The hippocampal sharp wave-ripple in memory retrieval for immediate use and consolidation

Learning offline: memory replay in biological and artificial reinforcement learning

Learning to act in an environment to maximise rewards is among the brain's key functions. This process has often been conceptualised within the framework of reinforcement learning, which has also gained prominence in machine learning and artificial intelligence (AI) as a way to optimise decision making. A common aspect of both biological and machine reinforcement learning is the reactivation of previously experienced episodes, referred to as replay. Replay is important for memory consolidation in biological neural networks and is key to stabilising learning in deep neural networks. Here, we review recent developments concerning the functional roles of replay in the fields of neuroscience and AI. Complementary progress suggests how replay might support learning processes, including generalisation and continual learning, affording opportunities to transfer knowledge across the two fields to advance the understanding of biological and artificial learning and memory.

How do we generalize?

Humans and animals are able to generalize or transfer information from previous experience so that they can behave appropriately in novel situations. What mechanisms-computations, representations, and neural systems-give rise to this remarkable ability? The members of this Generative Adversarial Collaboration (GAC) come from a range of academic backgrounds but are all interested in uncovering the mechanisms of generalization. We started out this GAC with the aim of arbitrating between two alternative conceptual accounts: (1) generalization stems from integration of multiple experiences into summary representations that reflect generalized knowledge, and (2) generalization is computed on-the-fly using separately stored individual memories. Across the course of this collaboration, we found that-despite using different terminology and techniques, and although some of our specific papers may provide evidence one way or the other-we in fact largely agree that both of these broad accounts (as well as several others) are likely valid. We believe that future research and theoretical synthesis across multiple lines of research is necessary to help determine the degree to which different candidate generalization mechanisms may operate simultaneously, operate on different scales, or be employed under distinct conditions. Here, as the first step, we introduce some of these candidate mechanisms and we discuss the issues currently hindering better synthesis of generalization research. Finally, we introduce some of our own research questions that have arisen over the course of this GAC, that we believe would benefit from future collaborative efforts.

Fear conditioning potentiates the hippocampal CA1 commissural pathway in vivo and increases awake phase sleep

The hippocampus is essential for spatial learning and memory. To assess learning we used contextual fear conditioning (cFC), where animals learn to associate a place with aversive events like foot‐shocks. Candidate memory mechanisms for cFC are long‐term potentiation (LTP) and long‐term depression (LTD), but there is little direct evidence of them operating in the hippocampus in vivo following cFC. Also, little is known about the behavioral state changes induced by cFC. To address these issues, we recorded local field potentials in freely behaving mice by stimulating in the left dorsal CA1 region and recording in the right dorsal CA1 region. Synaptic strength in the commissural pathway was monitored by measuring field excitatory postsynaptic potentials (fEPSPs) before and after cFC. After cFC, the commissural pathway's synaptic strength was potentiated. Although recordings occurred during the wake phase of the light/dark cycle, the mice slept more in the post‐conditioning period than in the pre‐conditioning period. Relative to awake periods, in non‐rapid eye movement (NREM) sleep the fEPSPs were larger in both pre‐ and post‐conditioning periods. We also found a significant negative correlation between the animal's speed and fEPSP size. Therefore, to avoid confounds in the fEFSP potentiation estimates, we controlled for speed‐related and sleep‐related fEPSP changes and still found that cFC induced long‐term potentiation, but no significant long‐term depression. Synaptic strength changes were not found in the control group that simply explored the fear‐conditioning chamber, indicating that exploration of the novel place did not produce the measurable effects caused by cFC. These results show that following cFC, the CA1 commissural pathway is potentiated, likely contributing to the functional integration of the left and right hippocampi in fear memory consolidation. In addition, the cFC paradigm produces significant changes in an animal's behavioral state, which are observable as proximal changes in sleep patterns.

Replay in minds and machines

Experience-related brain activity patterns reactivate during sleep, wakeful rest, and brief pauses from active behavior. In parallel, machine learning research has found that experience replay can lead to substantial performance improvements in artificial agents. Together, these lines of research suggest replay has a variety of computational benefits for decision-making and learning. Here, we provide an overview of putative computational functions of replay as suggested by machine learning and neuroscientific research. We show that replay can lead to faster learning, less forgetting, reorganization or augmentation of experiences, and support planning and generalization. In addition, we highlight the benefits of reactivating abstracted internal representations rather than veridical memories, and discuss how replay could provide a mechanism to build internal representations that improve learning and decision-making.

Impaired neural replay of inferred relationships in schizophrenia

An ability to build structured mental maps of the world underpins our capacity to imagine relationships between objects that extend beyond experience. In rodents, such representations are supported by sequential place cell reactivations during rest, known as replay. Schizophrenia is proposed to reflect a compromise in structured mental representations, with animal models reporting abnormalities in hippocampal replay and associated ripple activity during rest. Here, utilizing magnetoencephalography (MEG), we tasked patients with schizophrenia and control participants to infer unobserved relationships between objects by reorganizing visual experiences containing these objects. During a post-task rest session, controls exhibited fast spontaneous neural reactivation of presented objects that replayed inferred relationships. Replay was coincident with increased ripple power in hippocampus. Patients showed both reduced replay and augmented ripple power relative to controls, convergent with findings in animal models. These abnormalities are linked to impairments in behavioral acquisition and subsequent neural representation of task structure.

Aperiodic sleep networks promote memory consolidation

Hierarchical synchronization of sleep oscillations establishes communication pathways to support memory reactivation, transfer, and consolidation. From an information-theoretical perspective, oscillations constitute highly structured network states that provide limited information-coding capacity. Recent findings indicate that sleep oscillations occur in transient bursts that are interleaved with aperiodic network states, which were previously considered to be random noise. We argue that aperiodic activity exhibits unique and variable spatiotemporal patterns, providing an ideal information-rich neurophysiological substrate for imprinting new mnemonic patterns onto existing circuits. We discuss novel avenues in conceptualizing and quantifying aperiodic network states during sleep to further understand their relevance and interplay with sleep oscillations in support of memory consolidation.

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.

Memory consolidation as an adaptive process

We rely on our long-term memories to guide future behaviors, making it adaptive to prioritize the retention of goal-relevant, salient information in memory. In this review, we discuss findings from rodent and human research to demonstrate that active processes during post-encoding consolidation support the selective stabilization of recent experience into adaptive, long-term memories. Building upon literatures focused on dynamics at the cellular level, we highlight that consolidation also transforms memories at the systems level to support future goal-relevant behavior, resulting in more generalized memory traces in the brain and behavior. We synthesize previous literatures spanning animal research, human cognitive neuroscience, and cognitive psychology to propose an integrative framework for adaptive consolidation by which goal-relevant memoranda are "tagged" for subsequent consolidation, resulting in selective transformations to the structure of memories that support flexible, goal-relevant behaviors.

Isoflurane Suppresses Hippocampal High-frequency Ripples by Differentially Modulating Pyramidal Neurons and Interneurons in Mice

BACKGROUND

Isoflurane can induce anterograde amnesia. Hippocampal ripples are high-frequency oscillatory events occurring in the local field potentials of cornu ammonis 1 involved in memory processes. The authors hypothesized that isoflurane suppresses hippocampal ripples at a subanesthetic concentration by modulating the excitability of cornu ammonis 1 neurons.

METHODS

The potencies of isoflurane for memory impairment and anesthesia were measured in mice. Hippocampal ripples were measured by placing recording electrodes in the cornu ammonis 1. Effects of isoflurane on the excitability of hippocampal pyramidal neurons and interneurons were measured. A simulation model of ripples based on the firing frequency of hippocampal cornu ammonis 1 neurons was used to validate the effects of isoflurane on neuronal excitability in vitro and on ripples in vivo.

RESULTS

Isoflurane at 0.5%, which did not induce loss of righting reflex, impaired hippocampus-dependent fear memory by 97.4 ± 3.1% (mean ± SD; n = 14; P < 0.001). Isoflurane at 0.5% reduced ripple amplitude (38 ± 13 vs. 42 ± 13 μV; n = 9; P = 0.003), rate (462 ± 66 vs. 538 ± 81 spikes/min; n = 9; P = 0.002) and duration (36 ± 5 vs. 48 ± 9 ms; n = 9; P < 0.001) and increased the interarrival time (78 ± 7 vs. 69 ± 6 ms; n = 9; P < 0.001) and frequency (148.2 ± 3.9 vs. 145.0 ± 2.9 Hz; n = 9; P = 0.001). Isoflurane at the same concentration depressed action potential frequency in fast-spiking interneurons while slightly enhancing action potential frequency in cornu ammonis 1 pyramidal neurons. The simulated effects of isoflurane on hippocampal ripples were comparable to recordings in vivo.

CONCLUSIONS

The authors' results suggest that a subanesthetic concentration of isoflurane can suppress hippocampal ripples by differentially modulating the excitability of pyramidal neurons and interneurons, which may contribute to its amnestic action.

EDITOR’S PERSPECTIVE

Hippocampal ripples and their coordinated dialogue with the default mode network during recent and remote recollection

Hippocampal ripples are prominent synchronization events generated by hippocampal neuronal assemblies. To date, ripples have been primarily associated with navigational memory in rodents and short-term episodic recollections in humans. Here, we uncover different profiles of ripple activity in the human hippocampus during the retrieval of recent and remote autobiographical events and semantic facts. We found that the ripple rate increased significantly before reported recall compared to control conditions. Patterns of ripple activity across multiple hippocampal sites demonstrated remarkable specificity for memory type. Intriguingly, these ripple patterns revealed a semantization dimension, in which patterns associated with autobiographical contents become similar to those of semantic memory as a function of memory age. Finally, widely distributed sites across the neocortex exhibited ripple-coupled activations during recollection, with the strongest activation found within the default mode network. Our results thus reveal a key role for hippocampal ripples in orchestrating hippocampal-cortical communication across large-scale networks involved in conscious recollection.

Normal and Abnormal Sharp Wave Ripples in the Hippocampal-Entorhinal Cortex System: Implications for Memory Consolidation, Alzheimer's Disease, and Temporal Lobe Epilepsy

The appearance of hippocampal sharp wave ripples (SWRs) is an electrophysiological biomarker for episodic memory encoding and behavioral planning. Disturbed SWRs are considered a sign of neural network dysfunction that may provide insights into the structural connectivity changes associated with cognitive impairment in early-stage Alzheimer's disease (AD) and temporal lobe epilepsy (TLE). SWRs originating from hippocampus have been extensively studied during spatial navigation in rodents, and more recent studies have investigated SWRs in the hippocampal-entorhinal cortex (HPC-EC) system during a variety of other memory-guided behaviors. Understanding how SWR disruption impairs memory function, especially episodic memory, could aid in the development of more efficacious therapeutics for AD and TLE. In this review, we first provide an overview of the reciprocal association between AD and TLE, and then focus on the functions of HPC-EC system SWRs in episodic memory consolidation. It is posited that these waveforms reflect rapid network interactions among excitatory projection neurons and local interneurons and that these waves may contribute to synaptic plasticity underlying memory consolidation. Further, SWRs appear altered or ectopic in AD and TLE. These waveforms may thus provide clues to understanding disease pathogenesis and may even serve as biomarkers for early-stage disease progression and treatment response.

Sleep in Neurologic Disorders

Sleep is a complex brain state with fundamental relevance for cognitive functions, synaptic plasticity, brain resilience, and autonomic balance. Sleep pathologies may interfere with cerebral circuit organization, leading to negative consequences and favoring the development of neurologic disorders. Conversely, the latter can interfere with sleep functions. Accordingly, assessment of sleep quality is always recommended in the diagnosis of patients with neurologic disorders and during neurorehabilitation programs. This review investigates the complex interplay between sleep and brain pathologies, focusing on diseases in which the association with sleep disturbances is commonly overlooked and whereby major benefits may derive from their proper management.

Differential effect of sleep deprivation on place cell representations, sleep architecture, and memory in young and old mice

Poor sleep quality is associated with age-related cognitive decline, and whether reversal of these alterations is possible is unknown. In this study, we report how sleep deprivation (SD) affects hippocampal representations, sleep patterns, and memory in young and old mice. After training in a hippocampus-dependent object-place recognition (OPR) task, control animals sleep ad libitum, although experimental animals undergo 5 h of SD, followed by recovery sleep. Young controls and old SD mice exhibit successful OPR memory, whereas young SD and old control mice are impaired. Successful performance is associated with two cellular phenotypes: (1) "context" cells, which remain stable throughout training and testing, and (2) "object configuration" cells, which remap when objects are introduced to the context and during testing. Additionally, effective memory correlates with spindle counts during non-rapid eye movement (NREM)/rapid eye movement (REM) sigma transitions. These results suggest SD may serve to ameliorate age-related memory deficits and allow hippocampal representations to adapt to changing environments.

Disrupting the medial prefrontal cortex with designer receptors exclusively activated by designer drug alters hippocampal sharp-wave ripples and their associated cognitive processes

The hippocampus and medial prefrontal cortex (mPFC) interact during a myriad of cognitive processes including decision-making and long-term memory consolidation. Exactly how the mPFC and hippocampus interact during goal-directed decision-making remains to be fully elucidated. During periods of rest, bursts of high-frequency oscillations, termed sharp-wave ripple (SWR), appear in the local field potential. Impairing SWRs on the maze or during post-learning rest can interfere with memory-guided decision-making and memory consolidation. We hypothesize that the hippocampus and mPFC bidirectionally interact during SWRs to support memory consolidation and decision-making. Rats were trained on the neuroeconomic spatial decision-making task, Restaurant Row, to make serial stay-skip decisions where the amount of effort (delay to reward) varied upon entry to each restaurant. Hippocampal cells and SWRs were recorded in rats with the mPFC transduced with inhibitory DREADDs. We found that disrupting the mPFC impaired consolidating SWRs in the hippocampus. Hippocampal SWR rates depended on the internalized value of the reward (derived from individual flavor preferences), a parameter important in decision-making, and disrupting the mPFC changed this relationship. Additionally, we found a dissociation between SWRs that occurred while rats were on the maze dependent upon whether those SWRs occurred while the rat was anticipating food reward or during post-reward consumption.

Enhancing myelin renewal reverses cognitive dysfunction in a murine model of Alzheimer's disease

Severe cognitive decline is a hallmark of Alzheimer's disease (AD). In addition to gray matter loss, significant white matter pathology has been identified in AD patients. Here, we characterized the dynamics of myelin generation and loss in the APP/PS1 mouse model of AD. Unexpectedly, we observed a dramatic increase in the rate of new myelin formation in APP/PS1 mice, reminiscent of the robust oligodendroglial response to demyelination. Despite this increase, overall levels of myelination are decreased in the cortex and hippocampus of APP/PS1 mice and postmortem AD tissue. Genetically or pharmacologically enhancing myelin renewal, by oligodendroglial deletion of the muscarinic M1 receptor or systemic administration of the pro-myelinating drug clemastine, improved the performance of APP/PS1 mice in memory-related tasks and increased hippocampal sharp wave ripples. Taken together, these results demonstrate the potential of enhancing myelination as a therapeutic strategy to alleviate AD-related cognitive impairment.

Application of a convolutional neural network for fully-automated detection of spike ripples in the scalp electroencephalogram

BACKGROUND

A reliable biomarker to identify cortical tissue responsible for generating epileptic seizures is required to guide prognosis and treatment in epilepsy. Combined spike ripple events are a promising biomarker for epileptogenic tissue that currently require expert review for accurate identification. This expert review is time consuming and subjective, limiting reproducibility and high-throughput applications.

NEW METHOD

To address this limitation, we develop a fully-automated method for spike ripple detection. The method consists of a convolutional neural network trained to compute the probability that a spectrogram image contains a spike ripple.

RESULTS

We validate the proposed spike ripple detector on expert-labeled data and show that this detector accurately separates subjects with low and high seizure risks.

COMPARISON WITH EXISTING METHOD

The proposed method performs as well as existing methods that require manual validation of candidate spike ripple events. The introduction of a fully automated method reduces subjectivity and increases rigor and reproducibility of this epilepsy biomarker.

CONCLUSION

We introduce and validate a fully-automated spike ripple detector to support utilization of this epilepsy biomarker in clinical and translational work.

Stability of ripple events during task engagement in human hippocampus

High-frequency activity bursts in the hippocampus, known as ripples, are thought to support memory consolidation during “offline” states, such as sleep. Recently, human hippocampal ripples have been observed during “online” episodic memory tasks. It remains unclear whether similar ripple activity occurs during other cognitive states, including different types of episodic memory. However, identifying genuine ripple events in the human hippocampus is challenging. To address these questions, spectro-temporal ripple identification was applied to human hippocampal recordings across a variety of cognitive tasks. Overall, ripple attributes were stable across tasks of visual perception and associative memory, with mean rates lower than offline states of rest and sleep. In contrast, while more complex visual attention tasks did not modulate ripple attributes, rates were enhanced for more complex autobiographical memory conditions. Therefore, hippocampal ripples reliably occur across cognitive states but are specifically enhanced during offline states and complex memory processes, consistent with a role in consolidation.

Hippocampal ripples are high-frequency activity bursts proposed to support “offline” memory consolidation. Chen et al. identify that human hippocampal ripples occur with stable properties across tasks of visual perception and associative memory but are enhanced for autobiographical memory retrieval and non-REM sleep, supporting their “online” role in establishing and strengthening memory traces.

Endogenous memory reactivation during sleep in humans is clocked by slow oscillation-spindle complexes

Sleep is thought to support memory consolidation via reactivation of prior experiences, with particular electrophysiological sleep signatures (slow oscillations (SOs) and sleep spindles) gating the information flow between relevant brain areas. However, empirical evidence for a role of endogenous memory reactivation (i.e., without experimentally delivered memory cues) for consolidation in humans is lacking. Here, we devised a paradigm in which participants acquired associative memories before taking a nap. Multivariate decoding was then used to capture endogenous memory reactivation during non-rapid eye movement (NREM) sleep in surface EEG recordings. Our results reveal reactivation of learning material during SO-spindle complexes, with the precision of SO-spindle coupling predicting reactivation strength. Critically, reactivation strength (i.e. classifier evidence in favor of the previously studied stimulus category) in turn predicts the level of consolidation across participants. These results elucidate the memory function of sleep in humans and emphasize the importance of SOs and spindles in clocking endogenous consolidation processes.

Net decrease in spine-surface GluA1-containing AMPA receptors after post-learning sleep in the adult mouse cortex

The mechanisms by which sleep benefits learning and memory remain unclear. Sleep may further strengthen the synapses potentiated by learning or promote broad synaptic weakening while protecting the newly potentiated synapses. We tested these ideas by combining a motor task whose consolidation is sleep-dependent, a marker of synaptic AMPA receptor plasticity, and repeated two-photon imaging to track hundreds of spines in vivo with single spine resolution. In mouse motor cortex, sleep leads to an overall net decrease in spine-surface GluA1-containing AMPA receptors, both before and after learning. Molecular changes in single spines during post-learning sleep are correlated with changes in performance after sleep. The spines in which learning leads to the largest increase in GluA1 expression have a relative advantage after post-learning sleep compared to sleep deprivation, because sleep weakens all remaining spines. These results are obtained in adult mice, showing that sleep-dependent synaptic down-selection also benefits the mature brain.

Microcircuit mechanisms for the generation of sharp-wave ripples in the basolateral amygdala: A role for chandelier interneurons

Synchronized activity in neural circuits, detected as oscillations in the extracellular field potential, has been associated with learning and memory. Neural circuits in the basolateral amygdala (BLA), a mid-temporal lobe structure, generate oscillations in specific frequency bands to mediate emotional memory functions. However, how BLA circuits generate oscillations in distinct frequency bands is not known. Of these, sharp-waves (SWs) are repetitive, brief transitions that contain a low-frequency (<20 Hz) envelope, often coupled with ripples (100–300 Hz), have been associated with memory consolidation. Here, we show that SWs are retained in the BLA ex vivo and generated by local circuits. We demonstrate that an action potential in a chandelier interneuron is sufficient to initiate SWs through local circuits. Using a physiologically constrained model, we show that microcircuits organized as chandelier-interneuron-driven modules reproduce SWs and associated cellular events, revealing a functional role for chandelier interneurons and microcircuits for SW generation.

Perumal et al. investigate circuits that generate network oscillations called sharp waves (SWs) in the basolateral amygdala. They show that discharge in a chandelier interneuron can initiate SW oscillations—a network activity associated with memory consolidation. They develop a network model with chandelier-interneuron-driven modular microcircuits for SW generation.

Subthreshold membrane potential dynamics of posterior parietal cortical neurons coupled with hippocampal ripples

During behavioral states of immobility, sleep, and anesthesia, the hippocampus generates high-frequency oscillations called ripples. Ripples occur simultaneously with synchronous neuronal activity in the neocortex, known as slow waves, and contribute to memory consolidation. During these ripples, various neocortical regions exhibit modulations in spike rates and local field activity irrespective of whether they receive direct synaptic inputs from the hippocampus. However, little is known about the subthreshold dynamics of the membrane potentials of neocortical neurons during ripples. We patch-clamped layer 2/3 pyramidal cells in the posterior parietal cortex (PPC), a neocortical region that is involved in allocentric spatial representation of behavioral exploration and sequential series of relevant action potentials during ripples. We simultaneously monitored the membrane potentials of post hoc-identified PPC neurons and the local field potentials of the hippocampus in anesthetized mice. More than 50% of the recorded PPC neurons exhibited significant depolarizations and/or hyperpolarizations during ripples. Histological inspections of the recorded neurons revealed that the ripple-modulated PPC neurons were distributed in the PPC in a spatially non-biased fashion. These results suggest that hippocampal ripples are widely but selectively associated with the subthreshold dynamics of the membrane potentials of PPC neurons even though there is no monosynaptic connectivity between the hippocampus and the PPC.

Prefrontal synaptic activation during hippocampal memory reactivation

Cooperative reactivation of hippocampal and prefrontal neurons is considered crucial for mnemonic processes. To directly record synaptic substances supporting the interregional interactions, we develop concurrent spike recordings of hippocampal neuronal ensembles and whole-cell patch-clamp recordings of medial prefrontal neurons in awake rats. We find that medial prefrontal neurons depolarize when hippocampal neurons synchronize. The depolarization in medial prefrontal neurons is larger when hippocampal place cells that encoded overlapping place fields and place cells that encoded a novel environment are synchronously reactivated. Our results suggest a functional circuit-synapse association that enables prefrontal neurons to read out specific memory traces from the hippocampus.

Effects of Spatial Memory Processing on Hippocampal Ripples

Human High-Frequency-Oscillations (HFO) in the ripple band are oscillatory brain activity in the frequency range between 80 and 250 Hz. HFOs may comprise different subgroups that either play a role in physiologic or pathologic brain functions. An exact differentiation between physiologic and pathologic HFOs would help elucidate their relevance for cognitive and epileptogenic brain mechanisms, but the criteria for differentiating between physiologic and pathologic HFOs remain controversial. In particular, the separation of pathologic HFOs from physiologic HFOs could improve the identification of epileptogenic brain regions during the pre-surgical evaluation of epilepsy patients. In this study, we performed intracranial electroencephalography recordings from the hippocampus of epilepsy patients before, during, and after the patients completed a spatial navigation task. We isolated hippocampal ripples from the recordings and categorized the ripples into the putative pathologic group iesRipples, when they coincided with interictal spikes, and the putative physiologic group isolRipples, when they did not coincide with interictal spikes. We found that the occurrence of isolRipples significantly decreased during the task as compared to periods before and after the task. The rate of iesRipples was not modulated by the task. In patients who completed the spatial navigation task on two consecutive days, we furthermore examined the occurrence of ripples in the intervening night. We found that the rate of ripples that coincided with sleep spindles and were therefore putatively physiologic correlated with the performance improvement on the spatial navigation task, whereas the rate of all ripples did not show this relationship. Together, our results suggest that the differentiation of HFOs into putative physiologic and pathologic subgroups may help identify their role for spatial memory and memory consolidation processes. Conversely, excluding putative physiologic HFOs from putative pathologic HFOs may improve the HFO-based identification of epileptogenic brain regions in future studies.

The Best Laid Plans: Computational Principles of Anterior Cingulate Cortex

Despite continual debate for the past 30 years about the function of anterior cingulate cortex (ACC), its key contribution to neurocognition remains unknown. However, recent computational modeling work has provided insight into this question. Here we review computational models that illustrate three core principles of ACC function, related to hierarchy, world models, and cost. We also discuss four constraints on the neural implementation of these principles, related to modularity, binding, encoding, and learning and regulation. These observations suggest a role for ACC in hierarchical model-based hierarchical reinforcement learning (HMB-HRL), which instantiates a mechanism motivating the execution of high-level plans.

The evolving view of replay and its functions in wake and sleep

The term hippocampal replay originally referred to the temporally compressed reinstantiation, during rest, of sequential neural activity observed during prior active wake. Since its description in the 1990s, hippocampal replay has often been viewed as the key mechanism by which a memory trace is repeatedly rehearsed at high speeds during sleep and gradually transferred to neocortical circuits. However, the methods used to measure the occurrence of replay remain debated, and it is now clear that the underlying neural events are considerably more complicated than the traditional narratives had suggested. “Replay-like” activity happens during wake, can play out in reverse order, may represent trajectories never taken by the animal, and may have additional functions beyond memory consolidation, from learning values and solving the problem of credit assignment to decision-making and planning. Still, we know little about the role of replay in cognition, and to what extent it differs between wake and sleep. This may soon change, however, because decades-long efforts to explain replay in terms of reinforcement learning (RL) have started to yield testable predictions and possible explanations for a diverse set of observations. Here, we (1) survey the diverse features of replay, focusing especially on the latest findings; (2) discuss recent attempts at unifying disparate experimental results and putatively different cognitive functions under the banner of RL; (3) discuss methodological issues and theoretical biases that impede progress or may warrant a partial revaluation of the current literature, and finally; (4) highlight areas of considerable uncertainty and promising avenues of inquiry.

Alterations of Neuronal Dynamics as a Mechanism for Cognitive Impairment in Epilepsy

Epilepsy is commonly associated with cognitive and behavioral deficits that dramatically affect the quality of life of patients. In order to identify novel therapeutic strategies aimed at reducing these deficits, it is critical first to understand the mechanisms leading to cognitive impairments in epilepsy. Traditionally, seizures and epileptiform activity in addition to neuronal injury have been considered to be the most significant contributors to cognitive dysfunction. In this review we however highlight the role of a new mechanism: alterations of neuronal dynamics, i.e. the timing at which neurons and networks receive and process neural information. These alterations, caused by the underlying etiologies of epilepsy syndromes, are observed in both animal models and patients in the form of abnormal oscillation patterns in unit firing, local field potentials, and electroencephalogram (EEG). Evidence suggests that such mechanisms significantly contribute to cognitive impairment in epilepsy, independently of seizures and interictal epileptiform activity. Therefore, therapeutic strategies directly targeting neuronal dynamics rather than seizure reduction may significantly benefit the quality of life of patients.

Scaling of Network Excitability and Inhibition may Contribute to the Septotemporal Differentiation of Sharp Waves-Ripples in Rat Hippocampus In Vitro

The functional organization of the hippocampus along its longitudinal (septotemporal or dorsoventral) axis is conspicuously heterogeneous. This functional diversification includes the activity of sharp wave and ripples (SPW-Rs), a complex intrinsic network pattern involved in memory consolidation. In this study, using transverse slices from the ventral and the dorsal rat hippocampus and recordings of CA1 field potentials we studied the development of SPW-Rs and possible changes in local network excitability and inhibition, during in vitro maintenance of the hippocampal tissue. We found that SPW-Rs develop gradually in terms of magnitude and rate of occurrence in the ventral hippocampus. On the contrary, neither the magnitude nor the rate of occurrence significantly changed in dorsal hippocampal slices during their in vitro maintenance. The development of SPW-Rs was accompanied by an increase in local network excitability more in the ventral than in the dorsal hippocampus, and an increase in local network inhibition in the ventral hippocampus only. Furthermore, the amplitude of SPWs positively correlated with the level of maximum excitation of the local neuronal network in both segments of the hippocampus, and the local network excitability and inhibition in the ventral but not the dorsal hippocampus. Blockade of α5 subunit-containing GABA_A receptor by L-655,708 significantly reduced the rate of occurrence of SPWs and enhanced the probability of their generation in the form of clusters in the ventral hippocampus without affecting activity in the dorsal hippocampus. The present evidence suggests that a dynamic upregulation of excitation and inhibition in the local neuronal network may significantly contribute to the generation of SPW-Rs, particularly in the ventral hippocampus.

Detrimental impacts of mixed-ion radiation on nervous system function

Galactic cosmic radiation (GCR), composed of highly energetic and fully ionized atomic nuclei, produces diverse deleterious effects on the body. In researching the neurological risks of GCR exposures, including during human spaceflight, various ground-based single-ion GCR irradiation paradigms induce differential disruptions of cellular activity and overall behavior. However, it remains less clear how irradiation comprising a mix of multiple ions, more accurately recapitulating the space GCR environment, impacts the central nervous system. We therefore examined how mixed-ion GCR irradiation (two similar 5-6 beam combinations of protons, helium, oxygen, silicon and iron ions) influenced neuronal connectivity, functional generation of activity within neural circuits and cognitive behavior in mice. In electrophysiological recordings we find that space-relevant doses of mixed-ion GCR preferentially alter hippocampal inhibitory neurotransmission and produce related disruptions in the local field potentials of hippocampal oscillations. Such underlying perturbation in hippocampal network activity correspond with perturbed learning, memory and anxiety behavior.

Cross-species neuroscience: closing the explanatory gap

Neuroscience has seen substantial development in non-invasive methods available for investigating the living human brain. However, these tools are limited to coarse macroscopic measures of neural activity that aggregate the diverse responses of thousands of cells. To access neural activity at the cellular and circuit level, researchers instead rely on invasive recordings in animals. Recent advances in invasive methods now permit large-scale recording and circuit-level manipulations with exquisite spatio-temporal precision. Yet, there has been limited progress in relating these microcircuit measures to complex cognition and behaviour observed in humans. Contemporary neuroscience thus faces an explanatory gap between macroscopic descriptions of the human brain and microscopic descriptions in animal models. To close the explanatory gap, we propose adopting a cross-species approach. Despite dramatic differences in the size of mammalian brains, this approach is broadly justified by preserved homology. Here, we outline a three-armed approach for effective cross-species investigation that highlights the need to translate different measures of neural activity into a common space. We discuss how a cross-species approach has the potential to transform basic neuroscience while also benefiting neuropsychiatric drug development where clinical translation has, to date, seen minimal success. This article is part of the theme issue 'Key relationships between non-invasive functional neuroimaging and the underlying neuronal activity'.

The brain in motion: How ensemble fluidity drives memory-updating and flexibility

While memories are often thought of as flashbacks to a previous experience, they do not simply conserve veridical representations of the past but must continually integrate new information to ensure survival in dynamic environments. Therefore, 'drift' in neural firing patterns, typically construed as disruptive 'instability' or an undesirable consequence of noise, may actually be useful for updating memories. In our view, continual modifications in memory representations reconcile classical theories of stable memory traces with neural drift. Here we review how memory representations are updated through dynamic recruitment of neuronal ensembles on the basis of excitability and functional connectivity at the time of learning. Overall, we emphasize the importance of considering memories not as static entities, but instead as flexible network states that reactivate and evolve across time and experience.

Neuromodulation of the mind-wandering brain state: the interaction between neuromodulatory tone, sharp wave-ripples and spontaneous thought

Mind-wandering has become a captivating topic for cognitive neuroscientists. By now, it is reasonably well described in terms of its phenomenology and the large-scale neural networks that support it. However, we know very little about what neurobiological mechanisms trigger a mind-wandering episode and sustain the mind-wandering brain state. Here, we focus on the role of ascending neuromodulatory systems (i.e. acetylcholine, noradrenaline, serotonin and dopamine) in shaping mind-wandering. We advance the hypothesis that the hippocampal sharp wave-ripple (SWR) is a compelling candidate for a brain state that can trigger mind-wandering episodes. This hippocampal rhythm, which occurs spontaneously in quiescent behavioural states, is capable of propagating widespread activity in the default network and is functionally associated with recollective, associative, imagination and simulation processes. The occurrence of the SWR is heavily dependent on hippocampal neuromodulatory tone. We describe how the interplay of neuromodulators may promote the hippocampal SWR and trigger mind-wandering episodes. We then identify the global neuromodulatory signatures that shape the evolution of the mind-wandering brain state. Under our proposed framework, mind-wandering emerges due to the interplay between neuromodulatory systems that influence the transitions between brain states, which either facilitate, or impede, a wandering mind. This article is part of the theme issue 'Offline perception: voluntary and spontaneous perceptual experiences without matching external stimulation'.

Point process models for sequence detection in high-dimensional neural spike trains

Sparse sequences of neural spikes are posited to underlie aspects of working memory [1], motor production [2], and learning [3, 4]. Discovering these sequences in an unsupervised manner is a longstanding problem in statistical neuroscience [5-7]. Promising recent work [4, 8] utilized a convolutive nonnegative matrix factorization model [9] to tackle this challenge. However, this model requires spike times to be discretized, utilizes a sub-optimal least-squares criterion, and does not provide uncertainty estimates for model predictions or estimated parameters. We address each of these shortcomings by developing a point process model that characterizes fine-scale sequences at the level of individual spikes and represents sequence occurrences as a small number of marked events in continuous time. This ultra-sparse representation of sequence events opens new possibilities for spike train modeling. For example, we introduce learnable time warping parameters to model sequences of varying duration, which have been experimentally observed in neural circuits [10]. We demonstrate these advantages on experimental recordings from songbird higher vocal center and rodent hippocampus.

Tracing a Path for Memory in the Hippocampus

The hippocampal activity supporting trace fear conditioning has long been mysterious, but a leading hypothesis posits "time-cell"-like sequential patterns. In this issue of Neuron, Ahmed et al. (2020) present new data suggesting that, at least during the first session of learning, a subset of neurons coalesce to selectively encode the task but without expressing reliable sequences.

Neuronal Computation Underlying Inferential Reasoning in Humans and Mice

Every day we make decisions critical for adaptation and survival. We repeat actions with known consequences. But we also draw on loosely related events to infer and imagine the outcome of entirely novel choices. These inferential decisions are thought to engage a number of brain regions; however, the underlying neuronal computation remains unknown. Here, we use a multi-day cross-species approach in humans and mice to report the functional anatomy and neuronal computation underlying inferential decisions. We show that during successful inference, the mammalian brain uses a hippocampal prospective code to forecast temporally structured learned associations. Moreover, during resting behavior, coactivation of hippocampal cells in sharp-wave/ripples represent inferred relationships that include reward, thereby "joining-the-dots" between events that have not been observed together but lead to profitable outcomes. Computing mnemonic links in this manner may provide an important mechanism to build a cognitive map that stretches beyond direct experience, thus supporting flexible behavior.

Long-Term Characterization of Hippocampal Remapping during Contextual Fear Acquisition and Extinction

Hippocampal CA1 place cell spatial maps are known to alter their firing properties in response to contextual fear conditioning, a process called "remapping." In the present study, we use chronic calcium imaging to examine remapping during fear retrieval and extinction of an inhibitory avoidance task in mice of both sexes over an extended period of time and with thousands of neurons. We demonstrate that hippocampal ensembles encode space at a finer scale following fear memory acquisition. This effect is strongest near the shock grid. We also characterize the long-term effects of shock on place cell ensemble stability, demonstrating that shock delivery induces several days of high fear and low between-session place field stability, followed by a new, stable spatial representation that appears after fear extinction. Finally, we identify a novel group of CA1 neurons that robustly encode freeze behavior independently from spatial location. Thus, following fear acquisition, hippocampal CA1 place cells sharpen their spatial tuning and dynamically change spatial encoding stability throughout fear learning and extinction.SIGNIFICANCE STATEMENT The hippocampus contains place cells that encode an animal's location. This spatial code updates, or remaps, in response to environmental change. It is known that contextual fear can induce such remapping; in the present study, we use chronic calcium imaging to examine inhibitory avoidance-induced remapping over an extended period of time and with thousands of neurons and demonstrate that hippocampal ensembles encode space at a finer scale following electric shock, an effect which is enhanced by threat proximity. We also identify a novel group of freeze behavior-activated neurons. These results suggest that, more than merely shuffling their spatial code following threat exposure, place cells enhance their spatial coding with the possible benefit of improved threat localization.

Early Hippocampal Sharp-Wave Ripple Deficits Predict Later Learning and Memory Impairments in an Alzheimer's Disease Mouse Model

Alzheimer’s disease (AD) is characterized by progressive memory loss, and there is a pressing need to identify early pathophysiological alterations that predict subsequent memory impairment. Hippocampal sharp-wave ripples (SWRs)—electrophysiological signatures of memory reactivation in the hippocampus—are a compelling candidate for this purpose. Mouse models of AD show reductions in both SWR abundance and associated slow gamma (SG) power during aging, but these alterations have yet to be directly linked to memory impairments. In aged apolipoprotein E4 knockin (apoE4-KI) mice—a model of the major genetic risk factor for AD—we find that reduced SWR abundance and associated CA3 SG power predicted spatial memory impairments measured 1–2 months later. Importantly, SWR-associated CA3 SG power reduction in young apoE4-KI mice also predicted spatial memory deficits measured 10 months later. These results establish features of SWRs as potential functional biomarkers of memory impairment in AD.

Currently, there are no functional biomarkers that can predict progression to Alzheimer’s disease before cognitive decline begins. Jones et al. demonstrate that sharp-wave ripple and associated slow gamma deficits predict memory impairments in aged apoE4 mice. Slow gamma deficits in young apoE4 mice predict memory impairment onset 10+ months later.

An Integrated Index: Engrams, Place Cells, and Hippocampal Memory

The hippocampus and its extended network contribute to encoding and recall of episodic experiences. Drawing from recent anatomical, physiological, and behavioral studies, we propose that hippocampal engrams function as indices to mediate memory recall. We broaden this idea to discuss potential relationships between engrams and hippocampal place cells, as well as the molecular, cellular, physiological, and circuit determinants of engrams that permit flexible routing of information to intra- and extrahippocampal circuits for reinstatement, a feature critical to memory indexing. Incorporating indexing into frameworks of memory function opens new avenues of study and even therapies for hippocampal dysfunction.

Effect of Electroacupuncture at GV20 on Sleep Deprivation-Induced Depression-Like Behavior in Mice

Accumulating evidence suggests that sleep deprivation (S-Dep) is a critical risk factor for depression. Electroacupuncture (EA) treatment has been reported to ameliorate posttraumatic stress disorder- (PSTD-) like behavior and enhance hippocampal neurogenesis. However, whether EA treatment has any beneficial effect on S-Dep-induced depression-like behavior is still unknown. In the present study, we focused on whether EA at Baihui (GV20) can ameliorate the deterioration effect of S-Dep in mice. Mice were randomly divided into normal, S-Dep, S-Dep + EA, and S-Dep + sham EA groups. Cognitive behavior test and in vitro assay were performed separately to avoid the influence of behavior test on synaptic transmission and protein expression. Depression-like behaviors were determined by forced swimming test (FST), tail suspension test (TST), and Morris water maze (MWM). Neurogenesis was identified by BrdU, DCX, and NeuN immunofluorescence staining. In vitro long-term potentiation was detected by high frequency stimulation (HFS) at Schaffer collateral-CA1 synapses in hippocampal slices. Brain-derived neurotropic factor (BDNF) and tropomyosin receptor kinase B (TrkB) protein expression level were assayed by western blot. Our results indicated that D-Sep mice demonstrated depression-like behaviors determined by prolonged immobility duration in FST and TST; D-Sep mice also manifested spatial memory retention deficit in MWM. Furthermore, EA treatment ameliorated D-Sep-induced depression-like behaviors and spatial memory retention deficit. Mechanically, EA treatment alleviated neuron progenitor cell proliferation and differentiation, ameliorated the field excitatory postsynaptic potentials (fEPSPs) slope impaired by S-Dep, and elevated BDNF/TrkB protein expression. Taken together, our data suggested that EA treatment has a protective effect on S-Dep-induced depression-like behavior and cognitive impairment, which may be through regulating BDNF/TrkB protein expression.

Can sleep protect memories from catastrophic forgetting?

Continual learning remains an unsolved problem in artificial neural networks. The brain has evolved mechanisms to prevent catastrophic forgetting of old knowledge during new training. Building upon data suggesting the importance of sleep in learning and memory, we tested a hypothesis that sleep protects old memories from being forgotten after new learning. In the thalamocortical model, training a new memory interfered with previously learned old memories leading to degradation and forgetting of the old memory traces. Simulating sleep after new learning reversed the damage and enhanced old and new memories. We found that when a new memory competed for previously allocated neuronal/synaptic resources, sleep replay changed the synaptic footprint of the old memory to allow overlapping neuronal populations to store multiple memories. Our study predicts that memory storage is dynamic, and sleep enables continual learning by combining consolidation of new memory traces with reconsolidation of old memory traces to minimize interference.

Diversity and function of corticopetal and corticofugal GABAergic projection neurons

It is still widely thought that cortical projections to distant brain areas derive by and large from glutamatergic neurons. However, an increasing number of reports provide evidence that cortical GABAergic neurons comprise a smaller population of 'projection neurons' in addition to the well-known and much-studied interneurons. GABAergic long-range axons that derive from, or project to, cortical areas are thought to entrain distant brain areas for efficient information transfer and processing. Research conducted over the past 10 years has revealed that cortical GABAergic projection neurons are highly diverse in terms of molecular marker expression, synaptic targeting (identity of targeted cell types), activity pattern during distinct behavioural states and precise temporal recruitment relative to ongoing neuronal network oscillations. As GABAergic projection neurons connect many cortical areas unidirectionally or bidirectionally, it is safe to assume that they participate in the modulation of a whole series of behavioural and cognitive functions. We expect future research to examine how long-range GABAergic projections fine-tune activity in distinct distant networks and how their recruitment alters the behaviours that are supported by these networks.

Causal Contribution of Awake Post-encoding Processes to Episodic Memory Consolidation

Stable representations of past experience are thought to depend on processes that unfold after events are initially encoded into memory. Post-encoding reactivation and hippocampal-cortical interactions are leading candidate mechanisms thought to support memory retention and stabilization across hippocampal-cortical networks. Although putative consolidation mechanisms have been observed during sleep and periods of awake rest, the direct causal contribution of awake consolidation mechanisms to later behavior is unclear, especially in humans. Moreover, it has been argued that observations of putative consolidation processes are epiphenomenal and not causally important, yet there are few tools to test the functional contribution of these mechanisms in humans. Here, we combined transcranial magnetic stimulation (TMS) and fMRI to test the role of awake consolidation processes by targeting hippocampal interactions with lateral occipital cortex (LOC). We applied theta-burst TMS to LOC (and a control site) to interfere with an extended window (approximately 30-50 min) after memory encoding. Behaviorally, post-encoding TMS to LOC selectively impaired associative memory retention compared to multiple control conditions. In the control TMS condition, we replicated prior reports of post-encoding reactivation and memory-related hippocampal-LOC interactions during periods of awake rest using fMRI. However, post-encoding LOC TMS reduced these processes, such that post-encoding reactivation in LOC and memory-related hippocampal-LOC functional connectivity were no longer present. By targeting and manipulating post-encoding neural processes, these findings highlight the direct contribution of awake time periods to episodic memory consolidation. This combined TMS-fMRI approach provides an opportunity for causal manipulations of human memory consolidation.

Ih, GIRK, and KCNQ/Kv7 channels differently modulate sharp wave - ripples in the dorsal and ventral hippocampus

Sharp waves and ripples (SPW-Rs) are endogenous transient patterns of hippocampus local network activity implicated in several functions including memory consolidation, and they are diversified between the dorsal and the ventral hippocampus. Ion channels in the neuronal membrane play important roles in cell and local network function. In this study, using transverse slices and field potential recordings from the CA1 field of rat hippocampus we show that GIRK and KCNQ2/3 potassium channels play a higher role in modulating SPW-Rs in the dorsal hippocampus, while I_h and other KCNQ (presumably KCNQ5) channels, contribute to shaping SPW-R activity more in the ventral than in dorsal hippocampus. Specifically, blockade of I_h channels by ZD 7288 reduced the rate of occurrence of SPW-Rs and increased the generation of SPW-Rs in the form of clusters in both hippocampal segments, while enhanced the amplitude of SPW-Rs only in the ventral hippocampus. Most effects of ZD 7288 appeared to be independent of NMDA receptors' activity. However, the effects of blockade of NMDA receptors depended on the functional state of I_h channels in both hippocampal segments. Blockade of GIRK channels by Tertiapin-Q increased the rate of occurrence of SPW-Rs only in the dorsal hippocampus and the probability of clusters in both segments of the hippocampus. Blockade of KCNQ2/3 channels by XE 991 increased the rate of occurrence of SPW-Rs and the probability of clusters in the dorsal hippocampus, and only reduced the clustered generation of SPW-Rs in the ventral hippocampus. The blocker of KCNQ1/2 channels, that also enhances KCNQ5 channels, UCL 2077, increased the probability of clusters and the power of the ripple oscillation in the ventral hippocampus only. These results suggest that GIRK, KCNQ and I_h channels represent a key mechanism for modulation of SPW-R activity which act differently in the dorsal and ventral hippocampus, fundamentally supporting functional diversification along the dorsal-ventral axis of the hippocampus.

Dorsal hippocampus- and ACC-projecting medial septum neurons differentially contribute to the recollection of episodic-like memory

Episodic memory refers to the recollection of previous experiences containing specific temporal, spatial, and emotional information. The ability to recollect episodic memory requires coordination of multiple brain regions, including the hippocampus (HPC) and the cingulate cortex. While the afferents into HPC and cingulate cortex that orchestrate the episodic memory remain unclear. The medial septum (MS), one of the anatomical location of cholinergic centers, innervates not only the dorsal HPC (dHPC), but also the cingulate and entorhinal cortices. By using "What-Where-When" episodic-like memory (ELM) behavioral model and viral tracing, we found that MS neurons projected to dHPC and anterior cingulate cortex (ACC), which exerted distinct impacts on ELM recollection. Chemogenetic inhibition of the dHPC-projecting MS neurons disrupted "What-Where-When" ELM recollection as well as object location, object-in-place, and recency recognition memories recollection, while chemogenetic inhibition of the ACC-projecting MS neurons only disrupted "What-Where-When" ELM recollection. Moreover, neither dHPC- nor ACC-projecting MS neurons were involved in novel object recognition memory recollection or locomotor activity. Immunostaining showed that ACC- and dHPC-projecting MS neurons are partially overlapped populations. These findings reveal an unsuspected division of ELM processing and provide the potential mechanism that the recollection of episodic memory need the coordination of MS neurons projecting to dHPC and ACC.

BRAIN Initiative: Cutting-Edge Tools and Resources for the Community

The overarching goal of the NIH BRAIN (Brain Research through Advancing Innovative Neurotechnologies) Initiative is to advance the understanding of healthy and diseased brain circuit function through technological innovation. Core principles for this goal include the validation and dissemination of the myriad innovative technologies, tools, methods, and resources emerging from BRAIN-funded research. Innovators, BRAIN funding agencies, and non-Federal partners are working together to develop strategies for making these products usable, available, and accessible to the scientific community. Here, we describe several early strategies for supporting the dissemination of BRAIN technologies. We aim to invigorate a dialogue with the neuroscience research and funding community, interdisciplinary collaborators, and trainees about the existing and future opportunities for cultivating groundbreaking research products into mature, integrated, and adaptable research systems. Along with the accompanying Society for Neuroscience 2019 Mini-Symposium, "BRAIN Initiative: Cutting-Edge Tools and Resources for the Community," we spotlight the work of several BRAIN investigator teams who are making progress toward providing tools, technologies, and services for the neuroscience community. These tools access neural circuits at multiple levels of analysis, from subcellular composition to brain-wide network connectivity, including the following: integrated systems for EM- and florescence-based connectomics, advances in immunolabeling capabilities, and resources for recording and analyzing functional connectivity. Investigators describe how the resources they provide to the community will contribute to achieving the goals of the NIH BRAIN Initiative. Finally, in addition to celebrating the contributions of these BRAIN-funded investigators, the Mini-Symposium will illustrate the broader diversity of BRAIN Initiative investments in cutting-edge technologies and resources.

Dynamic representations in networked neural systems

A group of neurons can generate patterns of activity that represent information about stimuli; subsequently, the group can transform and transmit activity patterns across synapses to spatially distributed areas. Recent studies in neuroscience have begun to independently address the two components of information processing: the representation of stimuli in neural activity and the transmission of information in networks that model neural interactions. Yet only recently are studies seeking to link these two types of approaches. Here we briefly review the two separate bodies of literature; we then review the recent strides made to address this gap. We continue with a discussion of how patterns of activity evolve from one representation to another, forming dynamic representations that unfold on the underlying network. Our goal is to offer a holistic framework for understanding and describing neural information representation and transmission while revealing exciting frontiers for future research.

Competing Roles of Slow Oscillations and Delta Waves in Memory Consolidation versus Forgetting

Sleep has been implicated in both memory consolidation and forgetting of experiences. However, it is unclear what governs the balance between consolidation and forgetting. Here, we tested how activity-dependent processing during sleep might differentially regulate these two processes. We specifically examined how neural reactivations during non-rapid eye movement (NREM) sleep were causally linked to consolidation versus weakening of the neural correlates of neuroprosthetic skill. Strikingly, we found that slow oscillations (SOs) and delta (δ) waves have dissociable and competing roles in consolidation versus forgetting. By modulating cortical spiking linked to SOs or δ waves using closed-loop optogenetic methods, we could, respectively, weaken or strengthen consolidation and thereby bidirectionally modulate sleep-dependent performance gains. We further found that changes in the temporal coupling of spindles to SOs relative to δ waves could account for such effects. Thus, our results indicate that neural activity driven by SOs and δ waves have competing roles in sleep-dependent memory consolidation.

A time-dependent role for the transcription factor CREB in neuronal allocation to an engram underlying a fear memory revealed using a novel in vivo optogenetic tool to modulate CREB function

The internal representation of an experience is thought to be encoded by long-lasting physical changes to the brain ("engrams") . Previously, we and others showed within the lateral amygdala (LA), a region critical for auditory conditioned fear, eligible neurons compete against one other for allocation to an engram. Neurons with relatively higher function of the transcription factor CREB were more likely to be allocated to the engram. In these studies, though, CREB function was artificially increased for several days before training. Precisely when increased CREB function is important for allocation remains an unanswered question. Here, we took advantage of a novel optogenetic tool (opto-DN-CREB) to gain spatial and temporal control of CREB function in freely behaving mice. We found increasing CREB function in a small, random population of LA principal neurons in the minutes, but not 24 h, before training was sufficient to enhance memory, likely because these neurons were preferentially allocated to the underlying engram. However, similarly increasing CREB activity in a small population of random LA neurons immediately after training disrupted subsequent memory retrieval, likely by disrupting the precise spatial and temporal patterns of offline post-training neuronal activity and/or function required for consolidation. These findings reveal the importance of the timing of CREB activity in regulating allocation and subsequent memory retrieval, and further, highlight the potential of optogenetic approaches to control protein function with temporal specificity in behaving animals.