Firing characteristics of deep layer neurons in prefrontal cortex in rats performing spatial working memory tasks

Neuronal Waveform Classification in Multielectrode Recordings Using Machine Learning Techniques and Multidimensional Analysis

Extracellular recordings of neuronal spikes are crucial for studying brain activity. These signals are typically classified based on firing patterns and waveform shape, particularly trough-to-peak duration. While useful, this method oversimplifies the diversity of cortical neurons and discharge patterns. Recent advances in recording and analysis techniques allow for more precise waveform classification, though the main criteria remain waveform features. We aim to develop an automatic spike waveform classifier using advanced machine learning techniques selected from a range of candidate methods based on their optimized performance, such as Uniform Manifold Approximation and Projection (UMAP), Gaussian Mixture Model (GMM), and Random Forest (RF). The classifier is part of the working progress of a preprocessing pipeline previously developed. For the classifying step, we use all voltage samples that define each waveform, enabling a multi-dimensional analysis. To evaluate our approach, RF model was trained and tested on a subset of electrophysiological recordings from the human visual cortex achieving high [Formula: see text]-scores. The comparison of the classified neurons was carried out between our method and a waveform analysis toolbox described in the literature. Our method improves the characterization of the clusters of waveforms based on statistical measurements that found a third group while the accepted method categorizes just broad and narrow waveforms, labeling some as unclassifiable.

Conjoint generalized and trajectory-specific coding of task structure by prefrontal neurons

Neurons in the medial prefrontal cortex (mPFC) are spatially tuned. Trajectory-specific firing with distinct spatial tuning on different paths to reward sites as well as generalized spatial tuning with similar responses on separate trajectories have been described. However, it is unclear whether such distinct populations contribute differently to the encoding of task space. Here, we find coexisting populations of neurons with trajectory-specific and generalized tuning profiles in an olfaction-guided spatial memory task in mice. Neurons with generalized representation show stable spatial tuning within and across days, allow accurate predictions of the animal's position, and preferentially emerge upon task learning. In contrast, cells with trajectory-specific spatial tuning display dynamically changing tuning functions, are less informative about the current position, and can be identified at a larger proportion early in task learning. These results highlight a role for neurons with generalized tuning in the efficient and stable representation of task space.

Mediodorsal thalamus nucleus-medial prefrontal cortex circuitry regulates cost-benefit decision-making selections

Value-based decision-making involves weighing costs and benefits. The activity of the medial prefrontal cortex reflects cost-benefit assessments, and the mediodorsal thalamus, reciprocally connected with the medial prefrontal cortex, has increasingly been recognized as an active partner in decision-making. However, the specific role of the interaction between the mediodorsal thalamus and the medial prefrontal cortex in regulating the neuronal activity underlying how costs and benefits influence decision-making remains largely unexplored. We investigated this by training the rats to perform a self-determined decision-making task, where longer nose poke durations resulted in correspondingly larger rewards. Our results showed that the inactivation of either the medial prefrontal cortex or the mediodorsal thalamus significantly impaired rat to invest more nose poke duration for larger rewards. Moreover, optogenetic stimulation of the mediodorsal thalamus-medial prefrontal cortex pathway enhanced rats' motivation for larger rewards, whereas inhibition of this pathway resulted in decreased motivation. Notably, we identified a specific population of neurons in the medial prefrontal cortex that exhibited firing patterns correlated with motivation, and these neurons were modulated by the mediodorsal thalamus-medial prefrontal cortex projection. These findings suggest that the motivation during decision-making is encoded primarily by activity of particular neurons in the medial prefrontal cortex and indicate the crucial role of the mediodorsal thalamus-medial prefrontal cortex pathway in maintaining motivation.

Serotonergic neuromodulation of synaptic plasticity

Synaptic plasticity constitutes a fundamental process in the reorganization of neural networks that underlie memory, cognition, emotional responses, and behavioral planning. At the core of this phenomenon lie Hebbian mechanisms, wherein frequent synaptic stimulation induces long-term potentiation (LTP), while less activation leads to long-term depression (LTD). The synaptic reorganization of neuronal networks is regulated by serotonin (5-HT), a neuromodulator capable of modify synaptic plasticity to appropriately respond to mental and behavioral states, such as alertness, attention, concentration, motivation, and mood. Lately, understanding the serotonergic Neuromodulation of synaptic plasticity has become imperative for unraveling its impact on cognitive, emotional, and behavioral functions. Through a comparative analysis across three main forebrain structures-the hippocampus, amygdala, and prefrontal cortex, this review discusses the actions of 5-HT on synaptic plasticity, offering insights into its role as a neuromodulator involved in emotional and cognitive functions. By distinguishing between plastic and metaplastic effects, we provide a comprehensive overview about the mechanisms of 5-HT neuromodulation of synaptic plasticity and associated functions across different brain regions.

Rat anterior cingulate neurons responsive to rule or strategy changes are modulated by the hippocampal theta rhythm and sharp-wave ripples

To better understand neural processing during adaptive learning of stimulus-response-reward contingencies, we recorded synchrony of neuronal activity in anterior cingulate cortex (ACC) and hippocampal rhythms in male rats acquiring and switching between spatial and visual discrimination tasks in a Y-maze. ACC population activity as well as single unit activity shifted shortly after task rule changes or just before the rats adopted different task strategies. Hippocampal theta oscillations (associated with memory encoding) modulated an elevated proportion of rule-change responsive neurons (70%), but other neurons that were correlated with strategy-change, strategy value and reward-rate were not. However, hippocampal sharp wave-ripples modulated significantly higher proportions of rule-change, strategy-change and reward-rate responsive cells during post-session sleep but not pre-session sleep. This suggests an underestimated mechanism for hippocampal mismatch and contextual signals to facilitate ACC to detect contingency changes for cognitive flexibility, a function that is attenuated after it is damaged.

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.

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.

Large-scale coupling of prefrontal activity patterns as a mechanism for cognitive control in health and disease: evidence from rodent models

Cognitive control of behavior is crucial for well-being, as allows subject to adapt to changing environments in a goal-directed way. Changes in cognitive control of behavior is observed during cognitive decline in elderly and in pathological mental conditions. Therefore, the recovery of cognitive control may provide a reliable preventive and therapeutic strategy. However, its neural basis is not completely understood. Cognitive control is supported by the prefrontal cortex, structure that integrates relevant information for the appropriate organization of behavior. At neurophysiological level, it is suggested that cognitive control is supported by local and large-scale synchronization of oscillatory activity patterns and neural spiking activity between the prefrontal cortex and distributed neural networks. In this review, we focus mainly on rodent models approaching the neuronal origin of these prefrontal patterns, and the cognitive and behavioral relevance of its coordination with distributed brain systems. We also examine the relationship between cognitive control and neural activity patterns in the prefrontal cortex, and its role in normal cognitive decline and pathological mental conditions. Finally, based on these body of evidence, we propose a common mechanism that may underlie the impaired cognitive control of behavior.

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.

Local field potentials and single unit dynamics in motor cortex of unconstrained macaques during different behavioral states

Different sleep stages have been shown to be vital for a variety of brain functions, including learning, memory, and skill consolidation. However, our understanding of neural dynamics during sleep and the role of prominent LFP frequency bands remain incomplete. To elucidate such dynamics and differences between behavioral states we collected multichannel LFP and spike data in primary motor cortex of unconstrained macaques for up to 24 h using a head-fixed brain-computer interface (Neurochip3). Each 8-s bin of time was classified into awake-moving (Move), awake-resting (Rest), REM sleep (REM), or non-REM sleep (NREM) by using dimensionality reduction and clustering on the average spectral density and the acceleration of the head. LFP power showed high delta during NREM, high theta during REM, and high beta when the animal was awake. Cross-frequency phase-amplitude coupling typically showed higher coupling during NREM between all pairs of frequency bands. Two notable exceptions were high delta-high gamma and theta-high gamma coupling during Move, and high theta-beta coupling during REM. Single units showed decreased firing rate during NREM, though with increased short ISIs compared to other states. Spike-LFP synchrony showed high delta synchrony during Move, and higher coupling with all other frequency bands during NREM. These results altogether reveal potential roles and functions of different LFP bands that have previously been unexplored.

Striatum-projecting prefrontal cortex neurons support working memory maintenance

Neurons in the medial prefrontal cortex (mPFC) are functionally linked to working memory (WM) but how distinct projection pathways contribute to WM remains unclear. Based on optical recordings, optogenetic perturbations, and pharmacological interventions in male mice, we report here that dorsomedial striatum (dmStr)-projecting mPFC neurons are essential for WM maintenance, but not encoding or retrieval, in a T-maze spatial memory task. Fiber photometry of GCaMP6m-labeled mPFC→dmStr neurons revealed strongest activity during the maintenance period, and optogenetic inhibition of these neurons impaired performance only when applied during this period. Conversely, enhancing mPFC→dmStr pathway activity-via pharmacological suppression of HCN1 or by optogenetic activation during the maintenance period-alleviated WM impairment induced by NMDA receptor blockade. Moreover, cellular-resolution miniscope imaging revealed that >50% of mPFC→dmStr neurons are active during WM maintenance and that this subpopulation is distinct from neurons active during encoding and retrieval. In all task periods, neuronal sequences were evident. Striatum-projecting mPFC neurons thus critically contribute to spatial WM maintenance.

Resolving the prefrontal mechanisms of adaptive cognitive behaviors: A cross-species perspective

The prefrontal cortex (PFC) enables a staggering variety of complex behaviors, such as planning actions, solving problems, and adapting to new situations according to external information and internal states. These higher-order abilities, collectively defined as adaptive cognitive behavior, require cellular ensembles that coordinate the tradeoff between the stability and flexibility of neural representations. While the mechanisms underlying the function of cellular ensembles are still unclear, recent experimental and theoretical studies suggest that temporal coordination dynamically binds prefrontal neurons into functional ensembles. A so far largely separate stream of research has investigated the prefrontal efferent and afferent connectivity. These two research streams have recently converged on the hypothesis that prefrontal connectivity patterns influence ensemble formation and the function of neurons within ensembles. Here, we propose a unitary concept that, leveraging a cross-species definition of prefrontal regions, explains how prefrontal ensembles adaptively regulate and efficiently coordinate multiple processes in distinct cognitive behaviors.

Geometric transformation of cognitive maps for generalization across hippocampal-prefrontal circuits

The ability to abstract information to guide decisions during navigation across changing environments is essential for adaptation and requires the integrity of the hippocampal-prefrontal circuitry. The hippocampus encodes navigational information in a cognitive map, but it remains unclear how cognitive maps are transformed across hippocampal-prefrontal circuits to support abstraction and generalization. Here, we simultaneously record hippocampal-prefrontal ensembles as rats generalize navigational rules across distinct environments. We find that, whereas hippocampal representational maps maintain specificity of separate environments, prefrontal maps generalize across environments. Furthermore, while both maps are structured within a neural manifold of population activity, they have distinct representational geometries. Prefrontal geometry enables abstraction of rule-informative variables, a representational format that generalizes to novel conditions of existing variable classes. Hippocampal geometry lacks such abstraction. Together, these findings elucidate how cognitive maps are structured into distinct geometric representations to support abstraction and generalization while maintaining memory specificity.

Decoding spatial locations from primate lateral prefrontal cortex neural activity during virtual navigation

Objective. Decoding the intended trajectories from brain signals using a brain-computer interface system could be used to improve the mobility of patients with disabilities.Approach. Neuronal activity associated with spatial locations was examined while macaques performed a navigation task within a virtual environment.Main results.Here, we provide proof of principle that multi-unit spiking activity recorded from the lateral prefrontal cortex (LPFC) of non-human primates can be used to predict the location of a subject in a virtual maze during a navigation task. The spatial positions within the maze that require a choice or are associated with relevant task events can be better predicted than the locations where no relevant events occur. Importantly, within a task epoch of a single trial, multiple locations along the maze can be independently identified using a support vector machine model.Significance. Considering that the LPFC of macaques and humans share similar properties, our results suggest that this area could be a valuable implant location for an intracortical brain-computer interface system used for spatial navigation in patients with disabilities.

Working memory and reward increase the accuracy of animal location encoding in the medial prefrontal cortex

The ability to perceive spatial environments and locate oneself during navigation is crucial for the survival of animals. Mounting evidence suggests a role of the medial prefrontal cortex (mPFC) in spatially related behaviors. However, the properties of mPFC spatial encoding and how it is influenced by animal behavior are poorly defined. Here, we train the mice to perform 3 tasks differing in working memory and reward-seeking: a delayed non-match to place (DNMTP) task, a passive alternation (PA) task, and a free-running task. Single-unit recording in the mPFC shows that although individual mPFC neurons exhibit spatially selective firing, they do not reliably represent the animal location. The population activity of mPFC neurons predicts the animal location. Notably, the population coding of animal locations by the mPFC is modulated by animal behavior in that the coding accuracy is higher in tasks involved in working memory and reward-seeking. This study reveals an approach whereby the mPFC encodes spatial positions and the behavioral variables affecting it.

Emotional Memory Processing during REM Sleep with Implications for Post-Traumatic Stress Disorder

REM sleep is important for the processing of emotional memories, including fear memories. Rhythmic interactions, especially in the theta band, between the medial prefrontal cortex (mPFC) and limbic structures are thought to play an important role, but the ways in which memory processing occurs at a mechanistic and circuits level are largely unknown. To investigate how rhythmic interactions lead to fear extinction during REM sleep, we used a biophysically based model that included the infralimbic cortex (IL), a part of the mPFC with a critical role in suppressing fear memories. Theta frequency (4-12 Hz) inputs to a given cell assembly in IL, representing an emotional memory, resulted in the strengthening of connections from the IL to the amygdala and the weakening of connections from the amygdala to the IL, resulting in the suppression of the activity of fear expression cells for the associated memory. Lower frequency (4 Hz) theta inputs effected these changes over a wider range of input strengths. In contrast, inputs at other frequencies were ineffective at causing these synaptic changes and did not suppress fear memories. Under post-traumatic stress disorder (PTSD) REM sleep conditions, rhythmic activity dissipated, and 4 Hz theta inputs to IL were ineffective, but higher-frequency (10 Hz) theta inputs to IL induced changes similar to those seen with 4 Hz inputs under normal REM sleep conditions, resulting in the suppression of fear expression cells. These results suggest why PTSD patients may repeatedly experience the same emotionally charged dreams and suggest potential neuromodulatory therapies for the amelioration of PTSD symptoms.SIGNIFICANCE STATEMENT Rhythmic interactions in the theta band between the mPFC and limbic structures are thought to play an important role in processing emotional memories, including fear memories, during REM sleep. The infralimbic cortex (IL) in the mPFC is thought to play a critical role in suppressing fear memories. We show that theta inputs to the IL, unlike other frequency inputs, are effective in producing synaptic changes that suppress the activity of fear expression cells associated with a given memory. Under PTSD REM sleep conditions, lower-frequency (4 Hz) theta inputs to the IL do not suppress the activity of fear expression cells associated with the given memory but, surprisingly, 10 Hz inputs do. These results suggest potential neuromodulatory therapies for PTSD.

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.

Where Actions Meet Outcomes: Medial Prefrontal Cortex, Central Thalamus, and the Basal Ganglia

Medial prefrontal cortex (mPFC) interacts with distributed networks that give rise to goal-directed behavior through afferent and efferent connections with multiple thalamic nuclei and recurrent basal ganglia-thalamocortical circuits. Recent studies have revealed individual roles for different thalamic nuclei: mediodorsal (MD) regulation of signaling properties in mPFC neurons, intralaminar control of cortico-basal ganglia networks, ventral medial facilitation of integrative motor function, and hippocampal functions supported by ventral midline and anterior nuclei. Large scale mapping studies have identified functionally distinct cortico-basal ganglia-thalamocortical subnetworks that provide a structural basis for understanding information processing and functional heterogeneity within the basal ganglia. Behavioral analyses comparing functional deficits produced by lesions or inactivation of specific thalamic nuclei or subregions of mPFC or the basal ganglia have elucidated the interdependent roles of these areas in adaptive goal-directed behavior. Electrophysiological recordings of mPFC neurons in rats performing delayed non-matching-to position (DNMTP) and other complex decision making tasks have revealed populations of neurons with activity related to actions and outcomes that underlie these behaviors. These include responses related to motor preparation, instrumental actions, movement, anticipation and delivery of action outcomes, memory delay, and spatial context. Comparison of results for mPFC, MD, and ventral pallidum (VP) suggest critical roles for mPFC in prospective processes that precede actions, MD for reinforcing task-relevant responses in mPFC, and VP for providing feedback about action outcomes. Synthesis of electrophysiological and behavioral results indicates that different networks connecting mPFC with thalamus and the basal ganglia are organized to support distinct functions that allow organisms to act efficiently to obtain intended outcomes.

Dose-Dependent Regulation on Prefrontal Neuronal Working Memory by Dopamine D1 Agonists: Evidence of Receptor Functional Selectivity-Related Mechanisms

Low doses of dopamine D1 agonists improve working memory-related behavior, but high doses eliminate the improvement, thus yielding an ‘inverted-U’ dose-response curve. This dose-dependency also occurs at the single neuron level in the prefrontal cortex where the cellular basis of working memory is represented. Because signaling mechanisms are unclear, we examined this process at the neuron population level. Two D1 agonists (2-methyldihydrexidine and CY208,243) having different signaling bias were tested in rats performing a spatial working memory-related T-maze task. 2-Methyldihydrexidine is slightly bias toward D1-mediated β-arrestin-related signaling as it is a full agonist at adenylate cyclase and a super-agonist at β-arrestin recruitment, whereas CY208,243 is slightly bias toward D1-mediated cAMP signaling as it has relatively high intrinsic activity at adenylate cyclase, but is a partial agonist at β-arrestin recruitment. Both compounds had the expected inverted U dose-dependency in modulating prefrontal neuronal activities, albeit with important differences. Although CY208,243 was superior in improving the strength of neuronal outcome sensitivity to the working memory-related choice behavior in the T-maze, 2-methyldihydrexidine better reduced neuron-to-neuron variation. Interestingly, at the neuron population level, both drugs affected the percentage, uniformity, and ensemble strength of neuronal sensitivity in a complicated dose-dependent fashion, but the overall effect suggested higher efficiency and potency of 2-methyldihydrexidine compared to CY208,243. The differences between 2-methyldihydrexidine and CY208,243 may be related to their specific D1 signaling. These results suggest that D1-related dose-dependent regulation of working memory can be modified differentially by functionally selective ligands, theoretically increasing the balance between desired and undesired effects.

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.

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.

Topographically organized representation of space and context in the medial prefrontal cortex

The neocortex is composed of areas with specialized functions (e.g., sensory versus associational). Despite this functional diversity, emerging evidence suggests that the encoding of space might be a universal feature of cortical circuits. Here, we identified a gradient of spatial tuning depth along the dorsoventral axis. A complex topography of spatial tuning properties might support a division of labor among medial prefrontal cortical subnetworks to support local circuit computation relevant for the execution of context-dependent behavioral outcomes.

Spatial tuning of neocortical pyramidal cells has been observed in diverse cortical regions and is thought to rely primarily on input from the hippocampal formation. Despite the well-studied hippocampal place code, many properties of the neocortical spatial tuning system are still insufficiently understood. In particular, it has remained unclear how the topography of direct anatomical connections from hippocampus to neocortex affects spatial tuning depth, and whether the dynamics of spatial coding in the hippocampal output region CA1, such as remapping in novel environments, is transmitted to the neocortex. Using mice navigating through virtual environments, we addressed these questions in the mouse medial prefrontal cortex, which receives direct input from the hippocampus. We found a rapidly emerging prefrontal representation of space in the absence of task rules, which discriminates familiar from novel environments and is reinstated upon reexposure to the same familiar environment. Topographical analysis revealed a dorsoventral gradient in the representation of the own position, which runs opposite to the innervation density of hippocampal inputs. Jointly, these results reveal a dynamically emerging and topographically organized prefrontal place code during spontaneous locomotion.

Synthetic Spatial Foraging With Active Inference in a Geocaching Task

Humans are highly proficient in learning about the environments in which they operate. They form flexible spatial representations of their surroundings that can be leveraged with ease during spatial foraging and navigation. To capture these abilities, we present a deep Active Inference model of goal-directed behavior, and the accompanying belief updating. Active Inference rests upon optimizing Bayesian beliefs to maximize model evidence or marginal likelihood. Bayesian beliefs are probability distributions over the causes of observable outcomes. These causes include an agent's actions, which enables one to treat planning as inference. We use simulations of a geocaching task to elucidate the belief updating-that underwrites spatial foraging-and the associated behavioral and neurophysiological responses. In a geocaching task, the aim is to find hidden objects in the environment using spatial coordinates. Here, synthetic agents learn about the environment via inference and learning (e.g., learning about the likelihoods of outcomes given latent states) to reach a target location, and then forage locally to discover the hidden object that offers clues for the next location.

Event-based control of autonomic and emotional states by the anterior cingulate cortex

Despite being an intensive area of research, the function of the anterior cingulate cortex (ACC) remains somewhat of a mystery. Human imaging studies implicate the ACC in various cognitive functions, yet surgical ACC lesions used to treat emotional disorders have minimal lasting effects on cognition. An alternative view is that ACC regulates autonomic states, consistent with its interconnectivity with autonomic control regions and that stimulation evokes changes in autonomic/emotional states. At the cellular level, ACC neurons are highly multi-modal and promiscuous, and can represent a staggering array of task events. These neurons nevertheless combine to produce highly event-specific ensemble patterns that likely alter activity in downstream regions controlling emotional and autonomic tone. Since neuromodulators regulate the strength of the ensemble activity patterns, they would regulate the impact these patterns have on downstream targets. Through these mechanisms, the ACC may determine how strongly to react to the very events its ensembles represent. Pathologies arise when specific event-related representations gain excessive control over autonomic/emotional states.

Navigating for reward

An organism's survival can depend on its ability to recall and navigate to spatial locations associated with rewards, such as food or a home. Accumulating research has revealed that computations of reward and its prediction occur on multiple levels across a complex set of interacting brain regions, including those that support memory and navigation. However, how the brain coordinates the encoding, recall and use of reward information to guide navigation remains incompletely understood. In this Review, we propose that the brain's classical navigation centres - the hippocampus and the entorhinal cortex - are ideally suited to coordinate this larger network by representing both physical and mental space as a series of states. These states may be linked to reward via neuromodulatory inputs to the hippocampus-entorhinal cortex system. Hippocampal outputs can then broadcast sequences of states to the rest of the brain to store reward associations or to facilitate decision-making, potentially engaging additional value signals downstream. This proposal is supported by recent advances in both experimental and theoretical neuroscience. By discussing the neural systems traditionally tied to navigation and reward at their intersection, we aim to offer an integrated framework for understanding navigation to reward as a fundamental feature of many cognitive processes.

Prefrontal Cortical Neurons Are Selective for Non-Local Hippocampal Representations during Replay and Behavior

Diverse functions such as decision-making and memory consolidation may depend on communication between neurons in the hippocampus (HP) and prefrontal cortex (PFC). HP replay is a candidate mechanism to facilitate this communication, however details remain largely unknown because of the technical challenges of recording sufficient numbers of HP neurons for replay while also recording PFC neurons. Here, we implanted male rats with 40-tetrode drives, split between HP and PFC, during learning of a Y-maze spatial memory task. Surprisingly, we found that in contrast to their non-selectivity for maze arm during movement, a portion of PFC neurons were highly selective for HP replay of different arms. Moreover, PFC neurons' selectivity to HP non-local arm representation during running tended to match their replay arm selectivity and was predictive of future choice. Thus, PFC activity that is tuned to HP activity is best explained by non-local HP position representations rather than HP representation of actual position, providing a new potential mechanism of HP-PFC coordination during HP replay.SIGNIFICANCE STATEMENT The hippocampus (HP) is implicated in spatial learning while the prefrontal cortex (PFC) is implicated in decision-making. The question of how the two areas interact has been of great interest. A specific activity type in HP called replay is particularly interesting because it resembles internal exploration of non-local experiences, but is technically challenging to study, requiring recordings from large numbers of HP neurons simultaneously. Here, we combined replay recordings from HP with prefrontal recordings, to reveal a surprising degree of selectivity for replay, and a pattern of coordination that supports some conceptions of hippocampocortical interaction and challenges others.

The role of the medial prefrontal cortex in cognition, ageing and dementia

Humans require a plethora of higher cognitive skills to perform executive functions, such as reasoning, planning, language and social interactions, which are regulated predominantly by the prefrontal cortex. The prefrontal cortex comprises the lateral, medial and orbitofrontal regions. In higher primates, the lateral prefrontal cortex is further separated into the respective dorsal and ventral subregions. However, all these regions have variably been implicated in several fronto-subcortical circuits. Dysfunction of these circuits has been highlighted in vascular and other neurocognitive disorders. Recent advances suggest the medial prefrontal cortex plays an important regulatory role in numerous cognitive functions, including attention, inhibitory control, habit formation and working, spatial or long-term memory. The medial prefrontal cortex appears highly interconnected with subcortical regions (thalamus, amygdala and hippocampus) and exerts top-down executive control over various cognitive domains and stimuli. Much of our knowledge comes from rodent models using precise lesions and electrophysiology readouts from specific medial prefrontal cortex locations. Although, anatomical disparities of the rodent medial prefrontal cortex compared to the primate homologue are apparent, current rodent models have effectively implicated the medial prefrontal cortex as a neural substrate of cognitive decline within ageing and dementia. Human brain connectivity-based neuroimaging has demonstrated that large-scale medial prefrontal cortex networks, such as the default mode network, are equally important for cognition. However, there is little consensus on how medial prefrontal cortex functional connectivity specifically changes during brain pathological states. In context with previous work in rodents and non-human primates, we attempt to convey a consensus on the current understanding of the role of predominantly the medial prefrontal cortex and its functional connectivity measured by resting-state functional MRI in ageing associated disorders, including prodromal dementia states, Alzheimer's disease, post-ischaemic stroke, Parkinsonism and frontotemporal dementia. Previous cross-sectional studies suggest that medial prefrontal cortex functional connectivity abnormalities are consistently found in the default mode network across both ageing and neurocognitive disorders such as Alzheimer's disease and vascular cognitive impairment. Distinct disease-specific patterns of medial prefrontal cortex functional connectivity alterations within specific large-scale networks appear to consistently feature in the default mode network, whilst detrimental connectivity alterations are associated with cognitive impairments independently from structural pathological aberrations, such as grey matter atrophy. These disease-specific patterns of medial prefrontal cortex functional connectivity also precede structural pathological changes and may be driven by ageing-related vascular mechanisms. The default mode network supports utility as a potential biomarker and therapeutic target for dementia-associated conditions. Yet, these associations still require validation in longitudinal studies using larger sample sizes.

Concurrent electrophysiological recording and cognitive testing in a rodent touchscreen environment

Challenges in therapeutics development for neuropsychiatric disorders can be attributed, in part, to a paucity of translational models capable of capturing relevant phenotypes across clinical populations and laboratory animals. Touch-sensitive procedures are increasingly used to develop innovative animal models that better align with testing conditions used in human participants. In addition, advances in electrophysiological techniques have identified neurophysiological signatures associated with characteristics of neuropsychiatric illness. The present studies integrated these methodologies by developing a rat flanker task with electrophysiological recordings based on reverse-translated protocols used in human electroencephalogram (EEG) studies of cognitive control. Various touchscreen-based stimuli were evaluated for their ability to efficiently gain stimulus control and advance to flanker test sessions. Optimized stimuli were then examined for their elicitation of prototypical visual evoked potentials (VEPs) across local field potential (LFP) wires and EEG skull screws. Of the stimuli evaluated, purple and green photographic stimuli were associated with efficient training and expected flanker interference effects. Orderly stimulus-locked outcomes were also observed in VEPs across LFP and EEG recordings. These studies along with others verify the feasibility of concurrent electrophysiological recordings and rodent touchscreen-based cognitive testing and encourage future use of this integrated approach in therapeutics development.

Task-dependent mixed selectivity in the subiculum

CA1 and subiculum (SUB) connect the hippocampus to numerous output regions. Cells in both areas have place-specific firing fields, although they are more dispersed in SUB. Weak responses to head direction and running speed have been reported in both regions. However, how such information is encoded in CA1 and SUB and the resulting impact on downstream targets are poorly understood. Here, we estimate the tuning of simultaneously recorded CA1 and SUB cells to position, head direction, and speed. Individual neurons respond conjunctively to these covariates in both regions, but the degree of mixed representation is stronger in SUB, and more so during goal-directed spatial navigation than free foraging. Each navigational variable could be decoded with higher precision, from a similar number of neurons, in SUB than CA1. The findings point to a possible contribution of mixed-selective coding in SUB to efficient transmission of hippocampal representations to widespread brain regions.

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CA1 and subiculum neurons respond conjunctively to position, head direction, and speed

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The degree of conjunctive coding (“mixed selectivity”) is stronger in the subiculum

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Mixed selectivity is stronger during goal-directed navigation than in free foraging

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Decoding of each navigational covariate is more accurate with mixed selectivity

Neuronal Representation of Locomotion During Motivated Behavior in the Mouse Anterior Cingulate Cortex

The anterior cingulate cortex (ACC) is located within the dorsomedial prefrontal cortex (PFC), and processes and facilitates goal-directed behaviors relating to emotion, reward, and motor control. However, it is unclear how ACC neurons dynamically encode motivated behavior during locomotion. In this study, we examined how information for locomotion and behavioral outcomes is temporally represented by individual and ensembles of ACC neurons in mice during a self-paced locomotor reward-based task. By recording and analyzing the activity of ACC neurons with a microdrive tetrode array while the mouse performed the locomotor task, we found that more than two-fifths of the neurons showed phasic activity relating to locomotion or the reward behavior. Some of these neurons showed significant differences in their firing rate depending on the behavioral outcome. Furthermore, by applying a demixed principal component analysis, the ACC population activity was decomposed into components representing locomotion and the previous/future outcome. These results indicated that ACC neurons dynamically integrate motor and behavioral inputs during goal-directed behaviors.

Central Thalamic-Medial Prefrontal Control of Adaptive Responding in the Rat: Many Players in the Chamber

The medial prefrontal cortex (mPFC) has robust afferent and efferent connections with multiple nuclei clustered in the central thalamus. These nuclei are elements in large-scale networks linking mPFC with the hippocampus, basal ganglia, amygdala, other cortical areas, and visceral and arousal systems in the brainstem that give rise to adaptive goal-directed behavior. Lesions of the mediodorsal nucleus (MD), the main source of thalamic input to middle layers of PFC, have limited effects on delayed conditional discriminations, like DMTP and DNMTP, that depend on mPFC. Recent evidence suggests that MD sustains and amplifies neuronal responses in mPFC that represent salient task-related information and is important for detecting and encoding contingencies between actions and their consequences. Lesions of rostral intralaminar (rIL) and ventromedial (VM) nuclei produce delay-independent impairments of egocentric DMTP and DNMTP that resemble effects of mPFC lesions on response speed and accuracy: results consistent with projections of rIL to striatum and VM to motor cortices. The ventral midline and anterior thalamic nuclei affect allocentric spatial cognition and memory consistent with their connections to mPFC and hippocampus. The dorsal midline nuclei spare DMTP and DNMTP. They have been implicated in behavioral-state control and response to salient stimuli in associative learning. mPFC functions are served during DNMTP by discrete populations of neurons with responses related to motor preparation, movements, lever press responses, reinforcement anticipation, reinforcement delivery, and memory delay. Population analyses show that different responses are timed so that they effectively tile the temporal interval from when DNMTP trials are initiated until the end. Event-related responses of MD neurons during DNMTP are predominantly related to movement and reinforcement, information important for DNMTP choice. These responses closely mirror the activity of mPFC neurons with similar responses. Pharmacological inactivation of MD and adjacent rIL affects the expression of diverse action- and outcome-related responses of mPFC neurons. Lesions of MD before training are associated with a shift away from movement-related responses in mPFC important for DNMTP choice. These results suggest that MD has short-term effects on the expression of event-related activity in mPFC and long-term effects that tune mPFC neurons to respond to task-specific information.

The Versatile Wayfinder: Prefrontal Contributions to Spatial Navigation

The prefrontal cortex (PFC) supports decision-making, goal tracking, and planning. Spatial navigation is a behavior that taxes these cognitive processes, yet the role of the PFC in models of navigation has been largely overlooked. In humans, activity in dorsolateral PFC (dlPFC) and ventrolateral PFC (vlPFC) during detours, reveal a role in inhibition and replanning. Dorsal anterior cingulate cortex (dACC) is implicated in planning and spontaneous internally-generated changes of route. Orbitofrontal cortex (OFC) integrates representations of the environment with the value of actions, providing a 'map' of possible decisions. In rodents, medial frontal areas interact with hippocampus during spatial decisions and switching between navigation strategies. In reviewing these advances, we provide a framework for how different prefrontal regions may contribute to different stages of navigation.

The anterior cingulate cortex and event-based modulation of autonomic states

In spite of being an intensive area of research focus, the anterior cingulate cortex (ACC) remains somewhat of an enigma. Many theories have focused on its role in various aspects of cognition yet surgically precise lesions of the ACC, used to treat severe emotional disorders in human patients, typically have no lasting effects on cognition. An alternative view is that the ACC has a prominent role in regulating autonomic states. This view is consistent with anatomical data showing that a main target of the ACC are regions involved in autonomic control and with the observation that stimulation of the ACC evokes changes in autonomic states in both animals and humans. From an electrophysiological perspective, ACC neurons appear able to represent virtually any event or internal state, even though there is not always a strong link between these representations and behavior. Ensembles of neurons form robust contextual representations that strongly influence how specific events are encoded. The activity patterns associated with these contextually-based event representations presumably impact activity in downstream regions that control autonomic state. As a result, the ACC may regulate the autonomic and perhaps emotional reactions to events it is representing. This event-based control of autonomic tone by the ACC would likely arise during all types of cognitive and affective processes, without necessarily being critical for any of them.

Canonical goal-selective representations are absent from prefrontal cortex in a spatial working memory task requiring behavioral flexibility

The prefrontal cortex (PFC)'s functions are thought to include working memory, as its activity can reflect information that must be temporarily maintained to realize the current goal. We designed a flexible spatial working memory task that required rats to navigate - after distractions and a delay - to multiple possible goal locations from different starting points and via multiple routes. This made the current goal location the key variable to remember, instead of a particular direction or route to the goal. However, across a broad population of PFC neurons, we found no evidence of current-goal-specific memory in any previously reported form - that is differences in the rate, sequence, phase, or covariance of firing. This suggests that such patterns do not hold working memory in the PFC when information must be employed flexibly. Instead, the PFC grouped locations representing behaviorally equivalent task features together, consistent with a role in encoding long-term knowledge of task structure.

Prefrontal contributions to action control in rodents

The rodent medial prefrontal cortex (mPFC) is typically considered to be involved in cognitive aspects of action control, e.g., decision making, rule learning and application, working memory and generally guiding adaptive behavior (Euston, Gruber, & McNaughton, 2012). These cognitive aspects often occur on relatively slow time scales, i.e., in the order of several trials within a block structure (Murakami, Shteingart, Loewenstein, & Mainen, 2017). In this way, the mPFC is able to set up a representational memory (Goldman-Rakic, 1987). On the other hand, the mPFC can also impact action control more directly (i.e., more on the motoric and less cognitive side). This impact on motor control manifests on faster time scales, i.e., on a single trial level (Hardung et al., 2017). While the more cognitive aspects have been reviewed previously as well as in other subchapters of this book, we explicitly focus on the latter aspect in this chapter, particularly on movement inhibition. We discuss models of prefrontal motor interactions, the impact of the behavioral paradigm, evidences for mPFC involvement in action control, and the anatomical connections between mPFC and motor cortex.

Reward signaling by the rodent medial frontal cortex

The anatomical relevance and functional significance of medial parts of the rodent frontal cortex have been intensely debated over the modern history of neuroscience. Early studies emphasized common functions among medial frontal regions in rodents and the dorsolateral prefrontal cortex of primates. Behavioral tasks emphasized memory-guided performance and persistent neural activity as a marker of working memory. Over time, it became clear that long-standing concerns about cross-species homology were justified and the view emerged that rodents are useful for understanding medial parts of the frontal cortex in primates, and not the dorsolateral prefrontal cortex. Here, we summarize a series of studies on the rodent medial frontal cortex that began with an interest in studying working memory in the perigenual prelimbic area and ended up studying reward processing in the medial orbital region. Our experiments revealed a role for a 4-8Hz "theta" rhythm in tracking engagement in the consumption of rewarding fluids and denoting the value of a given reward. Evidence for a functional differentiation between the rostral and caudal medial frontal cortex and its relationship to other frontal cortical areas is also discussed with the hope of motivating future work on this part of the cerebral cortex.

Working memory training effects across the lifespan: Evidence from human and experimental animal studies

Working memory refers to a cognitive function that provides temporary storage and manipulation of the information necessary for complex cognitive tasks. Due to its central role in general cognition, several studies have investigated the possibility that training on working memory tasks could improve not only working memory function but also increase other cognitive abilities or modulate other behaviors. This possibility is still highly controversial, with prior studies providing contradictory findings. The lack of systematic approaches and methodological shortcomings complicates this debate even more. This review highlights the impact of working memory training at different ages on humans. Finally, it demonstrates several findings about the neural substrate of training in both humans and experimental animals, including non-human primates and rodents.

Plastic changes to dendritic spines in the cerebellar and prefrontal cortices underlie the decline in motor coordination and working memory during successful aging

Old age is the last stage of life and by taking a multidimensional view of aging, Neuroscientists have been able to characterize pathological or successful aging. Psychomotor and cognitive performance are recognized as two major domains of successful aging, with a loss of motor coordination and working memory deficits two of the most characteristic features of elderly people. Dendritic spines in both the cerebellar and prefrontal cortices diminish in aging, yet the plastic changes in dendritic spines have not been related to behavioral performance neither the changes in the cerebellar or prefrontal cortices. As such, motor coordination and visuospatial working memory (vsWM) was evaluated here in aged, 22-month-old rats, calculating the density of spines and the proportion of the different types of spines. These animals performed erratically and slowly in a motor coordination-related paradigm, and the vsWM was resolved deficiently. Spine density was reduced in aged animals, and the proportional density of each of the spine types studied diminished in both the brain regions studied. The loss of dendritic spines and particularly, the changes in the proportional density of the different spine types could underlie, at least in part, the behavioral deficits observed during aging. To our knowledge, this is the first study of the plastic changes in different dendritic spine types that might underlie the behavioral alterations in motor and cognitive abilities associated with aging. Further neurochemical and molecular studies will help better understand the functional significance of the plastic changes to dendritic spines in both successful and pathological aging.

Operant conditioning of motor cortex neurons reveals neuron-subtype-specific responses in a brain-machine interface task

Operant conditioning is implemented in brain-machine interfaces (BMI) to induce rapid volitional modulation of single neuron activity to control arbitrary mappings with an external actuator. However, intrinsic factors of the volitional controller (i.e. the brain) or the output stage (i.e. individual neurons) might hinder performance of BMIs with more complex mappings between hundreds of neurons and actuators with multiple degrees of freedom. Improved performance might be achieved by studying these intrinsic factors in the context of BMI control. In this study, we investigated how neuron subtypes respond and adapt to a given BMI task. We conditioned single cortical neurons in a BMI task. Recorded neurons were classified into bursting and non-bursting subtypes based on their spike-train autocorrelation. Both neuron subtypes had similar improvement in performance and change in average firing rate. However, in bursting neurons, the activity leading up to a reward increased progressively throughout conditioning, while the response of non-bursting neurons did not change during conditioning. These results highlight the need to characterize neuron-subtype-specific responses in a variety of tasks, which might ultimately inform the design and implementation of BMIs.

Using rat operant delayed match-to-sample task to identify neural substrates recruited with increased working memory load

The delayed match-to-sample task (DMS) is used to probe working memory (WM) across species. While the involvement of the PFC in this task has been established, limited information exists regarding the recruitment of broader circuitry, especially under the low- versus high-WM load. We sought to address this question by using a variable-delay operant DMS task. Male Sprague-Dawley rats were trained and tested to determine their baseline WM performance across all (0- to 24-sec) delays. Next, rats were tested in a single DMS test with either 0- or 24-sec fixed delay, to assess low-/high-load WM performance. c-Fos mRNA expression was quantified within cortical and subcortical regions and correlated with WM performance. High WM load up-regulated overall c-Fos mRNA expression within the PrL, as well as within a subset of mGlu5+ cells, with load-dependent, local activation of protein kinase C (PKC) as the proposed underlying molecular mechanism. The PrL activity negatively correlated with choice accuracy during high load WM performance. A broader circuitry, including several subcortical regions, was found to be activated under low and/or high load conditions. These findings highlight the role of mGlu5- and/or PKC-dependent signaling within the PrL, and corresponding recruitment of subcortical regions during high-load WM performance.

Representations of On-Going Behavior and Future Actions During a Spatial Working Memory Task by a High Firing-Rate Population of Medial Prefrontal Cortex Neurons

Spatial working memory (SWM) requires the encoding, maintenance, and retrieval of spatially relevant information to guide decision-making. The medial prefrontal cortex (mPFC) has long been implicated in the ability of rodents to perform SWM tasks. While past studies have demonstrated that mPFC ensembles reflect past and future experiences, most findings are derived from tasks that have an experimental overlap between the encoding and retrieval of trajectory specific information. In this study, we recorded single units from the mPFC of rats as they performed a T-maze delayed non-match to position (DNMP) task. This task consists of an encoding dominant sample phase, a memory maintenance delay period, and retrieval dominant choice phase. Using a linear classifier, we investigated whether distinct ensembles collectively reflect various trajectory-dependent experiences. We find that a population of high-firing rate mPFC neurons both predict a future choice and reflect changes in trajectory-dependent behaviors. We then developed a modeling procedure that estimated the number of high and low-firing rate units required to dissociate between various experiences. We find that low firing rate ensembles weakly reflect the direction that rats were forced to turn on the sample phase. This was in contrast to the highly active population that could effectively predict both future decision-making on early stem traversals and trajectory-divergences at T-junction. Finally, we compared the ensemble size necessary to code a forced trajectory to the size required to predict a decision. We provide evidence to suggest that a larger number of highly active neurons are employed during decision-making processes when compared to rewarded forced behaviors. Together, our study provides important insight into how specific ensembles of mPFC units support upcoming choices and ongoing behavior during SWM.

Three brain states in the hippocampus and cortex

Contemporary brain research seeks to understand how cognition is reducible to neural activity. Crucially, much of this effort is guided by a scientific paradigm that views neural activity as essentially driven by external stimuli. In contrast, recent perspectives argue that this paradigm is by itself inadequate and that understanding patterns of activity intrinsic to the brain is needed to explain cognition. Yet, despite this critique, the stimulus-driven paradigm still dominates-possibly because a convincing alternative has not been clear. Here, we review a series of findings suggesting such an alternative. These findings indicate that neural activity in the hippocampus occurs in one of three brain states that have radically different anatomical, physiological, representational, and behavioral correlates, together implying different functional roles in cognition. This three-state framework also indicates that neural representations in the hippocampus follow a surprising pattern of organization at the timescale of ∼1 s or longer. Lastly, beyond the hippocampus, recent breakthroughs indicate three parallel states in the cortex, suggesting shared principles and brain-wide organization of intrinsic neural activity.

Dorsomedial prefrontal cortex and hippocampus represent strategic context even while simultaneously changing representation throughout a task session

Dorsomedial prefrontal cortex (dmPFC) and hippocampus (HPC) are thought to play complementary roles in a spatial working memory and decision-making network, where spatial information from HPC informs representations in dmPFC, and contextual information from dmPFC biases how HPC recalls that information. We recorded simultaneously from neural ensembles in rodent dmPFC and HPC as rats performed a rule-switching task, and found that ensembles in dmPFC and HPC simultaneously encoded task contingencies and other time-varying information. While ensembles in HPC transitioned to represent new contingencies at the same time as rats updated their strategies to be consistent with the new contingency, dmPFC ensembles transitioned earlier. Neural representations of other time-varying information also changed faster in dmPFC than in HPC. Our results suggest that HPC and dmPFC represent contingencies while simultaneously representing other information which changes over time, and that this contextual information is integrated into hippocampal representations more slowly than in dmPFC.

Chronic alcohol-induced liver injury correlates with memory deficits: Role for neuroinflammation

Alcohol use disorder (AUD) affects over 15 million adults over age 18 in the United States, with estimated costs of 220 billion dollars annually - mainly due to poor quality of life and lost productivity, which in turn is intricately linked to cognitive dysfunction. AUD-induced neuroinflammation in the brain, notably the hippocampus, is likely to contribute to cognitive impairments. The neuroinflammatory mechanisms mediating the impact of chronic alcohol on the central nervous system, specifically cognition, require further study. We hypothesized that chronic alcohol consumption impairs memory and increases the inflammatory cytokines TNFα, IL6, MCP1, and IL1β in the hippocampus and prefrontal cortex regions in the brain. Using the chronic-binge Gao-NIAAA alcohol mouse model of liver disease, representative of the drinking pattern common to human alcoholics, we investigated behavioral and neuroinflammatory parameters. Our data show that chronic alcohol intake elevated peripheral and brain alcohol levels, induced serum alanine aminotransferase (ALT, a marker of liver injury), impaired memory and sensorimotor coordination, and increased inflammatory gene expression in the hippocampus and prefrontal cortex. Interestingly, serum ALT and hippocampal IL6 correlated with memory impairment, suggesting an intrinsic relationship between neuroinflammation, cognitive decline, and liver disease. Overall, our results point to a likely liver-brain functional partnership and suggest that future strategies to alleviate hepatic and/or neuroinflammatory impacts of chronic AUD may result in improved cognitive outcomes.

Distinct roles of parvalbumin- and somatostatin-expressing neurons in flexible representation of task variables in the prefrontal cortex

A hallmark of the prefrontal cortex (PFC) is flexible representation of task-relevant variables. To investigate roles of different interneuron subtypes in this process, we examined discharge characteristics and inactivation effects of parvalbumin (PV)- and somatostatin (SST)-expressing neurons in the mouse PFC during probabilistic classical conditioning. We found activity patterns and inactivation effects differed between PV and SST neurons: SST neurons conveyed cue-associated quantitative value signals until trial outcome, whereas PV neurons maintained valence signals even after trial outcome. Also, PV, but not SST, neuronal population showed opposite responses to reward and punishment. Moreover, inactivation of PV, but not SST, neurons affected outcome responses and activity reversal of pyramidal neurons. Modeling suggested opposite responses of PV neurons to reward and punishment as an efficient mechanism for facilitating rapid cue-outcome contingency learning. Our results suggest primary roles of mPFC PV neurons in rapid value updating and SST neurons in predicting values of upcoming events.

Distributed representations of temporal stimulus associations across regular-firing and fast-spiking neurons in rat medial prefrontal cortex

The prefrontal cortex has been implicated in various cognitive processes, including working memory, executive control, decision making, and relational learning. One core computational requirement underlying all these processes is the integration of information across time. When rodents and rabbits associate two temporally discontiguous stimuli, some neurons in the medial prefrontal cortex (mPFC) change firing rates in response to the preceding stimulus and sustain the firing rate during the subsequent temporal interval. These firing patterns are thought to serve as a mechanism to buffer the previously presented stimuli and signal the upcoming stimuli; however, how these critical properties are distributed across different neuron types remains unknown. We investigated the firing selectivity of regular-firing, burst-firing, and fast-spiking neurons in the prelimbic region of the mPFC while rats associated two neutral conditioned stimuli (CS) with one aversive stimulus (US). Analyses of firing patterns of individual neurons and neuron ensembles revealed that regular-firing neurons maintained rich information about CS identity and CS-US contingency during intervals separating the CS and US. Moreover, they further strengthened the latter selectivity with repeated conditioning sessions over a month. The selectivity of burst-firing neurons for both stimulus features was weaker than that of regular-firing neurons, indicating the difference in task engagement between two subpopulations of putative excitatory neurons. In contrast, putative inhibitory, fast-spiking neurons showed a stronger selectivity for CS identity than for CS-US contingency, suggesting their potential role in sensory discrimination. These results reveal a fine-scaled functional organization in the prefrontal network supporting the formation of temporal stimulus associations.NEW & NOTEWORTHY To associate stimuli that occurred separately in time, the brain needs to bridge the temporal gap by maintaining what was presented and predicting what would follow. We show that in rat medial prefrontal cortex, the former function is associated with a subpopulation of putative inhibitory neurons, whereas the latter is supported by a subpopulation of putative excitatory neurons. Our results reveal a distinct contribution of these microcircuit components to neural representations of temporal stimulus associations.

Characterization of the sensory, affective, cognitive, biochemical, and neuronal alterations in a modified chronic constriction injury model of neuropathic pain in mice

The chronic constriction injury (CCI) of the sciatic nerve is a nerve injury-based model of neuropathic pain (NP). Comorbidities of NP such as depression, anxiety, and cognitive deficits are associated with a functional reorganization of the medial prefrontal cortex (mPFC). Here, we have employed an adapted model of CCI by placing one single loose ligature around the sciatic nerve in mice for investigating the alterations in sensory, motor, affective, and cognitive behavior and in electrophysiological and biochemical properties in the prelimbic division (PrL) of the mPFC. Our adapted model of CCI induced mechanical allodynia, motor, and cognitive impairments and anxiety- and depression-like behavior. In the PrL division of mPFC was observed an increase in GABA and a decrease in d-aspartate levels. Moreover an increase in the activity of neurons responding to mechanical stimulation with an excitation, mPFC (+), and a decrease in those responding with an inhibition, mPFC (-), was found. Altogether these findings demonstrate that a single ligature around the sciatic nerve was able to induce sensory, affective, cognitive, biochemical, and functional alterations already observed in other neuropathic pain models and it may be an appropriate and easily reproducible model for studying neuropathic pain mechanisms and treatments.

Analysis of learning deficits in aged rats on the W-track continuous spatial alternation task

Young and aged animals were tested on a spatial alternation task that consisted of two interleaved components: (1) an "outbound" or alternation component (working memory) and (2) an "inbound" component, requiring the animal to remember to return to a central location in space (spatial memory). In the present study, aged rats made more outbound errors throughout testing, resulting in significantly more days to reach learning criterion, as compared to young rats. Furthermore, while all animals were able to learn the hippocampus-dependent inbound component of the task, most aged animals remained just above chance on the outbound component, even after extended testing days. Aged rats may be more impaired on the outbound part of the task because it requires cooperation of both the hippocampus and mPFC, each of which is compromised with age. In addition to presenting these results, we compare one commonly used analysis (repeated measures ANOVA) and two less common hierarchical modeling techniques (hierarchical generalized linear model and state-space random effects model) to determine the best method for comparing population learning over time. We found that hierarchical modeling is the most appropriate for this task and that a state-space model better captures the behavioral responses. (PsycINFO Database Record (c) 2018 APA, all rights reserved).