Medial Prefrontal Cortex Reduces Memory Interference by Modifying Hippocampal Encoding

New information triggers prospective codes to adapt for flexible navigation

Navigating a dynamic world requires rapidly updating choices by integrating past experiences with new information. In hippocampus and prefrontal cortex, neural activity representing future goals is theorized to support navigational planning. However, it remains unknown how prospective goal representations incorporate new, pivotal information. Accordingly, we designed a navigation task that precisely introduces new information using virtual reality, and we recorded neural activity as male mice flexibly adapted their planned destinations. Here we show that new information triggered increased hippocampal prospective representations of both possible goals; while in prefrontal cortex, new information caused prospective representations of choices to rapidly shift to the new choice. When mice did not adapt, prefrontal choice codes failed to switch. Prospective codes were dependent on the amount of behavioral adaptation needed; the new goal arm was represented more strongly when animals needed to change their behavior more. Thus, we show how prospective codes update with new information to flexibly adapt ongoing navigational plans.

Suppression of mPFC-Amygdala Circuit Mitigates Sevoflurane-Induced Cognitive Deficits in Aged Mice

BACKGROUND

Perioperative neurocognitive disorders (PND) are common and costly complications in elderly surgical patients, yet the involvement of specific neural circuits in their etiology remains poorly understood. We hypothesized that neural projections from the medial prefrontal cortex (mPFC) to the amygdala contribute to PND pathogenesis.

METHODS

Using chemogenetic approaches, we selectively suppressed or excited the mPFC and its projections to the amygdala in a murine model exposed to sevoflurane. We assessed cognitive deficits, synaptic plasticity (AMPA receptor activity, long-term potentiation [LTP]), mitochondrial stress, neuroinflammatory markers, and neuronal apoptosis in the amygdala. Additional interventions included pharmacological suppression of AMPA receptors, glutamate biosynthesis, and mitochondrial stress within the amygdala.

RESULTS

Sevoflurane exposure activated the mPFC-amygdala circuit. Chemogenetic suppression of the mPFC attenuated sevoflurane-induced cognitive deficits, AMPA receptor hyperexcitation, mitochondrial dysfunction, neuroinflammation, and neuronal apoptosis in the amygdala. Retrograde inhibition of mPFC projections to the amygdala alleviated cognitive impairments, whereas retrograde excitation exacerbated them. Suppressing AMPA receptors, glutamate synthesis, or mitochondrial stress in the amygdala similarly reduced cognitive deficits and pathological alterations. Notably, mPFC suppression rescued sevoflurane-induced LTP impairment in the amygdala.

CONCLUSIONS

These findings demonstrate that sevoflurane activates the mPFC-amygdala circuit, driving PND-associated cognitive deficits and neuropathological changes. Targeting this circuit or downstream mechanisms (AMPA signaling, mitochondrial stress) may mitigate sevoflurane-induced PND. This study provides empirical evidence implicating specific neural circuitry in anesthetic-related neurocognitive dysfunction.

Hippocampal output suppresses orbitofrontal cortex schema cell formation

Both the orbitofrontal cortex (OFC) and the hippocampus (HC) are implicated in the formation of cognitive maps and their generalization into schemas. However, how these areas interact in supporting this function remains unclear, with some proposals supporting a serial model in which the OFC draws on task representations created by the HC to extract key behavioral features and others suggesting a parallel model in which both regions construct representations that highlight different types of information. In the present study, we tested between these two models by asking how schema correlates in rat OFC would be affected by inactivating the output of the HC, after learning and during transfer across problems. We found that the prevalence and content of schema correlates were unaffected by inactivating one major HC output area, the ventral subiculum, after learning, whereas inactivation during transfer accelerated their formation. These results favor the proposal that the OFC and HC operate in parallel to extract different features defining cognitive maps and schemas.

Schemas, reinforcement learning and the medial prefrontal cortex

Schemas are rich and complex knowledge structures about the typical unfolding of events in a context; for example, a schema of a dinner at a restaurant. In this Perspective, we suggest that reinforcement learning (RL), a computational theory of learning the structure of the world and relevant goal-oriented behaviour, underlies schema learning. We synthesize literature about schemas and RL to offer that three RL principles might govern the learning of schemas: learning via prediction errors, constructing hierarchical knowledge using hierarchical RL, and dimensionality reduction through learning a simplified and abstract representation of the world. We then suggest that the orbitomedial prefrontal cortex is involved in both schemas and RL due to its involvement in dimensionality reduction and in guiding memory reactivation through interactions with posterior brain regions. Last, we hypothesize that the amount of dimensionality reduction might underlie gradients of involvement along the ventral-dorsal and posterior-anterior axes of the orbitomedial prefrontal cortex. More specific and detailed representations might engage the ventral and posterior parts, whereas abstraction might shift representations towards the dorsal and anterior parts of the medial prefrontal cortex.

Ventral tegmental area dopamine neural activity switches simultaneously with rule representations in the prefrontal cortex and hippocampus

Multiple brain regions need to coordinate activity to support cognitive flexibility and behavioral adaptation. Neural activity in both the hippocampus (HPC) and prefrontal cortex (PFC) is known to represent spatial context and is sensitive to reward and rule alterations. Midbrain dopamine (DA) activity is key in reward seeking behavior and learning. There is abundant evidence that midbrain DA modulates HPC and PFC activity. However, it remains underexplored how these networks engage dynamically and coordinate temporally when animals must adjust their behavior according to changing reward contingencies. In particular, is there any relationship between DA reward prediction change during rule switching, and rule representation changes in PFC and CA1? We addressed these questions using simultaneous recording of neuronal population activity from the hippocampal area CA1, PFC and ventral tegmental area (VTA) in male TH-Cre rats performing two spatial working memory tasks with frequent rule switches in blocks of trials. CA1 and PFC ensembles showed rule-specific activity both during maze running and at reward locations, with PFC rule coding more consistent across animals compared to CA1. Optogenetically tagged VTA DA neuron firing activity responded to and predicted reward outcome. We found that the correct prediction in DA emerged gradually over trials after rule-switching in coordination with transitions in PFC and CA1 ensemble representations of the current rule after a rule switch, followed by behavioral adaptation to the correct rule sequence. Therefore, our study demonstrates a crucial temporal coordination between the rule representation in PFC/CA1, the dopamine reward signal and behavioral strategy.

Cost-benefit tradeoff mediates the transition from rule-based to memory-based processing during practice

Practice not only improves task performance but also changes task execution from rule- to memory-based processing by incorporating experiences from practice. However, how and when this change occurs is unclear. We test the hypothesis that strategy transitions in task learning can result from decision-making guided by cost-benefit analysis. Participants learn 2 task sequences and are then queried about the task type at a cued sequence and position. Behavioral improvement with practice can be accounted for by a computational model implementing cost-benefit analysis and the model-predicted strategy transition points align with the observed behavioral slowing. Model comparisons using behavioral data show that strategy transitions are better explained by a cost-benefit analysis across alternative strategies rather than solely on memory strength. Model-guided fMRI findings suggest that the brain encodes a decision variable reflecting the cost-benefit analysis and that different strategy representations are double-dissociated. Further analyses reveal that strategy transitions are associated with activation patterns in the dorsolateral prefrontal cortex and increased pattern separation in the ventromedial prefrontal cortex. Together, these findings support cost-benefit analysis as a mechanism of practice-induced strategy shift.

Environmental complexity modulates information processing and the balance between decision-making systems

Behavior in naturalistic scenarios occurs in diverse environments. Adaptive strategies rely on multiple neural circuits and competing decision systems. However, past studies of rodent decision making have largely measured behavior in simple environments. To fill this gap, we recorded neural ensembles from hippocampus (HC), dorsolateral striatum (DLS), and dorsomedial prefrontal cortex (dmPFC) while rats foraged for food under changing rules in environments with varying topological complexity. Environmental complexity increased behavioral variability, lengthened HC nonlocal sequences, and modulated action caching. We found contrasting representations between DLS and HC, supporting a competition between decision systems. dmPFC activity was indicative of setting this balance, in particular predicting the extent of HC non-local coding. Inactivating mPFC impaired short-term behavioral adaptation and produced long-term deficits in balancing decision systems. Our findings reveal the dynamic nature of decision-making systems and how environmental complexity modulates their engagement with implications for behavior in naturalistic environments.

The Ubiquity of Time in Latent-cause Inference

Humans have an outstanding ability to generalize from past experiences, which requires parsing continuously experienced events into discrete, coherent units, and relating them to similar past experiences. Time is a key element in this process; however, how temporal information is used in generalization remains unclear. Latent-cause inference provides a Bayesian framework for clustering experiences, by building a world model in which related experiences are generated by a shared cause. Here, we examine how temporal information is used in latent-cause inference, using a novel task in which participants see "microbe" stimuli and explicitly report the latent cause ("strain") they infer for each microbe. We show that humans incorporate time in their inference of latent causes, such that recently inferred latent causes are more likely to be inferred again. In particular, a "persistent" model, in which the latent cause inferred for one observation has a fixed probability of continuing to cause the next observation, explains the data significantly better than two other time-sensitive models, although extensive individual differences exist. We show that our task and this model have good psychometric properties, highlighting their potential use for quantifying individual differences in computational psychiatry or in neuroimaging studies.

Cost-benefit Tradeoff Mediates the Rule- to Memory-based Processing Transition during Practice

Practice not only improves task performance but also changes task execution from rule- to memory-based processing by incorporating experiences from practice. However, how and when this change occurs is unclear. We test the hypothesis that strategy transitions in task learning can result from decision-making guided by cost-benefit analysis. Participants learn two task sequences and are then queried about the task type at a cued sequence and position. Behavioral improvement with practice can be accounted for by a computational model implementing cost-benefit analysis, and the model-predicted strategy transition points align with the observed behavioral slowing. Model comparisons using behavioral data show that strategy transitions are better explained by a cost-benefit analysis across alternative strategies rather than solely on memory strength. Model-guided fMRI findings suggest that the brain encodes a decision variable reflecting the cost-benefit analysis and that different strategy representations are double-dissociated. Further analyses reveal that strategy transitions are associated with activation patterns in the dorsolateral prefrontal cortex and increased pattern separation in the ventromedial prefrontal cortex. Together, these findings support cost-benefit analysis as a mechanism of practice-induced strategy shift.

From nasal respiration to brain dynamic

While breathing is a vital, involuntary physiological function, the mode of respiration, particularly nasal breathing, exerts a profound influence on brain activity and cognitive processes. This review synthesizes existing research on the interactions between nasal respiration and the entrainment of oscillations across brain regions involved in cognition. The rhythmic activation of olfactory sensory neurons during nasal respiration is linked to oscillations in widespread brain regions, including the prefrontal cortex, entorhinal cortex, hippocampus, amygdala, and parietal cortex, as well as the piriform cortex. The phase-locking of neural oscillations to the respiratory cycle, through nasal breathing, enhances brain inter-regional communication and is associated with cognitive abilities like memory. Understanding the nasal breathing impact on brain networks offers opportunities to explore novel methods for targeting the olfactory pathway as a means to enhance emotional and cognitive functions.

Memory's gatekeeper: The role of PFC in the encoding of congruent events

Theoretical models conventionally portray the consolidation of memories as a slow process that unfolds during sleep. According to the classical Complementary Learning Systems theory, the hippocampus (HPC) rapidly changes its connectivity during wakefulness to encode ongoing events and create memory ensembles that are later transferred to the prefrontal cortex (PFC) during sleep. However, recent experimental studies challenge this notion by showing that new information consistent with prior knowledge can be rapidly consolidated in PFC during wakefulness and that PFC lesions disrupt the encoding of congruent events in the HPC. The contributions of the PFC to memory encoding have therefore largely been overlooked. Moreover, most theoretical frameworks assume random and uncorrelated patterns representing memories, disregarding the correlations between our experiences. To address these shortcomings, we developed a HPC-PFC network model that simulates interactions between the HPC and PFC during the encoding of a memory (awake stage), and subsequent consolidation (sleeping stage) to examine the contributions of each region to the consolidation of novel and congruent memories. Our results show that the PFC network uses stored memory "schemas" consolidated during previous experiences to identify inputs that evoke congruent patterns of activity, quickly integrate it into its network, and gate which components are encoded in the HPC. More specifically, the PFC uses GABAergic long-range projections to inhibit HPC neurons representing input components correlated with a previously stored memory "schema," eliciting sparse hippocampal activity during exposure to congruent events, as it has been experimentally observed.

Using synchronized brain rhythms to bias memory-guided decisions

Functional interactions between the prefrontal cortex and hippocampus, as revealed by strong oscillatory synchronization in the theta (6-11 Hz) frequency range, correlate with memory-guided decision-making. However, the degree to which this form of long-range synchronization influences memory-guided choice remains unclear. We developed a brain-machine interface that initiated task trials based on the magnitude of prefrontal-hippocampal theta synchronization, then measured choice outcomes. Trials initiated based on strong prefrontal-hippocampal theta synchrony were more likely to be correct compared to control trials on both working memory-dependent and -independent tasks. Prefrontal-thalamic neural interactions increased with prefrontal-hippocampal synchrony and optogenetic activation of the ventral midline thalamus primarily entrained prefrontal theta rhythms, but dynamically modulated synchrony. Together, our results show that prefrontal-hippocampal theta synchronization leads to a higher probability of a correct choice and strengthens prefrontal-thalamic dialogue. Our findings reveal new insights into the neural circuit dynamics underlying memory-guided choices and highlight a promising technique to potentiate cognitive processes or behavior via brain-machine interfacing.

Flexible decision-making is related to strategy learning, vicarious trial and error, and medial prefrontal rhythms during spatial set-shifting

Flexible decision-making requires a balance between exploring features of an environment and exploiting prior knowledge. Behavioral flexibility is typically measured by how long it takes subjects to consistently make accurate choices after reward contingencies switch or task rules change. This measure, however, only allows for tracking flexibility across multiple trials, and does not assess the degree of flexibility. Plus, although increases in decision-making accuracy are strong indicators of learning, other decision-making behaviors have also been suggested as markers of flexibility, such as the on-the-fly decision reversals known as vicarious trial and error (VTE) or switches to a different, but incorrect, strategy. We sought to relate flexibility, learning, and neural activity by comparing choice history-derived evaluation of strategy use with changes in decision-making accuracy and VTE behavior while recording from the medial prefrontal cortex (mPFC) in rats. Using a set-shifting task that required rats to repeatedly switch between spatial decision-making strategies, we show that a previously developed strategy likelihood estimation procedure could identify putative learning points based on decision history. We confirm the efficacy of learning point estimation by showing increases in decision-making accuracy aligned to the learning point. Additionally, we show increases in the rate of VTE behavior surrounding identified learning points. By calculating changes in strategy likelihoods across trials, we tracked flexibility on a trial-by-trial basis and show that flexibility scores also increased around learning points. Further, we demonstrate that VTE behaviors could be separated into indecisive and deliberative subtypes depending on whether they occurred during periods of high or low flexibility and whether they led to correct or incorrect choice outcomes. Field potential recordings from the mPFC during decisions exhibited increased beta band activity on trials with VTE compared to non-VTE trials, as well as increased gamma during periods when learned strategies could be exploited compared to prelearning, exploratory periods. This study demonstrates that increased behavioral flexibility and VTE rates are often aligned to task learning. These relationships can break down, however, suggesting that VTE is not always an indicator of deliberative decision-making. Additionally, we further implicate the mPFC in decision-making and learning by showing increased beta-based activity on VTE trials and increased gamma after learning.

Stochastic characterization of navigation strategies in an automated variant of the Barnes maze

Animals can use a repertoire of strategies to navigate in an environment, and it remains an intriguing question how these strategies are selected based on the nature and familiarity of environments. To investigate this question, we developed a fully automated variant of the Barnes maze, characterized by 24 vestibules distributed along the periphery of a circular arena, and monitored the trajectories of mice over 15 days as they learned to navigate towards a goal vestibule from a random start vestibule. We show that the patterns of vestibule visits can be reproduced by the combination of three stochastic processes reminiscent of random, serial, and spatial strategies. The processes randomly selected vestibules based on either uniform (random) or biased (serial and spatial) probability distributions. They closely matched experimental data across a range of statistical distributions characterizing the length, distribution, step size, direction, and stereotypy of vestibule sequences, revealing a shift from random to spatial and serial strategies over time, with a strategy switch occurring approximately every six vestibule visits. Our study provides a novel apparatus and analysis toolset for tracking the repertoire of navigation strategies and demonstrates that a set of stochastic processes can largely account for exploration patterns in the Barnes maze.

Border cells without theta rhythmicity in the medial prefrontal cortex

The medial prefrontal cortex (mPFC) is a key brain structure for higher cognitive functions such as decision-making and goal-directed behavior, many of which require awareness of spatial variables including one's current position within the surrounding environment. Although previous studies have reported spatially tuned activities in mPFC during memory-related trajectory, the spatial tuning of mPFC network during freely foraging behavior remains elusive. Here, we reveal geometric border or border-proximal representations from the neural activity of mPFC ensembles during naturally exploring behavior, with both allocentric and egocentric boundary responses. Unlike most of classical border cells in the medial entorhinal cortex (MEC) discharging along a single wall, a large majority of border cells in mPFC fire particularly along four walls. mPFC border cells generate new firing fields to external insert, and remain stable under darkness, across distinct shapes, and in novel environments. In contrast to hippocampal theta entrainment during spatial working memory tasks, mPFC border cells rarely exhibited theta rhythmicity during spontaneous locomotion behavior. These findings reveal spatially modulated activity in mPFC, supporting local computation for cognitive functions involving spatial context and contributing to a broad spatial tuning property of cortical circuits.

Transient demyelination causes long-term cognitive impairment, myelin alteration and network synchrony defects

In the adult brain, activity-dependent myelin plasticity is required for proper learning and memory consolidation. Myelin loss, alteration, or even subtle structural modifications can therefore compromise the network activity, leading to functional impairment. In multiple sclerosis, spontaneous myelin repair process is possible, but it is heterogeneous among patients, sometimes leading to functional recovery, often more visible at the motor level than at the cognitive level. In cuprizone-treated mouse model, massive brain demyelination is followed by spontaneous and robust remyelination. However, reformed myelin, although functional, may not exhibit the same morphological characteristics as developmental myelin, which can have an impact on the activity of neural networks. In this context, we used the cuprizone-treated mouse model to analyze the structural, functional, and cognitive long-term effects of transient demyelination. Our results show that an episode of demyelination induces despite remyelination long-term cognitive impairment, such as deficits in spatial working memory, social memory, cognitive flexibility, and hyperactivity. These deficits were associated with a reduction in myelin content in the medial prefrontal cortex (mPFC) and hippocampus (HPC), as well as structural myelin modifications, suggesting that the remyelination process may be imperfect in these structures. In vivo electrophysiological recordings showed that the demyelination episode altered the synchronization of HPC-mPFC activity, which is crucial for memory processes. Altogether, our data indicate that the myelin repair process following transient demyelination does not allow the complete recovery of the initial myelin properties in cortical structures. These subtle modifications alter network features, leading to prolonged cognitive deficits in mice.

Beyond hippocampus: Thalamic and prefrontal contributions to an evolving memory

The hippocampus has long been at the center of memory research, and rightfully so. However, with emerging technological capabilities, we can increasingly appreciate memory as a more dynamic and brain-wide process. In this perspective, our goal is to begin developing models to understand the gradual evolution, reorganization, and stabilization of memories across the brain after their initial formation in the hippocampus. By synthesizing studies across the rodent and human literature, we suggest that as memory representations initially form in hippocampus, parallel traces emerge in frontal cortex that cue memory recall, and as they mature, with sustained support initially from limbic then diencephalic then cortical circuits, they become progressively independent of hippocampus and dependent on a mature cortical representation. A key feature of this model is that, as time progresses, memory representations are passed on to distinct circuits with progressively longer time constants, providing the opportunity to filter, forget, update, or reorganize memories in the process of committing to long-term storage.

Mystery of the memory engram: History, current knowledge, and unanswered questions

The quest to understand the memory engram has intrigued humans for centuries. Recent technological advances, including genetic labelling, imaging, optogenetic and chemogenetic techniques, have propelled the field of memory research forward. These tools have enabled researchers to create and erase memory components. While these innovative techniques have yielded invaluable insights, they often focus on specific elements of the memory trace. Genetic labelling may rely on a particular immediate early gene as a marker of activity, optogenetics may activate or inhibit one specific type of neuron, and imaging may capture activity snapshots in a given brain region at specific times. Yet, memories are multifaceted, involving diverse arrays of neuronal subpopulations, circuits, and regions that work in concert to create, store, and retrieve information. Consideration of contributions of both excitatory and inhibitory neurons, micro and macro circuits across brain regions, the dynamic nature of active ensembles, and representational drift is crucial for a comprehensive understanding of the complex nature of memory.

Tracking subjects' strategies in behavioural choice experiments at trial resolution

Investigating how, when, and what subjects learn during decision-making tasks requires tracking their choice strategies on a trial-by-trial basis. Here, we present a simple but effective probabilistic approach to tracking choice strategies at trial resolution using Bayesian evidence accumulation. We show this approach identifies both successful learning and the exploratory strategies used in decision tasks performed by humans, non-human primates, rats, and synthetic agents. Both when subjects learn and when rules change the exploratory strategies of win-stay and lose-shift, often considered complementary, are consistently used independently. Indeed, we find the use of lose-shift is strong evidence that subjects have latently learnt the salient features of a new rewarded rule. Our approach can be extended to any discrete choice strategy, and its low computational cost is ideally suited for real-time analysis and closed-loop control.

The medial prefrontal cortex during flexible decisions: Evidence for its role in distinct working memory processes

During decisions that involve working memory, task-related information must be encoded, maintained across delays, and retrieved. Few studies have attempted to causally disambiguate how different brain structures contribute to each of these components of working memory. In the present study, we used transient optogenetic disruptions of rat medial prefrontal cortex (mPFC) during a serial spatial reversal learning (SSRL) task to test its role in these specific working memory processes. By analyzing numerous performance metrics, we found: (1) mPFC disruption impaired performance during only the choice epoch of initial discrimination learning of the SSRL task; (2) mPFC disruption impaired performance in dissociable ways across all task epochs (delay, choice, return) during flexible decision-making; (3) mPFC disruption resulted in a reduction of the typical vicarious-trial-and-error rate modulation that was related to changes in task demands. Taken together, these findings suggest that the mPFC plays an outsized role in working memory retrieval, becomes involved in encoding and maintenance when recent memories conflict with task demands, and enables animals to flexibly utilize working memory to update behavior as environments change.

Using synchronized brain rhythms to bias memory-guided decisions

Functional interactions between the prefrontal cortex and hippocampus, as revealed by strong oscillatory synchronization in the theta (6-11 Hz) frequency range, correlate with memory-guided decision-making. However, the degree to which this form of long-range synchronization influences memory-guided choice remains unclear. We developed a brain machine interface that initiated task trials based on the magnitude of prefrontal hippocampal theta synchronization, then measured choice outcomes. Trials initiated based on strong prefrontal-hippocampal theta synchrony were more likely to be correct compared to control trials on both working memory-dependent and -independent tasks. Prefrontal-thalamic neural interactions increased with prefrontal-hippocampal synchrony and optogenetic activation of the ventral midline thalamus primarily entrained prefrontal theta rhythms, but dynamically modulated synchrony. Together, our results show that prefrontal-hippocampal theta synchronization leads to a higher probability of a correct choice and strengthens prefrontal-thalamic dialogue. Our findings reveal new insights into the neural circuit dynamics underlying memory-guided choices and highlight a promising technique to potentiate cognitive processes or behavior via brain machine interfacing.

A neural network model of hippocampal contributions to category learning

In addition to its critical role in encoding individual episodes, the hippocampus is capable of extracting regularities across experiences. This ability is central to category learning, and a growing literature indicates that the hippocampus indeed makes important contributions to this form of learning. Using a neural network model that mirrors the anatomy of the hippocampus, we investigated the mechanisms by which the hippocampus may support novel category learning. We simulated three category learning paradigms and evaluated the network's ability to categorize and recognize specific exemplars in each. We found that the trisynaptic pathway within the hippocampus-connecting entorhinal cortex to dentate gyrus, CA3, and CA1-was critical for remembering exemplar-specific information, reflecting the rapid binding and pattern separation capabilities of this circuit. The monosynaptic pathway from entorhinal cortex to CA1, in contrast, specialized in detecting the regularities that define category structure across exemplars, supported by the use of distributed representations and a relatively slower learning rate. Together, the simulations provide an account of how the hippocampus and its constituent pathways support novel category learning.

New information triggers prospective codes to adapt for flexible navigation

Navigating a dynamic world requires rapidly updating choices by integrating past experiences with new information. In hippocampus and prefrontal cortex, neural activity representing future goals is theorized to support planning. However, it remains unknown how prospective goal representations incorporate new, pivotal information. Accordingly, we designed a novel task that precisely introduces new information using virtual reality, and we recorded neural activity as mice flexibly adapted their planned destinations. We found that new information triggered increased hippocampal prospective representations of both possible goals; while in prefrontal cortex, new information caused prospective representations of choices to rapidly shift to the new choice. When mice did not flexibly adapt, prefrontal choice codes failed to switch, despite relatively intact hippocampal goal representations. Prospective code updating depended on the commitment to the initial choice and degree of adaptation needed. Thus, we show how prospective codes update with new information to flexibly adapt ongoing navigational plans.

Hippocampal and medial prefrontal ensemble spiking represents episodes and rules in similar task spaces

Episodic memory requires the hippocampus and prefrontal cortex to guide decisions by representing events in spatial, temporal, and personal contexts. Both brain regions have been described by cognitive theories that represent events in context as locations in maps or memory spaces. We query whether ensemble spiking in these regions described spatial structures as rats performed memory tasks. From each ensemble, we construct a state-space with each point defined by the coordinated spiking of single and pairs of units in 125-ms bins and investigate how state-space locations discriminate task features. Trajectories through state-spaces correspond with behavioral episodes framed by spatial, temporal, and internal contexts. Both hippocampal and prefrontal ensembles distinguish maze locations, task intervals, and goals by distances between state-space locations, consistent with cognitive mapping and relational memory space theories of episodic memory. Prefrontal modulation of hippocampal activity may guide choices by directing memory representations toward appropriate state-space goal locations.

Verbal memory and executive components of recall in adolescent binge drinkers

Introduction

Binge drinking (BD) is a common health-risk behavior among young people. Due to the incomplete maturation of the adolescent brain, BD can lead to structural and functional changes that impact neurocognitive processes, particularly executive functioning and verbal memory. This study aimed to investigate the influence of executive components, such as mnemonic strategies and error avoidance, on performance in a verbal memory test and the potential effects of BD on this performance.

Methods

A sample of 160 college students (51.55% female) with a mean age of 18.12 ± 0.32 years completed assessments for alcohol use disorders using the Alcohol Use Disorder Identification Test (AUDIT), as well as psychopathological (Symptom Checklist-90-R) and neuropsychological evaluations (Verbal Learning Test Spain-Complutense and WMS-III Logical Memory). The Intensive Drinking Evaluation Instrument (IECI) was utilized to gather detailed information about binge drinking habits, including the calculation of the highest blood alcohol concentration (BAC) during an episode of intake.

Results

Correlation and clustering analyses revealed a negative association between BAC values and verbal memory performance, as well as the use of memory strategies. The high BAC group (BD) exhibited negative values in verbal memory variables, higher accuracy errors, and less efficient strategy usage, while the low BAC group (No BD) demonstrated better memory test performance, fewer precision errors, and superior use of memory strategies.

Discussion

These findings support the hypothesis that, when solving tests requiring verbal memory, adolescents reporting a BD consumption pattern show fewer executive skills in their resolution and, therefore, achieved poorer performance than non-binge drinkers. Addressing excessive alcohol consumption in young individuals is crucial for safeguarding their cognitive development and overall well-being.

Theta oscillations as a substrate for medial prefrontal-hippocampal assembly interactions

The execution of cognitive functions requires coordinated circuit activity across different brain areas that involves the associated firing of neuronal assemblies. Here, we tested the circuit mechanism behind assembly interactions between the hippocampus and the medial prefrontal cortex (mPFC) of adult rats by recording neuronal populations during a rule-switching task. We identified functionally coupled CA1-mPFC cells that synchronized their activity beyond that expected from common spatial coding or oscillatory firing. When such cell pairs fired together, the mPFC cell strongly phase locked to CA1 theta oscillations and maintained consistent theta firing phases, independent of the theta timing of their CA1 counterpart. These functionally connected CA1-mPFC cells formed interconnected assemblies. While firing together with their CA1 assembly partners, mPFC cells fired along specific theta sequences. Our results suggest that upregulated theta oscillatory firing of mPFC cells can signal transient interactions with specific CA1 assemblies, thus enabling distributed computations.

Sharp-wave-ripple-associated activity in the medial prefrontal cortex supports spatial rule switching

Previous studies have highlighted an important role for hippocampal sharp-wave ripples in spatial alternation learning, as well as in modulating activity in the medial prefrontal cortex (mPFC). However, the direct influence of hippocampal sharp-wave ripples on mPFC activity during spatial alternation learning has not been investigated. Here, we train Long Evans rats on a three-arm radial maze to perform a sequence of alternations. Three alternation sequences needed to be learned, and while learning a sequence, the activity in the mPFC was inhibited either directly following sharp-wave ripples in the hippocampus (on-time condition) or with a randomized delay (delayed condition). In the on-time condition, the behavioral performance is significantly worse compared to the same animals in the delayed inhibition condition, as measured by a lower correct alternation performance and more perseverative behavior. This indicates that the activity in the mPFC directly following hippocampal sharp-wave ripples is necessary for spatial rule switching.

Functional network of contextual and temporal memory has increased amygdala centrality and connectivity with the retrosplenial cortex, thalamus, and hippocampus

In fear conditioning with time intervals between the conditioned (CS) and unconditioned (US) stimuli, a neural representation of the CS must be maintained over time to be associated with the later US. Usually, temporal associations are studied by investigating individual brain regions. It remains unknown, however, the effect of the interval at the network level, uncovering functional connections cooperating for the CS transient memory and its fear association. We investigated the functional network supporting temporal associations using a task in which a 5-s interval separates the contextual CS from the US (CFC-5s). We quantified c-Fos expression in forty-nine brain regions of male rats following the CFC-5s training, used c-Fos correlations to generate functional networks, and analyzed them by graph theory. Control groups were trained in contextual fear conditioning, in which CS and US overlap. The CFC-5s training additionally activated subdivisions of the basolateral, lateral, and medial amygdala; prelimbic, infralimbic, perirhinal, postrhinal, and intermediate entorhinal cortices; ventral CA1 and subiculum. The CFC-5s network had increased amygdala centrality and higher amygdala internal and external connectivity with the retrosplenial cortex, thalamus, and hippocampus. Amygdala and thalamic nuclei were network hubs. Functional connectivity among these brain regions could support CS transient memories and their association.

Subspace partitioning in the human prefrontal cortex resolves cognitive interference

The human prefrontal cortex (PFC) constitutes the structural basis underlying flexible cognitive control, where mixed-selective neural populations encode multiple task features to guide subsequent behavior. The mechanisms by which the brain simultaneously encodes multiple task-relevant variables while minimizing interference from task-irrelevant features remain unknown. Leveraging intracranial recordings from the human PFC, we first demonstrate that competition between coexisting representations of past and present task variables incurs a behavioral switch cost. Our results reveal that this interference between past and present states in the PFC is resolved through coding partitioning into distinct low-dimensional neural states; thereby strongly attenuating behavioral switch costs. In sum, these findings uncover a fundamental coding mechanism that constitutes a central building block of flexible cognitive control.

Hippocampal and Medial Prefrontal Cortex Fractal Spiking Patterns Encode Episodes and Rules

A central question in neuroscience is how the brain represents and processes information to guide behavior. The principles that organize brain computations are not fully known, and could include scale-free, or fractal patterns of neuronal activity. Scale-free brain activity may be a natural consequence of the relatively small subsets of neuronal populations that respond to task features, i.e., sparse coding. The size of the active subsets constrains the possible sequences of inter-spike intervals (ISI), and selecting from this limited set may produce firing patterns across wide-ranging timescales that form fractal spiking patterns. To investigate the extent to which fractal spiking patterns corresponded with task features, we analyzed ISIs in simultaneously recorded populations of CA1 and medial prefrontal cortical (mPFC) neurons in rats performing a spatial memory task that required both structures. CA1 and mPFC ISI sequences formed fractal patterns that predicted memory performance. CA1 pattern duration, but not length or content, varied with learning speed and memory performance whereas mPFC patterns did not. The most common CA1 and mPFC patterns corresponded with each region's cognitive function: CA1 patterns encoded behavioral episodes which linked the start, choice, and goal of paths through the maze whereas mPFC patterns encoded behavioral "rules" which guided goal selection. mPFC patterns predicted changing CA1 spike patterns only as animals learned new rules. Together, the results suggest that CA1 and mPFC population activity may predict choice outcomes by using fractal ISI patterns to compute task features.

Goal Choices Modify Frontotemporal Memory Representations

Adapting flexibly to changing circumstances is guided by memory of past choices, their outcomes in similar circumstances, and a method for choosing among potential actions. The hippocampus (HPC) is needed to remember episodes, and the prefrontal cortex (PFC) helps guide memory retrieval. Single-unit activity in the HPC and PFC correlates with such cognitive functions. Previous work recorded CA1 and mPFC activity as male rats performed a spatial reversal task in a plus maze that requires both structures, found that PFC activity helps reactivate HPC representations of pending goal choices but did not describe frontotemporal interactions after choices. We describe these interactions after choices here. CA1 activity tracked both current goal location and the past starting location of single trials; PFC activity tracked current goal location better than past start location. CA1 and PFC reciprocally modulated representations of each other both before and after goal choices. After choices, CA1 activity predicted changes in PFC activity in subsequent trials, and the magnitude of this prediction correlated with faster learning. In contrast, PFC start arm activity more strongly modulated CA1 activity after choices correlated with slower learning. Together, the results suggest post-choice HPC activity conveys retrospective signals to the PFC, which combines different paths to common goals into rules. In subsequent trials, prechoice mPFC activity modulates prospective CA1 signals informing goal selection.SIGNIFICANCE STATEMENT HPC and PFC activity supports cognitive flexibility in changing circumstances. HPC signals represent behavioral episodes that link the start, choice, and goal of paths. PFC signals represent rules that guide goal-directed actions. Although prior studies described HPC-PFC interactions preceding decisions in the plus maze, post-decision interactions were not investigated. Here, we show post-choice HPC and PFC activity distinguished the start and goal of paths, and CA1 signaled the past start of each trial more accurately than mPFC. Postchoice CA1 activity modulated subsequent PFC activity, so rewarded actions were more likely to occur. Together, the results show that in changing circumstances, HPC retrospective codes modulate subsequent PFC coding, which in turn modulates HPC prospective codes that predict choices.

Altered default mode network causal connectivity patterns in autism spectrum disorder revealed by Liang information flow analysis

Autism spectrum disorder (ASD) is a pervasive developmental disorder with severe cognitive impairment in social communication and interaction. Previous studies have reported that abnormal functional connectivity patterns within the default mode network (DMN) were associated with social dysfunction in ASD. However, how the altered causal connectivity pattern within the DMN affects the social functioning in ASD remains largely unclear. Here, we introduced the Liang information flow method, widely applied to climate science and quantum mechanics, to uncover the brain causal network patterns in ASD. Compared with the healthy controls (HC), we observed that the interactions among the dorsal medial prefrontal cortex (dMPFC), ventral medial prefrontal cortex (vMPFC), hippocampal formation, and temporo-parietal junction showed more inter-regional causal connectivity differences in ASD. For the topological property analysis, we also found the clustering coefficient of DMN and the In-Out degree of anterior medial prefrontal cortex were significantly decreased in ASD. Furthermore, we found that the causal connectivity from dMPFC to vMPFC was correlated with the clinical symptoms of ASD. These altered causal connectivity patterns indicated that the DMN inter-regions information processing was perturbed in ASD. In particular, we found that the dMPFC acts as a causal source in the DMN in HC, whereas it plays a causal target in ASD. Overall, our findings indicated that the Liang information flow method could serve as an important way to explore the DMN causal connectivity patterns, and it also can provide novel insights into the nueromechanisms underlying DMN dysfunction in ASD.

Optogenetic disruption of the prelimbic cortex alters long-term decision strategy but not valuation on a spatial delay discounting task

Rats demonstrate a preference for smaller, immediate rewards over larger, delayed ones, a phenomenon known as delay-discounting (DD). Behavior arises from the interaction of multiple decision-making systems, and the medial prefrontal cortex (mPFC) has been identified as a central component in the mediation between these decision systems. To investigate the role of the prelimbic (PL) subregion of mPFC on decision strategy interaction, we compared two cohorts of rats (ChR2-opsin-expressing 'Active' and opsin-absent 'Control') on a spatial delay-discounting task while delivering in-vivo light stimulation into PL at the choice point of select trials. By analyzing the overall delay-adjustment along with deliberative and procedural behavioral strategy markers, our study revealed differences in the decision strategies used between the active and control animals despite both groups showing similar valuations. Control animals developed the expected shift from deliberative to procedural decision strategy on this task (indicated by reaching delay-stability, particularly during late-session laps); however, active-virus animals repeatedly over-adjusted around their preferred delay throughout the entire session, suggesting a significant deficit in procedural decision-making on this task. Active animals showed a significant decrease in proportion of vicarious trial and error events (VTE, a behavior correlated with deliberative processes) on delay adjustment laps relative to control animals. This points to a more nuanced role for VTE, not just in executing deliberation, but in shifting from deliberative to procedural processes. This opto-induced change in VTE was especially pronounced for late-session adjustment laps. We found no other session-by-session or lap-by-lap effects, leaving a particular role for PL in the long-term development of procedural strategies on this task.

Temporal context and latent state inference in the hippocampal splitter signal

The hippocampus is thought to enable the encoding and retrieval of ongoing experience, the organization of that experience into structured representations like contexts, maps, and schemas, and the use of these structures to plan for the future. A central goal is to understand what the core computations supporting these functions are, and how these computations are realized in the collective action of single neurons. A potential access point into this issue is provided by 'splitter cells', hippocampal neurons that fire differentially on the overlapping segment of trajectories that differ in their past and/or future. However, the literature on splitter cells has been fragmented and confusing, owing to differences in terminology, behavioral tasks, and analysis methods across studies. In this review, we synthesize consistent findings from this literature, establish a common set of terms, and translate between single-cell and ensemble perspectives. Most importantly, we examine the combined findings through the lens of two major theoretical ideas about hippocampal function: representation of temporal context and latent state inference. We find that unique signature properties of each of these models are necessary to account for the data, but neither theory, by itself, explains all of its features. Specifically, the temporal gradedness of the splitter signal is strong support for temporal context, but is hard to explain using state models, while its flexibility and task-dependence is naturally accounted for using state inference, but poses a challenge otherwise. These theories suggest a number of avenues for future work, and we believe their application to splitter cells is a timely and informative domain for testing and refining theoretical ideas about hippocampal function.

Net gain and loss: influence of natural rewards and drugs of abuse on perineuronal nets

Overindulgence, excessive consumption, and a pattern of compulsive use of natural rewards, such as certain foods or drugs of abuse, may result in the development of obesity or substance use disorder, respectively. Natural rewards and drugs of abuse can trigger similar changes in the neurobiological substrates that drive food- and drug-seeking behaviors. This review examines the impact natural rewards and drugs of abuse have on perineuronal nets (PNNs). PNNs are specialized extracellular matrix structures that ensheathe certain neurons during development over the critical period to provide synaptic stabilization and a protective microenvironment for the cells they surround. This review also analyzes how natural rewards and drugs of abuse impact the density and maturation of PNNs within reward-associated circuitry of the brain, which may contribute to maladaptive food- and drug-seeking behaviors. Finally, we evaluate the relatively few studies that have degraded PNNs to perturb reward-seeking behaviors. Taken together, this review sheds light on the complex way PNNs are regulated by natural rewards and drugs and highlights a need for future studies to delineate the molecular mechanisms that underlie the modification and maintenance of PNNs following exposure to rewarding stimuli.

Complementary task representations in hippocampus and prefrontal cortex for generalizing the structure of problems

Humans and other animals effortlessly generalize prior knowledge to solve novel problems, by abstracting common structure and mapping it onto new sensorimotor specifics. To investigate how the brain achieves this, in this study, we trained mice on a series of reversal learning problems that shared the same structure but had different physical implementations. Performance improved across problems, indicating transfer of knowledge. Neurons in medial prefrontal cortex (mPFC) maintained similar representations across problems despite their different sensorimotor correlates, whereas hippocampal (dCA1) representations were more strongly influenced by the specifics of each problem. This was true for both representations of the events that comprised each trial and those that integrated choices and outcomes over multiple trials to guide an animal's decisions. These data suggest that prefrontal cortex and hippocampus play complementary roles in generalization of knowledge: PFC abstracts the common structure among related problems, and hippocampus maps this structure onto the specifics of the current situation.

The Role of Aberrant Neural Oscillations in the Hippocampal-Medial Prefrontal Cortex Circuit in Neurodevelopmental and Neurological Disorders

The hippocampus (HPC) and medial prefrontal cortex (mPFC) have well-established roles in cognition, emotion, and sensory processing. In recent years, interests have shifted towards developing a deeper understanding of the mechanisms underlying interactions between the HPC and mPFC in achieving these functions. Considerable research supports the idea that synchronized activity between the HPC and the mPFC is a general mechanism by which brain functions are regulated. In this review, we summarize current knowledge on the hippocampal-medial prefrontal cortex (HPC-mPFC) circuit in normal brain function with a focus on oscillations and highlight several neurodevelopmental and neurological disorders associated with aberrant HPC-mPFC circuitry. We further discuss oscillatory dynamics across the HPC-mPFC circuit as potentially useful biomarkers to assess interventions for neurodevelopmental and neurological disorders. Finally, advancements in brain stimulation, gene therapy and pharmacotherapy are explored as promising therapies for disorders with aberrant HPC-mPFC circuit dynamics.

Hippocampal signals modify orbitofrontal representations to learn new paths

We often remember the consequences of past choices to adapt to changing circumstances. Recalling past events requires the hippocampus (HPC), and using stimuli to anticipate outcome values requires the orbitofrontal cortex (OFC).1-3 Spatial reversal tasks require both structures to navigate newly rewarded paths.4,5 Both HPC place6 and OFC value cells7,8 fire in phase with theta (4-12 Hz) oscillations. Both structures are described as cognitive maps: HPC maps space9 and OFC maps task states.10 These similarities imply that OFC-HPC interactions are crucial for using memory to predict outcomes when circumstances change, but the mechanisms remain largely unknown. To investigate possible interactions, we simultaneously recorded ensembles in OFC and CA1 as rats learned spatial reversals in a plus maze. Striking interactions occurred only while rats learned their first reversal: CA1 population vectors predicted changes in OFC activity but not vice versa, OFC spikes phase locked to hippocampal theta oscillations, mixed pairs of CA1 and OFC neurons fired together within single theta cycles, and CA1 led OFC spikes by ∼30 ms. After the new contingency became familiar, CA1 ensembles stably represented distinct spatial paths, whereas OFC ensembles developed more generalized goal arm representations in different paths to identical rewards. These frontotemporal interactions, engaged selectively when new task features inform decision-making, suggest a mechanism for linking novel episodes with expected outcomes, when HPC signals trigger "cognitive remapping" by OFC.11.

Prefrontal feature representations drive memory recall

Memory formation involves binding of contextual features into a unitary representation1-4, whereas memory recall can occur using partial combinations of these contextual features. The neural basis underlying the relationship between a contextual memory and its constituent features is not well understood; in particular, where features are represented in the brain and how they drive recall. Here, to gain insight into this question, we developed a behavioural task in which mice use features to recall an associated contextual memory. We performed longitudinal imaging in hippocampus as mice performed this task and identified robust representations of global context but not of individual features. To identify putative brain regions that provide feature inputs to hippocampus, we inhibited cortical afferents while imaging hippocampus during behaviour. We found that whereas inhibition of entorhinal cortex led to broad silencing of hippocampus, inhibition of prefrontal anterior cingulate led to a highly specific silencing of context neurons and deficits in feature-based recall. We next developed a preparation for simultaneous imaging of anterior cingulate and hippocampus during behaviour, which revealed robust population-level representation of features in anterior cingulate, that lag hippocampus context representations during training but dynamically reorganize to lead and target recruitment of context ensembles in hippocampus during recall. Together, we provide the first mechanistic insights into where contextual features are represented in the brain, how they emerge, and how they access long-range episodic representations to drive memory recall.

Impact of Perineuronal Net Removal in the Rat Medial Prefrontal Cortex on Parvalbumin Interneurons After Reinstatement of Cocaine Conditioned Place Preference

Parvalbumin (PV)-positive cells are GABAergic fast-spiking interneurons that modulate the activity of pyramidal neurons in the medial prefrontal cortex (mPFC) and their output to brain areas associated with learning and memory. The majority of PV cells within the mPFC are surrounded by a specialized extracellular matrix structure called the perineuronal net (PNN). We have shown that removal of PNNs with the enzyme chondroitinase-ABC (Ch-ABC) in the mPFC prevents the consolidation and reconsolidation of cocaine-associated conditioned place preference (CPP) memories. Here we examined the extent to which retrieval of a CPP memory during cocaine-primed reinstatement altered the levels and function of PV neurons and their surrounding PNNs during the reconsolidation period. We further determined the extent to which PNN removal prior to reinstatement altered PV intensity levels and PV cell function. Male Sprague-Dawley rats were trained for cocaine-induced conditioned place preference (CPP) followed by extinction training, microinjection of Ch-ABC in the prelimbic PFC, and cocaine-induced reinstatement. Rats were sacrificed immediately prior to reinstatement or at 2 h, 6 h, or 48 h after reinstatement for immunohistochemistry or 2 h later for electrophysiology. Our findings indicate that PNN removal only partially diminished reinstatement. Cocaine-primed reinstatement produced only minor changes in PNN or PV intensity in vehicle controls. However, after PNN removal, the intensity of remaining PNN-surrounded PV cells was decreased at all times except at 2 h post-reinstatement, at which time cocaine increased PV intensity. Consistent with this, in vehicle controls, PV neurons naturally devoid of PNNs showed a similar pattern to Ch-ABC-treated rats prior to and after cocaine reinstatement, suggesting a protective effect of PNNs on cocaine-induced changes in PV intensity. Using whole-cell patch-clamp, cocaine-primed reinstatement in Ch-ABC-treated rats decreased the number of elicited action potentials but increased excitatory synaptic transmission, which may have been compensatory. These findings suggest that without PNNs, cocaine-induced reinstatement produces rapid changes in PV intensity and PV cell excitability, which may in turn regulate output of the mPFC post-memory retrieval and diminish the maintenance of cocaine memory during reconsolidation.

A cellular switchboard in memory circuits

Neurogliaform cells can direct the flow of information through the hippocampus

The ventral midline thalamus coordinates prefrontal-hippocampal neural synchrony during vicarious trial and error

When faced with difficult choices, the possible outcomes are considered through a process known as deliberation. In rats, deliberation is thought to be reflected by pause-and-reorienting behaviors, better known as vicarious trial and errors (VTEs). While VTEs are thought to require medial prefrontal cortex (mPFC) and dorsal hippocampal (dHPC) interactions, no empirical evidence has yet demonstrated such a dual requirement. The nucleus reuniens (Re) of the ventral midline thalamus is anatomically connected with both the mPFC and dHPC, is required for HPC-dependent spatial memory tasks, and is critical for mPFC-dHPC neural synchronization. Currently, it is unclear if, or how, the Re is involved in deliberation. Therefore, by examining the role of the Re on VTE behaviors, we can better understand the anatomical and physiological mechanisms supporting deliberation. Here, we examined the impact of Re suppression on VTE behaviors and mPFC-dHPC theta synchrony during asymptotic performance of a HPC-dependent delayed alternation (DA) task. Pharmacological suppression of the Re increased VTE behaviors that occurred with repetitive choice errors. These errors were best characterized as perseverative behaviors, in which some rats repeatedly selected a goal arm that previously yielded no reward. We then examined the impact of Re suppression on mPFC-dHPC theta synchrony during VTEs. We found that during VTEs, Re inactivation was associated with a reduction in mPFC-dHPC theta coherence and mPFC-to-dHPC theta directionality. Our findings suggest that the Re contributes to deliberation by coordinating mPFC-dHPC neural interactions.

Inhibition of the ventral midline thalamus does not alter encoding, short-term holding or retrieval of spatial information in rats performing a water-escape working memory task

Working memory (WM) is a function operating in three successive phases: encoding (sample trial), holding (delay), and retrieval (test trial) of information. Studies point to a possible implication of the thalamic reuniens nucleus (Re) in spatial WM (SWM). In which of the aforementioned 3 phases the Re has a function is largely unknown. Recently, in a delayed SWM water-escape task, we found that performance during the retrieval trial correlated positively with c-Fos expression in the Re nucleus, suggesting participation in retrieval. Here, we used the same task and muscimol (Musc) inhibition or DREADD(hM4Di)-mediated inhibition of the Re during information encoding, right thereafter (thereby affecting the holding phase), or during the retrieval trial. A 6-hour delay separated encoding from retrieval. Concerning SWM, Musc in the Re nucleus did not alter performance, be it during or after encoding, or during evaluation. CNO administered before encoding in DREADD-expressing rats was also ineffective, although CNO-induced inhibition disrupted set shifting performance, as found previously (Quet et al., Brain Struct Function 225, 2020), thereby validating DREADD efficiency. These findings are the first that do not support an implication of the Re nucleus in SWM. As most previous studies used T-maze alternation tasks, which carry high proactive interference risks, an important question to resolve now is whether these nuclei are required in (T-maze alternation) tasks using very short information-holding delays (seconds to minutes), and less so in other short-term spatial memory tasks with longer information holding intervals (hours) and therefore reduced interference risks.

ErbB4 in parvalbumin-positive interneurons mediates proactive interference in olfactory associative reversal learning

Consolidated memories influence later learning and cognitive processes when new information is overlapped with previous events. To reveal which cellular and molecular factors are associated with this proactive interference, we challenged mice with odor-reward associative learning followed by a reversal-learning task. The results showed that genetical ablation of ErbB4 in parvalbumin (PV)-positive interneurons improved performance in reversal-learning phase, with no alteration in learning phase, supporting that PV interneuron ErbB4 is required for proactive interference. Mechanistically, olfactory learning promoted PV interneuron excitatory synaptic plasticity and direct binding of ErbB4 with presynaptic Neurexin1β (NRXN1β) and postsynaptic scaffold PSD-95 in the prefrontal cortex. Interrupting ErbB4-NRXN1β interaction impaired network activity-driven excitatory inputs and excitatory synaptic transmission onto PV interneurons. Neuronal activity-induced ErbB4-PSD-95 association facilitated transsynaptic binding of ErbB4-NRXN1β and excitatory synapse formation in ErbB4-positive interneurons. Furthermore, ErbB4-NRXN1β binding was responsible for the activity-regulated activation of ErbB4 and extracellular signal-regulated kinase (ERK) 1/2 in PV interneurons, as well as synaptic plasticity-related expression of brain-derived neurotrophic factor (BDNF). Correlatedly, blocking ErbB4-NRXN1β coupling in the medial prefrontal cortex of adult mice facilitated reversal learning of an olfactory associative task. These findings provide novel insight into the physiological role of PV interneuron ErbB4 signaling in cognitive processes and reveal an associative learning-related transsynaptic NRXN1β-ErbB4-PSD-95 complex that affects the ERK1/2-BDNF pathway and underlies local inhibitory circuit plasticity and proactive interference.

Activity Subspaces in Medial Prefrontal Cortex Distinguish States of the World

Medial prefrontal cortex (mPfC) activity represents information about the state of the world, including present behavior, such as decisions, and the immediate past, such as short-term memory. Unknown is whether information about different states of the world are represented in the same mPfC neural population and, if so, how they are kept distinct. To address this, we analyze here mPfC population activity of male rats learning rules in a Y-maze, with self-initiated choice trials to an arm end followed by a self-paced return during the intertrial interval (ITI). We find that trial and ITI population activity from the same population fall into different low-dimensional subspaces. These subspaces encode different states of the world: multiple features of the task can be decoded from both trial and ITI activity, but the decoding axes for the same feature are roughly orthogonal between the two task phases, and the decodings are predominantly of features of the present during the trial but features of the preceding trial during the ITI. These subspace distinctions are carried forward into sleep, where population activity is preferentially reactivated in post-training sleep but differently for activity from the trial and ITI subspaces. Our results suggest that the problem of interference when representing different states of the world is solved in mPfC by population activity occupying different subspaces for the world states, which can be independently decoded by downstream targets and independently addressed by upstream inputs.SIGNIFICANCE STATEMENT Activity in the medial prefrontal cortex plays a role in representing the current and past states of the world. We show that during a maze task, the activity of a single population in medial prefrontal cortex represents at least two different states of the world. These representations were sequential and sufficiently distinct that a downstream population could separately read out either state from that activity. Moreover, the activity representing different states is differently reactivated in sleep. Different world states can thus be represented in the same medial prefrontal cortex population but in such a way that prevents potentially catastrophic interference between them.

Top-down control of hippocampal signal-to-noise by prefrontal long-range inhibition

Prefrontal cortex (PFC) is postulated to exert "top-down control" on information processing throughout the brain to promote specific behaviors. However, pathways mediating top-down control remain poorly understood. In particular, knowledge about direct prefrontal connections that might facilitate top-down control of hippocampal information processing remains sparse. Here we describe monosynaptic long-range GABAergic projections from PFC to hippocampus. These preferentially inhibit vasoactive intestinal polypeptide-expressing interneurons, which are known to disinhibit hippocampal microcircuits. Indeed, stimulating prefrontal-hippocampal GABAergic projections increases hippocampal feedforward inhibition and reduces hippocampal activity in vivo. The net effect of these actions is to specifically enhance the signal-to-noise ratio for hippocampal encoding of object locations and augment object-induced increases in spatial information. Correspondingly, activating or inhibiting these projections promotes or suppresses object exploration, respectively. Together, these results elucidate a top-down prefrontal pathway in which long-range GABAergic projections target disinhibitory microcircuits, thereby enhancing signals and network dynamics underlying exploratory behavior.

Prefrontal pyramidal neurons are critical for all phases of working memory

The prefrontal cortex (PFC) is essential for working memory (WM) and has primarily been viewed as being responsible for maintaining information over a delay, but it is unclear whether it also plays a more general role during WM. Using task phase-specific optogenetic silencing of pyramidal neurons in the medial PFC (mPFC) of mice performing a spatial WM task, we find that the mPFC is required not only during the delay phase of the task but also during other phases requiring the encoding and retrieval of spatial information. Imaging of mPFC pyramidal neurons reveals that they are most strongly influenced by the animals' position and running direction, indicating a fundamental role in spatial navigation. Pyramidal neuron ensembles also represent to-be-remembered goal locations in a dynamic manner. Taken together, these results delineate the functional contribution of mPFC pyramidal neurons to WM, extending their role beyond the maintenance of information.

Dual projecting cells linking thalamic and cortical communication routes between the medial prefrontal cortex and hippocampus

The interactions between the medial prefrontal cortex (mPFC) and the hippocampus (HC) are critical for memory and decision making and have been specifically implicated in several neurological disorders including schizophrenia, epilepsy, frontotemporal dementia, and Alzheimer's disease. The ventral midline thalamus (vmThal), and lateral entorhinal cortex and perirhinal cortex (LEC/PER) constitute major communication pathways that facilitate mPFC-HC interactions in memory. Although vmThal and LEC/PER circuits have been delineated separately we sought to determine whether these two regions share cell-specific inputs that could influence both routes simultaneously. To do this we used a dual fluorescent retrograde tracing approach using cholera toxin subunit-B (CTB-488 and CTB-594) with injections targeting vmThal and the LEC/PER in rats. Retrograde cell body labeling was examined in key regions of interest within the mPFC-HC system including: (1) mPFC, specifically anterior cingulate cortex (ACC), dorsal and ventral prelimbic cortex (dPL, vPL), and infralimbic cortex (IL); (2) medial and lateral septum (MS, LS); (3) subiculum (Sub) along the dorsal-ventral and proximal-distal axes; and (4) LEC and medial entorhinal cortex (MEC). Results showed that dual vmThal-LEC/PER-projecting cell populations are found in MS, vSub, and the shallow layers II/III of LEC and MEC. We did not find any dual projecting cells in mPFC or in the cornu ammonis (CA) subfields of the HC. Thus, mPFC and HC activity is sent to vmThal and LEC/PER via non-overlapping projection cell populations. Importantly, the dual projecting cell populations in MS, vSub, and EC are in a unique position to simultaneously influence both cortical and thalamic mPFC-HC pathways critical to memory. SIGNIFICANCE STATEMENT: The interactions between mPFC and HC are critical for learning and memory, and dysfunction within this circuit is implicated in various neurodegenerative and psychiatric diseases. mPFC-HC interactions are mediated through multiple communication pathways including a thalamic hub through the vmThal and a cortical hub through lateral entorhinal cortex and perirhinal cortex. Our data highlight newly identified dual projecting cell populations in the septum, Sub, and EC of the rat brain. These dual projecting cells may have the ability to modify the information flow within the mPFC-HC circuit through synchronous activity, and thus offer new cell-specific circuit targets for basic and translational studies in memory.

Multiple-Timescale Neural Networks: Generation of History-Dependent Sequences and Inference Through Autonomous Bifurcations

Sequential transitions between metastable states are ubiquitously observed in the neural system and underlying various cognitive functions such as perception and decision making. Although a number of studies with asymmetric Hebbian connectivity have investigated how such sequences are generated, the focused sequences are simple Markov ones. On the other hand, fine recurrent neural networks trained with supervised machine learning methods can generate complex non-Markov sequences, but these sequences are vulnerable against perturbations and such learning methods are biologically implausible. How stable and complex sequences are generated in the neural system still remains unclear. We have developed a neural network with fast and slow dynamics, which are inspired by the hierarchy of timescales on neural activities in the cortex. The slow dynamics store the history of inputs and outputs and affect the fast dynamics depending on the stored history. We show that the learning rule that requires only local information can form the network generating the complex and robust sequences in the fast dynamics. The slow dynamics work as bifurcation parameters for the fast one, wherein they stabilize the next pattern of the sequence before the current pattern is destabilized depending on the previous patterns. This co-existence period leads to the stable transition between the current and the next pattern in the non-Markov sequence. We further find that timescale balance is critical to the co-existence period. Our study provides a novel mechanism generating robust complex sequences with multiple timescales. Considering the multiple timescales are widely observed, the mechanism advances our understanding of temporal processing in the neural system.

Hippocampal-prefrontal interactions during spatial decision-making

The hippocampus has been linked to memory encoding and spatial navigation, while the prefrontal cortex is associated with cognitive functions such as decision-making. These regions are hypothesized to communicate in tasks that demand both spatial navigation and decision-making processes. However, the electrophysiological signatures underlying this communication remain to be better elucidated. To investigate the dynamics of the hippocampal-prefrontal interactions, we have analyzed their local field potentials and spiking activity recorded from rats performing a spatial alternation task on a figure eight-shaped maze. We found that the phase coherence of theta peaked around the choice point area of the maze. Moreover, Granger causality revealed a hippocampus → prefrontal cortex directionality of information flow at theta frequency, peaking at starting areas of the maze, and on the reverse direction at delta frequency, peaking near the turn onset. Additionally, the patterns of phase-amplitude cross-frequency coupling within and between the regions also showed spatial selectivity, and hippocampal theta and prefrontal delta modulated not only gamma amplitude but also inter-regional gamma synchrony. Finally, we found that the theta rhythm dynamically modulated neurons in both regions, with the highest modulation at the choice area; interestingly, prefrontal cortex neurons were more strongly modulated by the hippocampal theta rhythm than by their local field rhythm. In all, our results reveal maximum electrophysiological interactions between the hippocampus and the prefrontal cortex near the decision-making period of the spatial alternation task, corroborating the hypothesis that a dynamic interplay between these regions takes place during spatial decisions.