Learning-induced enduring changes in functional connectivity among prefrontal cortical neurons

A Taxonomy of Neuroscientific Strategies Based on Interaction Orders

In recent decades, neuroscience has advanced with increasingly sophisticated strategies for recording and analysing brain activity, enabling detailed investigations into the roles of functional units, such as individual neurons, brain regions and their interactions. Recently, new strategies for the investigation of cognitive functions regard the study of higher order interactions-that is, the interactions involving more than two brain regions or neurons. Although methods focusing on individual units and their interactions at various levels offer valuable and often complementary insights, each approach comes with its own set of limitations. In this context, a conceptual map to categorize and locate diverse strategies could be crucial to orient researchers and guide future research directions. To this end, we define the spectrum of orders of interaction, namely, a framework that categorizes the interactions among neurons or brain regions based on the number of elements involved in these interactions. We use a simulation of a toy model and a few case studies to demonstrate the utility and the challenges of the exploration of the spectrum. We conclude by proposing future research directions aimed at enhancing our understanding of brain function and cognition through a more nuanced methodological framework.

Quantifying information stored in synaptic connections rather than in firing patterns of neural networks

A cornerstone of our understanding of both biological and artificial neural networks is that they store information in the strengths of connections among the constituent neurons. However, in contrast to the well-established theory for quantifying information encoded by the firing patterns of neural networks, little is known about quantifying information encoded by its synaptic connections. Here, we develop a theoretical framework using continuous Hopfield networks as an exemplar for associative neural networks, and data that follow mixtures of broadly applicable multivariate log-normal distributions. Specifically, we analytically derive the Shannon mutual information between the data and singletons, pairs, triplets, quadruplets, and arbitrary n-tuples of synaptic connections within the network. Our framework corroborates well-established insights about storage capacity of, and distributed coding by, neural firing patterns. Strikingly, it discovers synergistic interactions among synapses, revealing that the information encoded jointly by all the synapses exceeds the 'sum of its parts'. Taken together, this study introduces an interpretable framework for quantitatively understanding information storage in neural networks, one that illustrates the duality of synaptic connectivity and neural population activity in learning and memory.

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.

Acetylcholine-gated current translates wake neuronal firing rate information into a spike timing-based code in Non-REM sleep, stabilizing neural network dynamics during memory consolidation

Sleep is critical for memory consolidation, although the exact mechanisms mediating this process are unknown. Combining reduced network models and analysis of in vivo recordings, we tested the hypothesis that neuromodulatory changes in acetylcholine (ACh) levels during non-rapid eye movement (NREM) sleep mediate stabilization of network-wide firing patterns, with temporal order of neurons’ firing dependent on their mean firing rate during wake. In both reduced models and in vivo recordings from mouse hippocampus, we find that the relative order of firing among neurons during NREM sleep reflects their relative firing rates during prior wake. Our modeling results show that this remapping of wake-associated, firing frequency-based representations is based on NREM-associated changes in neuronal excitability mediated by ACh-gated potassium current. We also show that learning-dependent reordering of sequential firing during NREM sleep, together with spike timing-dependent plasticity (STDP), reconfigures neuronal firing rates across the network. This rescaling of firing rates has been reported in multiple brain circuits across periods of sleep. Our model and experimental data both suggest that this effect is amplified in neural circuits following learning. Together our data suggest that sleep may bias neural networks from firing rate-based towards phase-based information encoding to consolidate memories.

We show that neuromodulatory changes during non-rapid eye movement (NREM) sleep generate stable spike timing relationships between neurons, the ordering of which reflects the neurons’ relative firing rates during wake. Learning-dependent ordering of firing in the hippocampus during NREM, acting in tandem with spike timing-dependent plasticity, reconfigures neuronal firing rates across the hippocampal network. This “rescaling” of neuronal firing rates has recently been reported in multiple brain circuits across periods of sleep. Together, our results suggest that the brain is remapping frequency-biased representations of information formed during wake into timing biased-representations during NREM sleep.

Learning to select actions shapes recurrent dynamics in the corticostriatal system

Learning to select appropriate actions based on their values is fundamental to adaptive behavior. This form of learning is supported by fronto-striatal systems. The dorsal-lateral prefrontal cortex (dlPFC) and the dorsal striatum (dSTR), which are strongly interconnected, are key nodes in this circuitry. Substantial experimental evidence, including neurophysiological recordings, have shown that neurons in these structures represent key aspects of learning. The computational mechanisms that shape the neurophysiological responses, however, are not clear. To examine this, we developed a recurrent neural network (RNN) model of the dlPFC-dSTR circuit and trained it on an oculomotor sequence learning task. We compared the activity generated by the model to activity recorded from monkey dlPFC and dSTR in the same task. This network consisted of a striatal component which encoded action values, and a prefrontal component which selected appropriate actions. After training, this system was able to autonomously represent and update action values and select actions, thus being able to closely approximate the representational structure in corticostriatal recordings. We found that learning to select the correct actions drove action-sequence representations further apart in activity space, both in the model and in the neural data. The model revealed that learning proceeds by increasing the distance between sequence-specific representations. This makes it more likely that the model will select the appropriate action sequence as learning develops. Our model thus supports the hypothesis that learning in networks drives the neural representations of actions further apart, increasing the probability that the network generates correct actions as learning proceeds. Altogether, this study advances our understanding of how neural circuit dynamics are involved in neural computation, revealing how dynamics in the corticostriatal system support task learning.

Temporal Learning Among Prefrontal and Striatal Ensembles

Behavioral flexibility requires the prefrontal cortex and striatum, but it is unclear if these structures play similar or distinct roles in adapting to novel circumstances. Here, we investigate neuronal ensembles in the medial frontal cortex (MFC) and the dorsomedial striatum (DMS) during one form of behavioral flexibility: learning a new temporal interval. We studied corticostriatal neuronal activity as rodents trained to respond after a 12-s fixed interval (FI12) learned to respond at a shorter 3-s fixed interval (FI3). On FI12 trials, we found that a key form of temporal processing—time-related ramping activity—decreased in the MFC but did not change in the DMS as animals learned to respond at a shorter interval. However, while MFC and DMS ramping was stable with successive days of two-interval performance, temporal decoding by DMS ensembles improved on FI3 trials. Finally, when comparing FI12 versus FI3 trials, we found that more DMS neurons than MFC neurons exhibited differential interval-related activity early in two-interval performance. These data suggest that the MFC and DMS play distinct roles during temporal learning and provide insight into corticostriatal circuits.

Functional brain network reconfiguration during learning in a dynamic environment

When learning about dynamic and uncertain environments, people should update their beliefs most strongly when new evidence is most informative, such as when the environment undergoes a surprising change or existing beliefs are highly uncertain. Here we show that modulations of surprise and uncertainty are encoded in a particular, temporally dynamic pattern of whole-brain functional connectivity, and this encoding is enhanced in individuals that adapt their learning dynamics more appropriately in response to these factors. The key feature of this whole-brain pattern of functional connectivity is stronger connectivity, or functional integration, between the fronto-parietal and other functional systems. Our results provide new insights regarding the association between dynamic adjustments in learning and dynamic, large-scale changes in functional connectivity across the brain.

Prefrontal-hippocampal interaction during the encoding of new memories

The hippocampus rapidly forms associations among ongoing events as they unfold and later instructs the gradual stabilisation of their memory traces in the neocortex. Although this two-stage model of memory consolidation has gained substantial empirical support, parallel evidence from rodent studies suggests that the neocortex, in particular the medial prefrontal cortex, might work in concert with the hippocampus during the encoding of new experiences. This opinion article first summarises findings from behavioural, electrophysiological, and molecular studies in rodents that uncovered immediate changes in synaptic connectivity and neural selectivity in the medial prefrontal cortex during and shortly after novel experiences. Based on these findings, I then propose a model positing that the medial prefrontal cortex and hippocampus might use different strategies to encode information during novel experiences, leading to the parallel formation of complementary memory traces in the two regions. The hippocampus captures moment-to-moment changes in incoming inputs with accurate spatial and temporal contexts, whereas the medial prefrontal cortex may sort the inputs based on their similarity and integrates them over time. These processes of pattern recognition and integration enable the medial prefrontal cortex to, in real time, capture the central content of novel experience and emit relevancy signal that helps to enhance the contrast between the relevant and incidental features of the experience. This hypothesis serves as a framework for future investigations on the potential top-down modulation that the medial prefrontal cortex may exert over the hippocampus to enable the selective, perhaps more intelligent encoding of new information.

Critical Dynamics Mediate Learning of New Distributed Memory Representations in Neuronal Networks

We explore the possible role of network dynamics near a critical point in the storage of new information in silico and in vivo, and show that learning and memory may rely on neuronal network features mediated by the vicinity of criticality. Using a mean-field, attractor-based model, we show that new information can be consolidated into attractors through state-based learning in a dynamical regime associated with maximal susceptibility at the critical point. Then, we predict that the subsequent consolidation process results in a shift from critical to sub-critical dynamics to fully encapsulate the new information. We go on to corroborate these findings using analysis of rodent hippocampal CA1 activity during contextual fear memory (CFM) consolidation. We show that the dynamical state of the CA1 network is inherently poised near criticality, but the network also undergoes a shift towards sub-critical dynamics due to successful consolidation of the CFM. Based on these findings, we propose that dynamical features associated with criticality may be universally necessary for storing new memories.

Hippocampus-nidopallium caudolaterale interactions exist in the goal-directed behavior of pigeon

Avian hippocampus (Hp) and nidopallium caudolaterale (NCL) are believed to play key roles in goal-directed behavior. However, it is still unclear whether there are interactions between the two brain regions in the goal-directed behavior of pigeons. To investigate the interactions between the Hp and the NCL in the goal-directed behavior, we recorded local field potential (LFP) signals from the two regions simultaneously when the pigeons performed a goal-directed decision-making task. Amplitude-amplitude coupling analysis revealed that the coupling value between the LFP recorded from the Hp and that from the NCL increased significantly (P < 0.05) in slow gamma-band (40-60 Hz) during the turning area. In addition, the LFP functional network analysis demonstrated the LFP functional connections between the Hp and the NCL increased significantly (P < 0.05) in the turning area. The result of partial directed coherence (PDC) analysis showed that the predominant direction of information flow is thought to be from the Hp to the NCL. These findings suggest that there are causal functional interactions between the Hp and the NCL by which information is transmitted between the two regions relevant to goal-directed behavior.

Learning the meaning of new stimuli increases the cross-correlated activity of prefrontal neurons

The prefrontal cortex (PF) has a key role in learning rules and generating associations between stimuli and responses also called conditional motor learning. Previous studies in PF have examined conditional motor learning at the single cell level but not the correlation of discharges between neurons at the ensemble level. In the present study, we recorded from two rhesus monkeys in the dorsolateral and the mediolateral parts of the prefrontal cortex to address the role of correlated firing of simultaneously recorded pairs during conditional motor learning. We trained two rhesus monkeys to associate three stimuli with three response targets, such that each stimulus was mapped to only one response. We recorded the neuronal activity of the same neuron pairs during learning of new associations and with already learned associations. In these tasks after a period of fixation, a visual instruction stimulus appeared centrally and three potential response targets appeared in three positions: right, left, and up from center. We found a higher number of neuron pairs significantly correlated and higher cross-correlation coefficients during stimulus presentation in the new than in the familiar mapping task. These results demonstrate that learning affects the PF neural correlation structure.

Dynamical networks: Finding, measuring, and tracking neural population activity using network science

Systems neuroscience is in a headlong rush to record from as many neurons at the same time as possible. As the brain computes and codes using neuron populations, it is hoped these data will uncover the fundamentals of neural computation. But with hundreds, thousands, or more simultaneously recorded neurons come the inescapable problems of visualizing, describing, and quantifying their interactions. Here I argue that network science provides a set of scalable, analytical tools that already solve these problems. By treating neurons as nodes and their interactions as links, a single network can visualize and describe an arbitrarily large recording. I show that with this description we can quantify the effects of manipulating a neural circuit, track changes in population dynamics over time, and quantitatively define theoretical concepts of neural populations such as cell assemblies. Using network science as a core part of analyzing population recordings will thus provide both qualitative and quantitative advances to our understanding of neural computation.

Large-scale analysis reveals populational contributions of cortical spike rate and synchrony to behavioural functions

KEY POINTS

There have been few systematic population-wide analyses of relationships between spike synchrony within a period of several milliseconds and behavioural functions. In this study, we obtained a large amount of spike data from > 23,000 neuron pairs by multiple single-unit recording from deep layer neurons in motor cortical areas in rats performing a forelimb movement task. The temporal changes of spike synchrony in the whole neuron pairs were statistically independent of behavioural changes during the task performance, although some neuron pairs exhibited correlated changes in spike synchrony. Mutual information analyses revealed that spike synchrony made a smaller contribution than spike rate to behavioural functions. The strength of spike synchrony between two neurons was statistically independent of the spike rate-based preferences of the pair for behavioural functions.

ABSTRACT

Spike synchrony within a period of several milliseconds in presynaptic neurons enables effective integration of functional information in the postsynaptic neuron. However, few studies have systematically analysed the population-wide relationships between spike synchrony and behavioural functions. Here we obtained a sufficiently large amount of spike data among regular-spiking (putatively excitatory) and fast-spiking (putatively inhibitory) neuron subtypes (> 23,000 pairs) by multiple single-unit recording from deep layers in motor cortical areas (caudal forelimb area, rostral forelimb area) in rats performing a forelimb movement task. After holding a lever, rats pulled the lever either in response to a cue tone (external-trigger trials) or spontaneously without any cue (internal-trigger trials). Many neurons exhibited functional spike activity in association with forelimb movements, and the preference of regular-spiking neurons in the rostral forelimb area was more biased toward externally triggered movement than that in the caudal forelimb area. We found that a population of neuron pairs with spike synchrony does exist, and that some neuron pairs exhibit a dependence on movement phase during task performance. However, the population-wide analysis revealed that spike synchrony was statistically independent of the movement phase and the spike rate-based preferences of the pair for behavioural functions, whereas spike rates were clearly dependent on the movement phase. In fact, mutual information analyses revealed that the contribution of spike synchrony to the behavioural functions was small relative to the contribution of spike rate. Our large-scale analysis revealed that cortical spike rate, rather than spike synchrony, contributes to population coding for movement.

Impaired Functional Connectivity in the Prefrontal Cortex: A Mechanism for Chronic Stress-Induced Neuropsychiatric Disorders

Chronic stress-related psychiatric diseases, such as major depression, posttraumatic stress disorder, and schizophrenia, are characterized by a maladaptive organization of behavioral responses that strongly affect the well-being of patients. Current evidence suggests that a functional impairment of the prefrontal cortex (PFC) is implicated in the pathophysiology of these diseases. Therefore, chronic stress may impair PFC functions required for the adaptive orchestration of behavioral responses. In the present review, we integrate evidence obtained from cognitive neuroscience with neurophysiological research with animal models, to put forward a hypothesis that addresses stress-induced behavioral dysfunctions observed in stress-related neuropsychiatric disorders. We propose that chronic stress impairs mechanisms involved in neuronal functional connectivity in the PFC that are required for the formation of adaptive representations for the execution of adaptive behavioral responses. These considerations could be particularly relevant for understanding the pathophysiology of chronic stress-related neuropsychiatric disorders.

Role of the thalamic nucleus reuniens in mediating interactions between the hippocampus and medial prefrontal cortex during spatial working memory

Despite decades of research, the neural mechanisms of spatial working memory remain poorly understood. Although the dorsal hippocampus is known to be critical for memory-guided behavior, experimental evidence suggests that spatial working memory depends not only on the hippocampus itself, but also on the circuit comprised of the hippocampus and the medial prefrontal cortex (mPFC). Disruption of hippocampal-mPFC interactions may result in failed transfer of spatial and contextual information processed by the hippocampus to the circuitry in mPFC responsible for decision making and goal-directed behavior. Oscillatory synchrony between the hippocampus and mPFC has been shown to increase in tasks with high spatial working memory demand. However, the mechanisms and circuitry supporting hippocampal-mPFC interactions during these tasks is unknown. The midline thalamic nucleus reuniens (RE) is reciprocally connected to both the hippocampus and the mPFC and has been shown to be critical for a variety of working memory tasks. Therefore, it is likely that hippocampal-mPFC oscillatory synchrony is modulated by RE activity. This article will review the anatomical connections between the hippocampus, mPFC and RE along with the behavioral studies that have investigated the effects of RE disruption on working memory task performance. The article will conclude with suggestions for future directions aimed at identifying the specific role of the RE in regulating functional interactions between the hippocampus and the PFC and investigating the degree to which these interactions contribute to spatial working memory.

Emergence of task-dependent representations in working memory circuits

A wealth of experimental evidence suggests that working memory circuits preferentially represent information that is behaviorally relevant. Still, we are missing a mechanistic account of how these representations come about. Here we provide a simple explanation for a range of experimental findings, in light of prefrontal circuits adapting to task constraints by reward-dependent learning. In particular, we model a neural network shaped by reward-modulated spike-timing dependent plasticity (r-STDP) and homeostatic plasticity (intrinsic excitability and synaptic scaling). We show that the experimentally-observed neural representations naturally emerge in an initially unstructured circuit as it learns to solve several working memory tasks. These results point to a critical, and previously unappreciated, role for reward-dependent learning in shaping prefrontal cortex activity.

Volitional enhancement of firing synchrony and oscillation by neuronal operant conditioning: interaction with neurorehabilitation and brain-machine interface

In this review, we focus on neuronal operant conditioning in which increments in neuronal activities are directly rewarded without behaviors. We discuss the potential of this approach to elucidate neuronal plasticity for enhancing specific brain functions and its interaction with the progress in neurorehabilitation and brain-machine interfaces. The key to-be-conditioned activities that this paper emphasizes are synchronous and oscillatory firings of multiple neurons that reflect activities of cell assemblies. First, we introduce certain well-known studies on neuronal operant conditioning in which conditioned enhancements of neuronal firing were reported in animals and humans. These studies demonstrated the feasibility of volitional control over neuronal activity. Second, we refer to the recent studies on operant conditioning of synchrony and oscillation of neuronal activities. In particular, we introduce a recent study showing volitional enhancement of oscillatory activity in monkey motor cortex and our study showing selective enhancement of firing synchrony of neighboring neurons in rat hippocampus. Third, we discuss the reasons for emphasizing firing synchrony and oscillation in neuronal operant conditioning, the main reason being that they reflect the activities of cell assemblies, which have been suggested to be basic neuronal codes representing information in the brain. Finally, we discuss the interaction of neuronal operant conditioning with neurorehabilitation and brain-machine interface (BMI). We argue that synchrony and oscillation of neuronal firing are the key activities required for developing both reliable neurorehabilitation and high-performance BMI. Further, we conclude that research of neuronal operant conditioning, neurorehabilitation, BMI, and system neuroscience will produce findings applicable to these interrelated fields, and neuronal synchrony and oscillation can be a common important bridge among all of them.

Diverse synchrony of firing reflects diverse cell-assembly coding in the prefrontal cortex

In the present paper, we focus on the coding by cell assemblies in the prefrontal cortex (PFC) and discuss the diversity of the coding, which results in stable and dynamic representations and the processing of various information in that higher brain region. The key activity that reflects cell-assembly coding is the synchrony of the firing of multiple neurons when animals are performing cognitive and memory tasks. First, we introduce some studies that have shown task-related synchrony of neuronal firing in the monkey PFC. These studies have reported fixed and several types of dynamic synchronous firing during working memory, long-term visual memory, and goal selection. The results of these studies have indicated that cell assemblies in the PFC can contribute to both the stability and the dynamics of various types of information. Second, we refer to rat studies and introduce the findings of cellular interactions that contribute to synchrony in working memory, learning-induced changes in synchrony in spatial tasks, and interactions of the PFC and hippocampus in dynamic synchrony. These studies have proposed neuronal mechanisms of cell-assembly coding in the PFC and its critical role in the learning of task demands in problematic situations. Based on the monkey and rat studies, we conclude that cell-assembly coding in the PFC is diverse and has various facets, which allow multipotentiality in the higher brain region. Finally, we discuss the problem of the sizes of cell assembly, how diverse the sizes are in the PFC, and the technical problems in their investigation. We introduce a unique spike-sorting method that can detect small and local cell assemblies that consist of closely neighboring neurons. Then, we describe the findings of our study that showed that the monkey PFC has both small and large cell assemblies, which have different roles in information coding in the working brain.

A review of cell assemblies

Since the cell assembly (CA) was hypothesised, it has gained substantial support and is believed to be the neural basis of psychological concepts. A CA is a relatively small set of connected neurons, that through neural firing can sustain activation without stimulus from outside the CA, and is formed by learning. Extensive evidence from multiple single unit recording and other techniques provides support for the existence of CAs that have these properties, and that their neurons also spike with some degree of synchrony. Since the evidence is so broad and deep, the review concludes that CAs are all but certain. A model of CAs is introduced that is informal, but is broad enough to include, e.g. synfire chains, without including, e.g. holographic reduced representation. CAs are found in most cortical areas and in some sub-cortical areas, they are involved in psychological tasks including categorisation, short-term memory and long-term memory, and are central to other tasks including working memory. There is currently insufficient evidence to conclude that CAs are the neural basis of all concepts. A range of models have been used to simulate CA behaviour including associative memory and more process- oriented tasks such as natural language parsing. Questions involving CAs, e.g. memory persistence, CAs' complex interactions with brain waves and learning, remain unanswered. CA research involves a wide range of disciplines including biology and psychology, and this paper reviews literature directly related to the CA, providing a basis of discussion for this interdisciplinary community on this important topic. Hopefully, this discussion will lead to more formal and accurate models of CAs that are better linked to neuropsychological data.

Signals for previous goal choice persist in the dorsomedial, but not dorsolateral striatum of rats

The cortico-basal ganglia network has been proposed to consist of parallel loops serving distinct functions. However, it is still uncertain how the content of processed information varies across different loops and how it is related to the functions of each loop. We investigated this issue by comparing neuronal activity in the dorsolateral (sensorimotor) and dorsomedial (associative) striatum, which have been linked to habitual and goal-directed action selection, respectively, in rats performing a dynamic foraging task. Both regions conveyed significant neural signals for the animal's goal choice and its outcome. Moreover, both regions conveyed similar levels of neural signals for action value before the animal's goal choice and chosen value after the outcome of the animal's choice was revealed. However, a striking difference was found in the persistence of neural signals for the animal's chosen action. Signals for the animal's goal choice persisted in the dorsomedial striatum until the outcome of the animal's next goal choice was revealed, whereas they dissipated rapidly in the dorsolateral striatum. These persistent choice signals might be used for causally linking temporally discontiguous responses and their outcomes in the dorsomedial striatum, thereby contributing to its role in goal-directed action selection.

Stimulus-induced reduction of noise correlation in rat prefrontal cortex

We have shown previously that stimulus-induced modulation of noise correlation in rat somatosensory cortex conveys additional information about the delivery of tactile stimulation. Here we investigated whether noise correlation is also modulated by an external sensory stimulus in rat prefrontal cortex and, if so, whether such modulation conveys additional information on stimulus delivery. Noise correlation was significantly reduced after the onset of a conditional stimulus (auditory tone) that signaled an electric foot shock in the prefrontal cortex. However, noise correlation contributed little to the transmission of information on stimulus delivery. These results indicate that a meaningful sensory stimulus reduces noise correlation in rat prefrontal cortex, but such modulation does not play a significant role in conveying information on stimulus delivery.

Rapid task acquisition of spatial-delayed alternation in an automated T-maze by mice

The spatial-delayed alternation task using a T-maze is the standard method for testing working memory in rodents and is widely used. Until now, however, there has been a gap in the understanding of the underlying brain mechanisms. The development of new manganese-enhanced brain imaging methods now permit a more specific examination of these mechanisms by allowing behavioural brain stimulation to take place outside the MRI scanner and the scan identifying the activation of specific brain regions to take place subsequently. The requirements for this method are a frequent repetition of the behaviour of interest, a control group that differs in only one task parameter and the minimization of unspecific environmental factors to avoid irrelevant stimulation. To meet these requirements, a fully automated spatial-delayed alternation task in a T-maze was developed that used identity detectors and automated gates to route mice individually from their social home cage to the T-maze. An experimental and a control group of mice were trained in procedures that differed only in the parameter "working-memory based alternation". Our data demonstrate that both groups can be trained concurrently with a rapid procedure using the automated T-maze. With its high level of stimulation, the minimization of unspecific stimulation through environmental factors and the simultaneous training of a control group that differs in only one task parameter our set-up and procedure met the requirements of new imaging techniques for the study of the influence of a specific cognitive component of spatial-delayed alternation on activity in specific brain regions.

Neural syntax: cell assemblies, synapsembles, and readers

A widely discussed hypothesis in neuroscience is that transiently active ensembles of neurons, known as "cell assemblies," underlie numerous operations of the brain, from encoding memories to reasoning. However, the mechanisms responsible for the formation and disbanding of cell assemblies and temporal evolution of cell assembly sequences are not well understood. I introduce and review three interconnected topics, which could facilitate progress in defining cell assemblies, identifying their neuronal organization, and revealing causal relationships between assembly organization and behavior. First, I hypothesize that cell assemblies are best understood in light of their output product, as detected by "reader-actuator" mechanisms. Second, I suggest that the hierarchical organization of cell assemblies may be regarded as a neural syntax. Third, constituents of the neural syntax are linked together by dynamically changing constellations of synaptic weights ("synapsembles"). The existing support for this tripartite framework is reviewed and strategies for experimental testing of its predictions are discussed.

Arc/Arg3.1 mRNA global expression patterns elicited by memory recall in cerebral cortex differ for remote versus recent spatial memories

The neocortex plays a critical role in the gradual formation and storage of remote declarative memories. Because the circuitry mechanisms of systems-level consolidation are not well understood, the precise cortical sites for memory storage and the nature of enduring memory correlates (mnemonic plasticity) are largely unknown. Detailed maps of neuronal activity underlying recent and remote memory recall highlight brain regions that participate in systems consolidation and constitute putative storage sites, and thus may facilitate detection of mnemonic plasticity. To localize cortical regions involved in the recall of a spatial memory task, we trained rats in a water-maze and then mapped mRNA expression patterns of a neuronal activity marker Arc/Arg3.1 (Arc) upon recall of recent (24 h after training) or remote (1 month after training) memories and compared them with swimming and naive controls. Arc gene expression was significantly more robust 24 h after training compared to 1 month after training. Arc expression diminished in the parietal, cingulate and visual areas, but select segments in the prefrontal, retrosplenial, somatosensory and motor cortical showed similar robust increases in the Arc expression. When Arc expression was compared across select segments of sensory, motor and associative regions within recent and remote memory groups, the overall magnitude and cortical laminar patterns of task-specific Arc expression were similar (stereotypical). Arc mRNA fractions expressed in the upper cortical layers (2/3, 4) increased after both recent and remote recall, while layer 6 fractions decreased only after the recent recall. The data suggest that robust recall of remote memory requires an overall smaller increase in neuronal activity within fewer cortical segments. This activity trend highlights the difficulty in detecting the storage sites and plasticity underlying remote memory. Application of the Arc maps may ameliorate this difficulty.

Distinct roles of rodent orbitofrontal and medial prefrontal cortex in decision making

We investigated how different subregions of rodent prefrontal cortex contribute to value-based decision making, by comparing neural signals related to animal's choice, its outcome, and action value in orbitofrontal cortex (OFC) and medial prefrontal cortex (mPFC) of rats performing a dynamic two-armed bandit task. Neural signals for upcoming action selection arose in the mPFC, including the anterior cingulate cortex, only immediately before the behavioral manifestation of animal's choice, suggesting that rodent prefrontal cortex is not involved in advanced action planning. Both OFC and mPFC conveyed signals related to the animal's past choices and their outcomes over multiple trials, but neural signals for chosen value and reward prediction error were more prevalent in the OFC. Our results suggest that rodent OFC and mPFC serve distinct roles in value-based decision making and that the OFC plays a prominent role in updating the values of outcomes expected from chosen actions.

Role of striatum in updating values of chosen actions

The striatum is thought to play a crucial role in value-based decision making. Although a large body of evidence suggests its involvement in action selection as well as action evaluation, underlying neural processes for these functions of the striatum are largely unknown. To obtain insights on this matter, we simultaneously recorded neuronal activity in the dorsal and ventral striatum of rats performing a dynamic two-armed bandit task, and examined temporal profiles of neural signals related to animal's choice, its outcome, and action value. Whereas significant neural signals for action value were found in both structures before animal's choice of action, signals related to the upcoming choice were relatively weak and began to emerge only in the dorsal striatum approximately 200 ms before the behavioral manifestation of the animal's choice. In contrast, once the animal revealed its choice, signals related to choice and its value increased steeply and persisted until the outcome of animal's choice was revealed, so that some neurons in both structures concurrently conveyed signals related to animal's choice, its outcome, and the value of chosen action. Thus, all the components necessary for updating values of chosen actions were available in the striatum. These results suggest that the striatum not only represents values associated with potential choices before animal's choice of action, but might also update the value of chosen action once its outcome is revealed. In contrast, action selection might take place elsewhere or in the dorsal striatum only immediately before its behavioral manifestation.

Rat prefrontal cortical neurons selectively code strategy switches

Multiple memory systems are distinguished by different sets of neuronal circuits and operating principles optimized to solve different problems across mammalian species (Tulving and Schacter, 1994). When a rat selects an arm in a plus maze, for example, the choice can be guided by distinct neural systems (White and Wise, 1999) that encode different relationships among perceived stimuli, actions, and reward. Thus, egocentric or stimulus-response associations require striatal circuits, whereas spatial or episodic learning requires hippocampal circuits (Packard et al., 1989). Although these memory systems function in parallel (Packard and McGaugh, 1996), they can also interact competitively or synergistically (Kim and Ragozzino, 2005). The neuronal mechanisms that coordinate these multiple memory systems are not fully known, but converging evidence suggests that the prefrontal cortex (PFC) is central. The PFC is crucial for abstract, rule-guided behavior in primates and for switching rapidly between memory strategies in rats. We now report that rat medial PFC neuronal activity predicts switching between hippocampus- and caudate-dependent memory strategies. Prelimbic (PL) and infralimbic (IL) neuronal activity changed as rats switched memory strategies even as the rats performed identical behaviors but did not change when rats learned new contingencies using the same strategy. PL dynamics anticipated learning performance whereas IL lagged, suggesting that the two regions help initiate and establish new strategies, respectively. These neuronal dynamics suggest that the PFC contributes to the coordination of memory strategies by integrating the predictive relationships among stimuli, actions, and reward.

Cortical network functional connectivity in the descent to sleep

Descent into sleep is accompanied by disengagement of the conscious brain from the external world. It follows that this process should be associated with reduced neural activity in regions of the brain known to mediate interaction with the environment. We examined blood oxygen dependent (BOLD) signal functional connectivity using conventional seed-based analyses in 3 primary sensory and 3 association networks as normal young adults transitioned from wakefulness to light sleep while lying immobile in the bore of a magnetic resonance imaging scanner. Functional connectivity was maintained in each network throughout all examined states of arousal. Indeed, correlations within the dorsal attention network modestly but significantly increased during light sleep compared to wakefulness. Moreover, our data suggest that neuronally mediated BOLD signal variance generally increases in light sleep. These results do not support the view that ongoing BOLD fluctuations primarily reflect unconstrained cognition. Rather, accumulating evidence supports the hypothesis that spontaneous BOLD fluctuations reflect processes that maintain the integrity of functional systems in the brain.

Plasticity and memory in the prefrontal cortex

Neuropsychological and neuroimaging studies in humans have shown that the prefrontal cortex (PFC) is involved in long-term memory functioning. In general, the participation of the PFC in long-term memory has been attributed to its role in executive control rather than information storage. Accumulating data from recent animal studies, however, suggest the possible role of the PFC in the storage of long-term memory. In support of this view, there is evidence that various projection systems in the PFC support long-term synaptic plasticity. Recording studies have further demonstrated neural correlates of learning in various animal species. Lastly, behavioral and physiological studies indicate that the PFC is critically involved in memory consolidation, retrieval and extinction processes. These studies then suggest that the PFC is an integral part of the neural network where long-term memory trace is stored and retrieved. Though decisive evidence is still lacking at present, we propose here to assign a term 'control memory' (i.e., memory for top-down control processes) as a new type of memory function for the PFC. This new principle of PFC-long-term memory can help organize existing data and provide novel insights into future empirical studies.

Behavior-dependent short-term assembly dynamics in the medial prefrontal cortex

Although short-term plasticity is believed to play a fundamental role in cortical computation, empirical evidence bearing on its role during behavior is scarce. Here we looked for the signature of short-term plasticity in the fine-timescale spiking relationships of a simultaneously recorded population of physiologically identified pyramidal cells and interneurons, in the medial prefrontal cortex of the rat, in a working memory task. On broader timescales, sequentially organized and transiently active neurons reliably differentiated between different trajectories of the rat in the maze. On finer timescales, putative monosynaptic interactions reflected short-term plasticity in their dynamic and predictable modulation across various aspects of the task, beyond a statistical accounting for the effect of the neurons' co-varying firing rates. Seeking potential mechanisms for such effects, we found evidence for both firing pattern-dependent facilitation and depression, as well as for a supralinear effect of presynaptic coincidence on the firing of postsynaptic targets.

Prefrontal cortex and hippocampus subserve different components of working memory in rats

Both the medial prefrontal cortex (mPFC) and hippocampus are implicated in working memory tasks in rodents. Specifically, it has been hypothesized that the mPFC is primarily engaged in the temporary storage and processing of information lasting from a subsecond to several seconds, while the hippocampal function becomes more critical as the working memory demand extends into longer temporal scales. Although these structures may be engaged in a temporally separable manner, the extent of their contributions in the "informational content" of working memory remains unclear. To investigate this issue, the mPFC and dorsal hippocampus (dHPC) were temporarily inactivated via targeted infusions of the GABA(A) receptor agonist muscimol in rats prior to their performance on a delayed alternation task (DAT), employing an automated figure-eight maze that required the animals to make alternating arm choice responses after 3-, 30-, and 60-sec delays for water reward. We report that inactivation of either the mPFC or dHPC significantly reduced DAT at all delay intervals tested. However, there were key qualitative differences in the behavioral effects. Specifically, mPFC inactivation selectively impaired working memory (i.e., arm choice accuracy) without altering reference memory (i.e., the maze task rule) and arm choice response latencies. In contrast, dHPC inactivation increased both reference memory errors and arm choice response latencies. Moreover, dHPC, but not mPFC, inactivation increased the incidence of successive working memory errors. These results suggest that while both the mPFC and hippocampus are necessarily involved in DAT, they seem to process different informational components associated with the memory task.

Brain and behavior: a task-dependent eye movement study

Recent electrophysiological and behavioral studies have found similarities in the neurology of pursuit and saccadic eye movements. In a previous study on eye movements using closely matched paradigms for pursuit and saccades, we revealed that both exhibit bimodal distributions of latency to predictable (PRD) and randomized (RND) stimuli; however, the latency to each type of stimulus was different, and there was more segregation of latencies in saccades than pursuit (Burke MR, Barnes GR. 2006. Quantitative differences in smooth pursuit and saccadic eye movements in humans. Exp Brain Res. 175(4):596-608). To investigate the brain areas involved in these tasks, and to search for correlates of behavior, we used functional magnetic resonance imaging during equivalent PRD and RND target presentations. In the contrast pursuit > saccades, which reflects velocity-dependent versus position-dependent activities, respectively, we found higher activation in the dorsolateral prefrontal cortex (DLPFC) for pursuit and in the frontopolar region for saccades. In the contrast RND > PRD, which principally reflects activation related to visually driven versus memory-driven responses, respectively, we found a higher sustained level of activation in the frontal eye fields during visually guided eye movements. The reverse contrast revealed higher activity for the memory-guided responses in the supplementary eye fields and the superior parietal lobe. In addition, we found learning-related activation during the PRD condition in visual area V5, the DLPFC, and the cerebellum.

Encoding of action history in the rat ventral striatum

In a dynamic environment, animals need to update information about the rewards expected from their alternative actions continually to make optimal choices for its survival. Because the reward resulting from a given action can be substantially delayed, the process of linking a reward to its causative action would be facilitated by memory signals related to the animal's previous actions. Although the ventral striatum has been proposed to play a key role in updating the information about the rewards expected from specific actions, it is not known whether the signals related to previous actions exist in the ventral striatum. In the present study, we recorded neuronal ensemble activity in the rat ventral striatum during a visual discrimination task and investigated whether neuronal activity in the ventral striatum encoded signals related to animal's previous actions. The results show that many neurons modulated their activity according to the animal's goal choice in the previous trial, indicating that memory signals for previous actions are available in the ventral striatum. In contrast, few neurons conveyed signals on impending goal choice of the animal, suggesting the absence of decision signals in the ventral striatum. Memory signals for previous actions might contribute to the process of updating the estimates of rewards expected from alternative actions in the ventral striatum.

LTP induction modifies functional relationship among hippocampal neurons

To obtain evidence linking long-term potentiation (LTP) and memory, we examined whether LTP induction modifies functional relationship among neurons in the rat hippocampus. In contrast to neurons in low-frequency stimulated or AP5-treated slices, LTP induction altered 'functional connectivity,' as defined by the degree of synchronous firing, among simultaneously recorded neurons in the CA3 region. Interestingly, functional connectivity changed bidirectionally so that the total sum of functional connectivity remained constant. These results demonstrate LTP-induced changes in neuronal functional connectivity and suggest the existence of a normalization mechanism for the total sum of functional connectivity.