As predicted, GC single-neuron and population responses reflected both parameters in separate response epochs: sodium concentration-related information appeared with the earliest taste-specific responses, giving way to palatability-related information, in an overlapping subset of neurons, several hundred milliseconds later. CeA single-neuron and population responses, meanwhile, contained only a brief period of concentration specificity, occurring just before palatability-related information emerged (simultaneously with, or slightly later than, in GC). Thus, cortex and amygdala both prominently reflect NaCl palatability late in their responses; CeA neurons largely respond to either palatable or aversive stimuli, while GC responses tend to reflect the entire palatability spectrum in a graded fashion.

Natural stimuli evoke dynamic sequences of states in sensory cortical ensembles.

Although temporal coding is a frequent topic of neurophysiology research, trial-to-trial variability in temporal codes is typically dismissed as noise and thought to play no role in sensory function. Here, we show that much of this supposed "noise" faithfully reflects stimulus-related processes carried out in coherent neural networks. Cortical neurons responded to sensory stimuli by progressing through sequences of states, identifiable only in examinations of simultaneously recorded ensembles. The specific times at which ensembles transitioned from state to state varied from trial to trial, but the state sequences were reliable and stimulus-specific. Thus, the characterization of ensemble responses in terms of state sequences captured facets of sensory processing that are missing from, and obscured in, other analyses. This work provides evidence that sensory neurons act as parts of a systems-level dynamic process, the nature of which can best be appreciated through observation of distributed ensembles.

Orbitofrontal neurons signal sensory associations underlying model-based inference in a sensory preconditioning task.

Using knowledge of the structure of the world to infer value is at the heart of model-based reasoning and relies on a circuit that includes the orbitofrontal cortex (OFC). Some accounts link this to the representation of biological significance or value by neurons in OFC, while other models focus on the representation of associative structure or cognitive maps. Here we tested between these accounts by recording OFC neurons in rats during an OFC-dependent sensory preconditioning task. We found that while OFC neurons were strongly driven by biological significance or reward predictions at the end of training, they also showed clear evidence of acquiring the incidental stimulus-stimulus pairings in the preconditioning phase, prior to reward training. These results support a role for OFC in representing associative structure, independent of value.

Toward a theoretical role for tonic norepinephrine in the orbitofrontal cortex in facilitating flexible learning.

To adaptively respond in a complex, changing world, animals need to flexibly update their understanding of the world when their expectations are violated. Though several brain regions in rodents and primates have been implicated in aspects of this updating, current models of orbitofrontal cortex (OFC) and norepinephrine neurons of the locus coeruleus (LC-NE) suggest that each plays a role in responding to environmental change, where the OFC allows updating of prior learning to occur without overwriting or unlearning one's previous understanding of the world that changed, while elevated tonic NE allows for increased flexibility in behavior that tracks an animal's uncertainty. In light of recent studies highlighting a specific LC-NE projection to the OFC, in this review we discuss current models of OFC and NE function, and their potential synergy in the updating of associations following environmental change.

Ensembles in medial and lateral orbitofrontal cortex construct cognitive maps emphasizing different features of the behavioral landscape.

The orbitofrontal cortex (OFC) has long been implicated in the ability to use the current value of expected outcomes to guide behavior. More recently, this specific role has been conceptualized as a special case of a more general function that OFC plays in constructing a "cognitive map" of the behavioral task space by labeling the current task state and learning relationships among task states. Here, we have used single unit recording data from 2 prior studies to examine whether and how information relating different states within and across trials is represented in medial versus lateral OFC in rats. Using a hierarchical clustering analysis, we examined how neurons from each area represented information about differently valued trial types, defined by the cue-outcome pairings, versus how those same neurons represented information about similar epochs between these different trial types, such as the stimulus sample, delay, and reward consumption epochs. This analysis revealed that ensembles in the lateral OFC (lOFC) group states according to trial epoch, whereas those in the medial OFC (mOFC) organize the same states by trial type. These results suggest that the lOFC and mOFC construct cognitive maps that emphasize different features of the behavioral landscape, with lOFC tracking events based on local similarities, irrespective of their values and mOFC tracking more distal or higher order relationships relevant to value. (PsycINFO Database Record

Midbrain dopamine neurons compute inferred and cached value prediction errors in a common framework.

Midbrain dopamine neurons have been proposed to signal reward prediction errors as defined in temporal difference (TD) learning algorithms. While these models have been extremely powerful in interpreting dopamine activity, they typically do not use value derived through inference in computing errors. This is important because much real world behavior - and thus many opportunities for error-driven learning - is based on such predictions. Here, we show that error-signaling rat dopamine neurons respond to the inferred, model-based value of cues that have not been paired with reward and do so in the same framework as they track the putative cached value of cues previously paired with reward. This suggests that dopamine neurons access a wider variety of information than contemplated by standard TD models and that, while their firing conforms to predictions of TD models in some cases, they may not be restricted to signaling errors from TD predictions.

Lateral orbitofrontal neurons acquire responses to upshifted, downshifted, or blocked cues during unblocking.

The lateral orbitofrontal cortex (lOFC) has been described as signaling either outcome expectancies or value. Previously, we used unblocking to show that lOFC neurons respond to a predictive cue signaling a 'valueless' change in outcome features (McDannald, 2014). However, many lOFC neurons also fired to a cue that simply signaled more reward. Here, we recorded lOFC neurons in a variant of this task in which rats learned about cues that signaled either more (upshift), less (downshift) or the same (blocked) amount of reward. We found that neurons acquired responses specifically to one of the three cues and did not fire to the other two. These results show that, at least early in learning, lOFC neurons fire to valued cues in a way that is more consistent with signaling of the predicted outcome's features than with signaling of a general, abstract or cached value that is independent of the outcome.