Anterior cingulate neurons signal neutral cue pairings during sensory preconditioning

Prefrontal encoding of an internal model for emotional inference

A key function of brain systems mediating emotion is to learn to anticipate unpleasant experiences. Although organisms readily associate sensory stimuli with aversive outcomes, higher-order forms of emotional learning and memory require inference to extrapolate the circumstances surrounding directly experienced aversive events to other indirectly related sensory patterns that were not part of the original experience. This type of learning requires internal models of emotion, which flexibly track directly experienced and inferred aversive associations. Although the brain mechanisms of simple forms of aversive learning have been well studied in areas such as the amygdala1-4, whether and how the brain forms and represents internal models of emotionally relevant associations are not known5. Here we report that neurons in the rodent dorsomedial prefrontal cortex (dmPFC) encode a flexible internal model of emotion by linking sensory stimuli in the environment with aversive events, whether they were directly or indirectly associated with that experience. These representations form through a multi-step encoding mechanism involving recruitment and stabilization of dmPFC cells that support inference. Although dmPFC population activity encodes all salient associations, dmPFC neurons projecting to the amygdala specifically represent and are required to express inferred associations. Together, these findings reveal how internal models of emotion are encoded in the dmPFC to regulate subcortical systems for recall of inferred emotional memories.

Integration of sensory and fear memories in the rat medial temporal lobe

Wong et al., 2019 used a sensory preconditioning protocol to examine how sensory and fear memories are integrated in the rat medial temporal lobe. In this protocol, rats integrate a sound-light (sensory) memory that forms in stage 1 with a light-shock (fear) memory that forms in stage 2 to generate fear responses (freezing) across test presentations of the sound in stage 3. Here, we advance this research by showing that (1) how/when rats integrate the sound-light and light-shock memories (online in stage 2 or at test in stage 3) changes with the number of sound-light pairings in stage 1; and (2) regardless of how/when it occurs, the integration requires communication between two regions of the medial temporal lobe: the perirhinal cortex and basolateral amygdala complex. Thus, 'event familiarity' determines how/when sensory and fear memories are integrated but not the circuitry by which the integration occurs: this remains the same.

Neural coding of choice and outcome are modulated by uncertainty in orbitofrontal but not secondary motor cortex

Orbitofrontal cortex (OFC) and secondary motor cortex (M2) are both implicated in flexible reward learning but the conditions that differentially recruit these regions are not fully understood. We imaged calcium activity from single neurons in OFC or M2 during de novo learning of uncertain reward probability schedules. Predictions of choice were decoded from M2 neurons with high accuracy under all certainty conditions, but were more accurately decoded from OFC neurons under greater uncertainty. In M2, the proportion of outcome-selective neurons decreased with uncertainty whereas this proportion remained stable in OFC, due to an increased recruitment of reward-selective neurons across levels of uncertainty. Decoding accuracy of both choice and outcome were predicted by indices of flexible strategy like Win-Stay and Lose-Shift in OFC, but not M2. When schedules were experienced in increasing and then decreasing uncertainty, chemogenetic perturbation of M2 and OFC neurons resulted in opposing roles in certain and uncertain conditions, respectively. Our results indicate that M2 neurons are causally involved in learning of more certain conditions, whereas OFC neurons preferentially encode choices and outcomes that foster greater reliance on adaptive strategies under conditions of uncertainty. This reveals a novel functional heterogeneity within frontal cortex in support of flexible learning.

Prefrontal neuronal ensembles link prior knowledge with novel actions during flexible action selection

We make decisions based on currently perceivable information or an internal model of the environment. The medial prefrontal cortex (mPFC) and its interaction with the hippocampus have been implicated in the latter, model-based decision-making; however, the underlying computational properties remain incompletely understood. We have examined mPFC spiking and hippocampal oscillatory activity while rats flexibly select new actions using a known associative structure of environmental cues and outcomes. During action selection, the mPFC reinstates representations of the associative structure. These awake reactivation events are accompanied by synchronous firings among neurons coding the associative structure and those coding actions. Moreover, their functional coupling is strengthened upon the reactivation events leading to adaptive actions. In contrast, only cue-coding neurons improve functional coupling during hippocampal sharp wave ripples. Thus, the lack of direct experience disconnects the mPFC from the hippocampus to independently form self-organized neuronal ensemble dynamics linking prior knowledge with novel actions.

Computationally Informed Interventions for Targeting Compulsive Behaviors

Compulsive behaviors are central to addiction and obsessive-compulsive disorder and can be understood as a failure of adaptive decision making. Particularly, they can be conceptualized as an imbalance in behavioral control, such that behavior is guided predominantly by learned rather than inferred outcome expectations. Inference is a computational process required for adaptive behavior, and recent work across species has identified the neural circuitry that supports inference-based decision making. This includes the orbitofrontal cortex, which has long been implicated in disorders of compulsive behavior. Inspired by evidence that modulating orbitofrontal cortex activity can alter inference-based behaviors, here we discuss noninvasive approaches to target these circuits in humans. Specifically, we discuss the potential of network-targeted transcranial magnetic stimulation and real-time neurofeedback to modulate the neural underpinnings of inference. Both interventions leverage recent advances in our understanding of the neurocomputational mechanisms of inference-based behavior and may be used to complement current treatment approaches for behavioral disorders.

Calcium activity is a degraded estimate of spikes

Recording action potentials extracellularly during behavior has led to fundamental discoveries regarding neural function-hippocampal neurons respond to locations in space,1 motor cortex neurons encode movement direction,2 and dopamine neurons signal reward prediction errors3-observations undergirding current theories of cognition,4 movement,5 and learning.6 Recently it has become possible to measure calcium flux, an internal cellular signal related to spiking. The ability to image calcium flux in anatomically7,8 or genetically9 identified neurons can extend our knowledge of neural circuit function by allowing activity to be monitored in specific cell types or projections, or in the same neurons across many days. However, while initial studies were grounded in prior unit recording work, it has become fashionable to assume that calcium is identical to spiking, even though the spike-to-fluorescence transformation is nonlinear, noisy, and unpredictable under real-world conditions.10 It remains an open question whether calcium provides a high-fidelity representation of single-unit activity in awake, behaving subjects. Here, we have addressed this question by recording both signals in the lateral orbitofrontal cortex (OFC) of rats during olfactory discrimination learning. Activity in the OFC during olfactory learning has been well-studied in humans,11,12,13,14 nonhuman primates,15,16 and rats,17,18,19,20,21 where it has been shown to signal information about both the sensory properties of odor cues and the rewards they predict. Our single-unit results replicated prior findings, whereas the calcium signal provided only a degraded estimate of the information available in the single-unit spiking, reflecting primarily reward value.

Flexibility of memory for future-oriented cognition

Memories of daily experiences contain incidental details unique to each experience as well as common latent patterns shared with others. Neural representations focusing on the latter aspect can be reinstated by similar new experiences even though their perceptual features do not match the original experiences perfectly. Such flexible memory use allows for faster learning and better decision-making in novel situations. Here, I review evidence from rodent and primate electrophysiological studies to discuss how memory flexibility is implemented in the spiking activity of neuronal ensembles. These findings uncovered innate and learned coding properties and their potential refinement during sleep that support flexible integration and application of memories for better future adaptation.