Calcium activity is a degraded estimate of spikes

Hippocampal and orbitofrontal neurons contribute to complementary aspects of associative structure

The ability to establish associations between environmental stimuli is fundamental for higher-order brain functions like state inference and generalization. Both the hippocampus and orbitofrontal cortex (OFC) play pivotal roles in this, demonstrating complex neural activity changes after associative learning. However, how precisely they contribute to representing learned associations remains unclear. Here, we train head-restrained mice to learn four 'odor-outcome' sequence pairs composed of several task variables-the past and current odor cues, sequence structure of 'cue-outcome' arrangement, and the expected outcome; and perform calcium imaging from these mice throughout learning. Sequence-splitting signals that distinguish between paired sequences are detected in both brain regions, reflecting associative memory formation. Critically, we uncover differential contents in represented associations by examining, in each area, how these task variables affect splitting signal generalization between sequence pairs. Specifically, the hippocampal splitting signals are influenced by the combination of past and current cues that define a particular sensory experience. In contrast, the OFC splitting signals are similar between sequence pairs that share the same sequence structure and expected outcome. These findings suggest that the hippocampus and OFC uniquely and complementarily organize the acquired associative structure.

Learning enhances representations of taste-guided decisions in the mouse gustatory insular cortex

Learning to discriminate overlapping gustatory stimuli that predict distinct outcomes-a feat known as discrimination learning-can mean the difference between ingesting a poison or a nutritive meal. Despite the obvious importance of this process, very little is known about the neural basis of taste discrimination learning. In other sensory modalities, this form of learning can be mediated by either the sharpening of sensory representations or the enhanced ability of "decision-making" circuits to interpret sensory information. Given the dual role of the gustatory insular cortex (GC) in encoding both sensory and decision-related variables, this region represents an ideal site for investigating how neural activity changes as animals learn a novel taste discrimination. Here, we present results from experiments relying on two-photon calcium imaging of GC neural activity in mice performing a taste-guided mixture discrimination task. The task allows for the recording of neural activity before and after learning induced by training mice to discriminate increasingly similar pairs of taste mixtures. Single-neuron and population analyses show a time-varying pattern of activity, with early sensory responses emerging after taste delivery and binary, choice-encoding responses emerging later in the delay before a decision is made. Our results demonstrate that, while both sensory and decision-related information is encoded by GC in the context of a taste mixture discrimination task, learning and improved performance are associated with a specific enhancement of decision-related responses.

Orbitofrontal and Prelimbic Cortices Serve Complementary Roles in Adapting Reward Seeking to Learned Anxiety

BACKGROUND

Anxiety is a common symptom of several mental health disorders and adversely affects motivated behaviors. Anxiety can emerge from associating risk of future harm while engaged in goal-guided actions. Using a recently developed behavioral paradigm to model this aspect of anxiety, we investigated the role of 2 cortical subregions, the prelimbic medial frontal cortex (PL) and lateral orbitofrontal cortex (lOFC), which have been implicated in anxiety and outcome expectation, in flexible representation of actions associated with harm risk.

METHODS

A seek-take reward-guided instrumental task design was used to train animals (N = 8) to associate the seek action with a variable risk of punishment. After learning, animals underwent extinction training for this association. Fiber photometry was used to measure and compare neuronal activity in the PL and lOFC during learning and extinction.

RESULTS

Animals increased action suppression in response to punishment contingencies. This increase dissipated after extinction training. These behavioral changes were associated with region-specific changes in neuronal activity. PL neuronal activity preferentially adapted to the threat of punishment, whereas lOFC activity adapted to safe aspects of the task. Moreover, correlated activity between these regions was suppressed during actions associated with harm risk, suggesting that these regions may guide behavior independently under anxiety.

CONCLUSIONS

These findings suggest that the PL and lOFC serve distinct but complementary roles in the representation of learned anxiety. This dissociation may provide a mechanism to explain how overlapping cortical systems are implicated in reward-guided action execution during anxiety.

Egocentric processing of items in spines, dendrites, and somas in the retrosplenial cortex

Egocentric representations of external items are essential for spatial navigation and memory. Here, we explored the neural mechanisms underlying egocentric processing in the retrosplenial cortex (RSC), a pivotal area for memory and navigation. Using one-photon and two-photon calcium imaging, we identified egocentric tuning for environment boundaries in dendrites, spines, and somas of RSC neurons (egocentric boundary cells) in the open-field task. Dendrites with egocentric tuning tended to have similarly tuned spines. We further identified egocentric neurons representing landmarks in a virtual navigation task or remembered cue location in a goal-oriented task, respectively. These neurons formed an independent population with egocentric boundary cells, suggesting that dedicated neurons with microscopic clustering of functional inputs shaped egocentric boundary processing in RSC and that RSC adopted a labeled line code with distinct classes of egocentric neurons responsible for representing different items in specific behavioral contexts, which could lead to efficient and flexible computation.

Approaches and considerations of studying neuronal ensembles: a brief review

First theorized by Hebb, neuronal ensembles have provided a framework for understanding how the mammalian brain operates, especially regarding learning and memory. Neuronal ensembles are discrete, sparsely distributed groups of neurons that become activated in response to a specific stimulus and are thought to provide an internal representation of the world. Beyond the study of region-wide or projection-wide activation, the study of ensembles offers increased specificity and resolution to identify and target specific memories or associations. Neuroscientists interested in the neurobiology of learning, memory, and motivated behavior have used electrophysiological-, calcium-, and protein-based proxies of neuronal activity in preclinical models to better understand the neurobiology of learned and motivated behaviors. Although these three approaches may be used to pursue the same general goal of studying neuronal ensembles, technical differences lead to inconsistencies in the output and interpretation of data. This mini-review highlights some of the methodologies used in electrophysiological-, calcium-, and protein-based studies of neuronal ensembles and discusses their strengths and weaknesses.