Spatiotemporal patterns of neocortical activity around hippocampal sharp-wave ripples

Linking brain activity across scales with simultaneous opto- and electrophysiology

The brain enables adaptive behavior via the dynamic coordination of diverse neuronal signals across spatial and temporal scales: from fast action potential patterns in microcircuits to slower patterns of distributed activity in brain-wide networks. Understanding principles of multiscale dynamics requires simultaneous monitoring of signals in multiple, distributed network nodes. Combining optical and electrical recordings of brain activity is promising for collecting data across multiple scales and can reveal aspects of coordinated dynamics invisible to standard, single-modality approaches. We review recent progress in combining opto- and electrophysiology, focusing on mouse studies that shed new light on the function of single neurons by embedding their activity in the context of brain-wide activity patterns. Optical and electrical readouts can be tailored to desired scales to tackle specific questions. For example, fast dynamics in single cells or local populations recorded with multi-electrode arrays can be related to simultaneously acquired optical signals that report activity in specified subpopulations of neurons, in non-neuronal cells, or in neuromodulatory pathways. Conversely, two-photon imaging can be used to densely monitor activity in local circuits while sampling electrical activity in distant brain areas at the same time. The refinement of combined approaches will continue to reveal previously inaccessible and under-appreciated aspects of coordinated brain activity.

Multivariate sharp-wave ripples in schizophrenia during awake state

AIMS

Schizophrenia (SZ) is a brain disorder characterized by psychotic symptoms and cognitive dysfunction. Recently, irregularities in sharp-wave ripples (SPW-Rs) have been reported in SZ. As SPW-Rs play a critical role in memory, their irregularities can cause psychotic symptoms and cognitive dysfunction in patients with SZ. In this study, we investigated the SPW-Rs in human SZ.

METHODS

We measured whole-brain activity using magnetoencephalography (MEG) in patients with SZ (n = 20) and sex- and age-matched healthy participants (n = 20) during open-eye rest. We identified SPW-Rs and analyzed their occurrence and time-frequency traits. Furthermore, we developed a novel multivariate analysis method, termed "ripple-gedMEG" to extract the global features of SPW-Rs. We also examined the association between SPW-Rs and brain state transitions. The outcomes of these analyses were modeled to predict the positive and negative syndrome scale (PANSS) scores of SZ.

RESULTS

We found that SPW-Rs in the SZ (1) occurred more frequently, (2) the delay of the coupling phase (3) appeared in different brain areas, (4) consisted of a less organized spatiotemporal pattern, and (5) were less involved in brain state transitions. Finally, some of the neural features associated with the SPW-Rs were found to be PANSS-positive, a pathological indicator of SZ. These results suggest that widespread but disorganized SPW-Rs underlies the symptoms of SZ.

CONCLUSION

We identified irregularities in SPW-Rs in SZ and confirmed that their alternations were strongly associated with SZ neuropathology. These results suggest a new direction for human SZ research.

Imaging high-frequency voltage dynamics in multiple neuron classes of behaving mammals

Fluorescent genetically encoded voltage indicators report transmembrane potentials of targeted cell-types. However, voltage-imaging instrumentation has lacked the sensitivity to track spontaneous or evoked high-frequency voltage oscillations in neural populations. Here we describe two complementary TEMPO voltage-sensing technologies that capture neural oscillations up to ~100 Hz. Fiber-optic TEMPO achieves ~10-fold greater sensitivity than prior photometry systems, allows hour-long recordings, and monitors two neuron-classes per fiber-optic probe in freely moving mice. With it, we uncovered cross-frequency-coupled theta- and gamma-range oscillations and characterized excitatory-inhibitory neural dynamics during hippocampal ripples and visual cortical processing. The TEMPO mesoscope images voltage activity in two cell-classes across a ~8-mm-wide field-of-view in head-fixed animals. In awake mice, it revealed sensory-evoked excitatory-inhibitory neural interactions and traveling gamma and 3-7 Hz waves in the visual cortex, and previously unreported propagation directions for hippocampal theta and beta waves. These technologies have widespread applications probing diverse oscillations and neuron-type interactions in healthy and diseased brains.

Prefrontal cortical ripples mediate top-down suppression of hippocampal reactivation during sleep memory consolidation

Consolidation of initially encoded hippocampal representations in the neocortex through reactivation is crucial for long-term memory formation and is facilitated by the coordination of hippocampal sharp-wave ripples (SWRs) with cortical slow and spindle oscillations during non-REM sleep. Recent evidence suggests that high-frequency cortical ripples can also coordinate with hippocampal SWRs in support of consolidation; however, the contribution of cortical ripples to reactivation remains unclear. We used high-density, continuous recordings in the hippocampus (area CA1) and prefrontal cortex (PFC) over the course of spatial learning and show that independent PFC ripples dissociated from SWRs are prevalent in NREM sleep and predominantly suppress hippocampal activity. PFC ripples paradoxically mediate top-down suppression of hippocampal reactivation rather than coordination, and this suppression is stronger for assemblies that are reactivated during coordinated CA1-PFC ripples for consolidation of recent experiences. Further, we show non-canonical, serial coordination of independent cortical ripples with slow and spindle oscillations, which are known signatures of memory consolidation. These results establish a role for prefrontal cortical ripples in top-down regulation of behaviorally relevant hippocampal representations during consolidation.

Local field potential sharp waves with diversified impact on cortical neuronal encoding of haptic input

Cortical sensory processing is greatly impacted by internally generated activity. But controlling for that activity is difficult since the thalamocortical network is a high-dimensional system with rapid state changes. Therefore, to unwind the cortical computational architecture there is a need for physiological 'landmarks' that can be used as frames of reference for computational state. Here we use a waveshape transform method to identify conspicuous local field potential sharp waves (LFP-SPWs) in the somatosensory cortex (S1). LFP-SPW events triggered short-lasting but massive neuronal activation in all recorded neurons with a subset of neurons initiating their activation up to 20 ms before the LFP-SPW onset. In contrast, LFP-SPWs differentially impacted the neuronal spike responses to ensuing tactile inputs, depressing the tactile responses in some neurons and enhancing them in others. When LFP-SPWs coactivated with more distant cortical surface (ECoG)-SPWs, suggesting an involvement of these SPWs in global cortical signaling, the impact of the LFP-SPW on the neuronal tactile response could change substantially, including inverting its impact to the opposite. These cortical SPWs shared many signal fingerprint characteristics as reported for hippocampal SPWs and may be a biomarker for a particular type of state change that is possibly shared byboth hippocampus and neocortex.

Potential role of oxytocin in the regulation of memories and treatment of memory disorders

Oxytocin (OXT) is an "affiliative" hormone or neurohormone or neuropeptide consists of nine amino acids, synthesized in magnocellular neurons of paraventricular (PVN) and supraoptic nuclei (SON) of hypothalamus. OXT receptors are widely distributed in various region of brain and OXT has been shown to regulate various social and nonsocial behavior. Hippocampus is the main region which regulates the learning and memory. Hippocampus particularly regulates the acquisition of new memories and retention of acquired memories. OXT has been shown to regulate the synaptic plasticity, neurogenesis, and consolidation of memories. Further, findings from both preclinical and clinical studies have suggested that the OXT treatment improves performance in memory related task. Various trials have suggested the positive impact of intranasal OXT in the dementia patients. However, these studies are limited in number. In the present study authors have highlighted the role of OXT in the formation and retrieval of memories. Further, the study demonstrated the outcome of OXT treatment in various memory and related disorders.

Wide-field imaging in behaving mice as a tool to study cognitive function

Cognitive functions are mediated through coordinated and dynamic neuronal responses that involve many different areas across the brain. Therefore, it is of high interest to simultaneously record neuronal activity from as many brain areas as possible while the subject performs a cognitive behavioral task. One of the emerging tools to achieve a mesoscopic field of view is wide-field imaging of cortex-wide dynamics in mice. Wide-field imaging is cost-effective, user-friendly, and enables obtaining cortex-wide signals from mice performing complex and demanding cognitive tasks. Importantly, wide-field imaging offers an unbiased cortex-wide observation that sheds light on overlooked cortical regions and highlights parallel processing circuits. Recent wide-field imaging studies have shown that multi-area cortex-wide patterns, rather than just a single area, are involved in encoding cognitive functions. The optical properties of wide-field imaging enable imaging of different brain signals, such as layer-specific, inhibitory subtypes, or neuromodulation signals. Here, I review the main advantages of wide-field imaging in mice, review the recent literature, and discuss future directions of the field. It is expected that wide-field imaging in behaving mice will continue to gain popularity and aid in understanding the mesoscale dynamics underlying cognitive function.

Bridging Neuroscience and AI: Environmental Enrichment as a Model for Forward Knowledge Transfer

Continual learning (CL) refers to an agent's capability to learn from a continuous stream of data and transfer knowledge without forgetting old information. One crucial aspect of CL is forward transfer, i.e., improved and faster learning on a new task by leveraging information from prior knowledge. While this ability comes naturally to biological brains, it poses a significant challenge for artificial intelligence (AI). Here, we suggest that environmental enrichment (EE) can be used as a biological model for studying forward transfer, inspiring human-like AI development. EE refers to animal studies that enhance cognitive, social, motor, and sensory stimulation and is a model for what, in humans, is referred to as 'cognitive reserve'. Enriched animals show significant improvement in learning speed and performance on new tasks, typically exhibiting forward transfer. We explore anatomical, molecular, and neuronal changes post-EE and discuss how artificial neural networks (ANNs) can be used to predict neural computation changes after enriched experiences. Finally, we provide a synergistic way of combining neuroscience and AI research that paves the path toward developing AI capable of rapid and efficient new task learning.

Sleep loss diminishes hippocampal reactivation and replay

Memories benefit from sleep1, and the reactivation and replay of waking experiences during hippocampal sharp-wave ripples (SWRs) are considered to be crucial for this process2. However, little is known about how these patterns are impacted by sleep loss. Here we recorded CA1 neuronal activity over 12 h in rats across maze exploration, sleep and sleep deprivation, followed by recovery sleep. We found that SWRs showed sustained or higher rates during sleep deprivation but with lower power and higher frequency ripples. Pyramidal cells exhibited sustained firing during sleep deprivation and reduced firing during sleep, yet their firing rates were comparable during SWRs regardless of sleep state. Despite the robust firing and abundance of SWRs during sleep deprivation, we found that the reactivation and replay of neuronal firing patterns was diminished during these periods and, in some cases, completely abolished compared to ad libitum sleep. Reactivation partially rebounded after recovery sleep but failed to reach the levels found in natural sleep. These results delineate the adverse consequences of sleep loss on hippocampal function at the network level and reveal a dissociation between the many SWRs elicited during sleep deprivation and the few reactivations and replays that occur during these events.

Spatial-Temporal Analysis of Neural Desynchronization in Sleeplike States Reveals Critical Dynamics

Sleep is characterized by nonrapid eye movement sleep, originating from widespread neuronal synchrony, and rapid eye movement sleep, with neuronal desynchronization akin to waking behavior. While these were thought to be global brain states, recent research suggests otherwise. Using time-frequency analysis of mesoscopic voltage-sensitive dye recordings of mice in a urethane-anesthetized model of sleep, we find transient neural desynchronization occurring heterogeneously across the cortex within a background of synchronized neural activity, in a manner reminiscent of a critical spreading process and indicative of an "edge-of-synchronization" phase transition.

Cross-strata co-occurrence of ripples with theta-frequency oscillations in the hippocampus of foraging rats

Brain rhythms have been postulated to play central roles in animal cognition. A prominently reported dichotomy of hippocampal rhythms links theta-frequency oscillations (4-12 Hz) and ripples (120-250 Hz) exclusively to preparatory and consummatory behaviours, respectively. However, because of the differential power expression of these two signals across hippocampal strata, such exclusivity requires validation through analyses of simultaneous multi-strata recordings. We assessed co-occurrence of theta-frequency oscillations with ripples in multi-channel recordings of extracellular potentials across hippocampal strata from foraging rats. We detected all ripple events from an identified stratum pyramidale (SP) channel. We then defined theta epochs based on theta oscillations detected from the stratum lacunosum-moleculare (SLM) or the stratum radiatum (SR). We found ∼20% of ripple events (in SP) to co-occur with theta epochs identified from SR/SLM channels, defined here as theta ripples. Strikingly, when theta epochs were instead identified from the SP channel, such co-occurrences were significantly reduced because of a progressive reduction in theta power along the SLM-SR-SP axis. Behaviourally, we found most theta ripples to occur during immobile periods, with comparable theta power during exploratory and immobile theta epochs. Furthermore, the progressive reduction in theta power along the SLM-SR-SP axis was common to exploratory and immobile periods. Finally, we found a strong theta-phase preference of theta ripples within the fourth quadrant [3π/2 - 2π] of the associated theta oscillation. The prevalence of theta ripples expands the potential roles of ripple-frequency oscillations to span the continuum of encoding, retrieval and consolidation, achieved through interactions with theta oscillations. KEY POINTS: The brain manifests oscillations in recorded electrical potentials, with different frequencies of oscillation associated with distinct behavioural states. A prominently reported dichotomy assigns theta-frequency oscillations (4-12 Hz) and ripples (120-250 Hz) recorded in the hippocampus to be exclusively associated with preparatory and consummatory behaviours, respectively. Our multi-strata recordings from the rodent hippocampus coupled with cross-strata analyses provide direct quantitative evidence for the occurrence of ripple events nested within theta oscillations. These results highlight the need for an analysis pipeline that explicitly accounts for the specific strata where individual oscillatory power is high, in analysing simultaneously recorded data from multiple strata. Our observations open avenues for investigations involving cross-strata interactions between theta oscillations and ripples across different behavioural states.

Differences in sleep spindle wave density between patients with diabetes mellitus and matched controls: implications for sensing and regulation of peripheral blood glucose

Background

Brain waves during sleep are involved in sensing and regulating peripheral glucose level. Whether brain waves in patients with diabetes differ from those of healthy subjects is unknown. We examined the hypothesis that patients with diabetes have reduced sleep spindle waves, a form of brain wave implicated in periphery glucose regulation during sleep.

Methods

From a retrospective analysis of polysomnography (PSG) studies on patients who underwent sleep apnea evaluation, we identified 1,214 studies of patients with diabetes mellitus (>66% type 2) and included a sex- and age-matched control subject for each within the scope of our analysis. We similarly identified 376 patients with prediabetes and their matched controls. We extracted spindle characteristics from artifact-removed PSG electroencephalograms and other patient data from records. We used rank-based statistical methods to test hypotheses. We validated our finding on an external PSG dataset.

Results

Patients with diabetes mellitus exhibited on average about half the spindle density (median=0.38 spindles/min) during sleep as their matched control subjects (median=0.70 spindles/min) (P<2.2e-16). Compared to controls, spindle loss was more pronounced in female patients than in male patients in the frontal regions of the brain (P=0.04). Patients with prediabetes also exhibited signs of lower spindle density compared to matched controls (P=0.01-0.04).

Conclusions

Patients with diabetes have fewer spindle waves that are implicated in glucose regulation than matched controls during sleep. Besides offering a possible explanation for neurological complications from diabetes, our findings open the possibility that reversing/reducing spindle loss could improve the overall health of patients with diabetes mellitus.

Coupled sleep rhythms for memory consolidation

How do passing moments turn into lasting memories? Sheltered from external tasks and distractions, sleep constitutes an optimal state for the brain to reprocess and consolidate previous experiences. Recent work suggests that consolidation is governed by the intricate interaction of slow oscillations (SOs), spindles, and ripples - electrophysiological sleep rhythms that orchestrate neuronal processing and communication within and across memory circuits. This review describes how sequential SO-spindle-ripple coupling provides a temporally and spatially fine-tuned mechanism to selectively strengthen target memories across hippocampal and cortical networks. Coupled sleep rhythms might be harnessed not only to enhance overnight memory retention, but also to combat memory decline associated with healthy ageing and neurodegenerative diseases.

Hippocampal replay sequence governed by spontaneous brain-wide dynamics

Neurons in the hippocampus exhibit spontaneous spiking activity during rest that appears to recapitulate previously experienced events. While this replay activity is frequently linked to memory consolidation and learning, the underlying mechanisms are not well understood. Recent large-scale neural recordings in mice have demonstrated that resting-state spontaneous activity is expressed as quasi-periodic cascades of spiking activity that pervade the forebrain, with each cascade engaging a high proportion of recorded neurons. Hippocampal ripples are known to be coordinated with cortical dynamics; however, less is known about the occurrence of replay activity relative to other brain-wide spontaneous events. Here we analyzed responses across the mouse brain to multiple viewings of natural movies, as well as subsequent patterns of neural activity during rest. We found that hippocampal neurons showed time-selectivity, with individual neurons responding consistently during particular moments of the movie. During rest, the population of time-selective hippocampal neurons showed both forward and time-reversed replay activity that matched the sequence observed in the movie. Importantly, these replay events were strongly time-locked to brain-wide spiking cascades, with forward and time-reversed replay activity associated with distinct cascade types. Thus, intrinsic hippocampal replay activity is temporally structured according to large-scale spontaneous physiology affecting areas throughout the forebrain. These findings shed light on the coordination between hippocampal and cortical circuits thought to be critical for memory consolidation.

Hippocampal ripples coincide with "up-state" and spindles in retrosplenial cortex

During NREM sleep, hippocampal sharp-wave ripple (SWR) events are thought to stabilize memory traces for long-term storage in downstream neocortical structures. Within the neocortex, a set of distributed networks organized around retrosplenial cortex (RS-network) interact preferentially with the hippocampus purportedly to consolidate those traces. Transient bouts of slow oscillations and sleep spindles in this RS-network are often observed around SWRs, suggesting that these two activities are related and that their interplay possibly contributes to memory consolidation. To investigate how SWRs interact with the RS-network and spindles, we combined cortical wide-field voltage imaging, Electrocorticography, and hippocampal LFP recordings in anesthetized and sleeping mice. Here, we show that, during SWR, "up-states" and spindles reliably co-occur in a cortical subnetwork centered around the retrosplenial cortex. Furthermore, retrosplenial transient activations and spindles predict slow gamma oscillations in CA1 during SWRs. Together, our results suggest that retrosplenial-hippocampal interaction may be a critical pathway of information exchange between the cortex and hippocampus.

Ripple-locked coactivity of stimulus-specific neurons and human associative memory

Associative memory enables the encoding and retrieval of relations between different stimuli. To better understand its neural basis, we investigated whether associative memory involves temporally correlated spiking of medial temporal lobe (MTL) neurons that exhibit stimulus-specific tuning. Using single-neuron recordings from patients with epilepsy performing an associative object-location memory task, we identified the object-specific and place-specific neurons that represented the separate elements of each memory. When patients encoded and retrieved particular memories, the relevant object-specific and place-specific neurons activated together during hippocampal ripples. This ripple-locked coactivity of stimulus-specific neurons emerged over time as the patients' associative learning progressed. Between encoding and retrieval, the ripple-locked timing of coactivity shifted, suggesting flexibility in the interaction between MTL neurons and hippocampal ripples according to behavioral demands. Our results are consistent with a cellular account of associative memory, in which hippocampal ripples coordinate the activity of specialized cellular populations to facilitate links between stimuli.

Theta mediated dynamics of human hippocampal-neocortical learning systems in memory formation and retrieval

Episodic memory arises as a function of dynamic interactions between the hippocampus and the neocortex, yet the mechanisms have remained elusive. Here, using human intracranial recordings during a mnemonic discrimination task, we report that 4-5 Hz (theta) power is differentially recruited during discrimination vs. overgeneralization, and its phase supports hippocampal-neocortical when memories are being formed and correctly retrieved. Interactions were largely bidirectional, with small but significant net directional biases; a hippocampus-to-neocortex bias during acquisition of new information that was subsequently correctly discriminated, and a neocortex-to-hippocampus bias during accurate discrimination of new stimuli from similar previously learned stimuli. The 4-5 Hz rhythm may facilitate the initial stages of information acquisition by neocortex during learning and the recall of stored information from cortex during retrieval. Future work should further probe these dynamics across different types of tasks and stimuli and computational models may need to be expanded accordingly to accommodate these findings.

Converging diencephalic and hippocampal supports for episodic memory

To understand the neural basis of episodic memory it is necessary to appreciate the significance of the fornix. This pathway creates a direct link between those temporal lobe and medial diencephalic sites responsible for anterograde amnesia. A collaboration with Andrew Mayes made it possible to recruit and scan 38 patients with colloid cysts in the third ventricle, a condition associated with variable fornix damage. Complete fornix loss was seen in three patients, who suffered chronic long-term memory problems. Volumetric analyses involving all 38 patients then revealed a highly consistent relationship between mammillary body volume and the recall of episodic memory. That relationship was not seen for working memory or tests of recognition memory. Three different methods all supported a dissociation between recollective-based recognition (impaired) and familiarity-based recognition (spared). This dissociation helped to show how the mammillary body-anterior thalamic nuclei axis, as well as the hippocampus, is vital for episodic memory yet is not required for familiarity-based recognition. These findings set the scene for a reformulation of temporal lobe and diencephalic amnesia. In this revised model, these two regions converge on overlapping cortical areas, including retrosplenial cortex. The united actions of the hippocampal formation and the anterior thalamic nuclei on these cortical areas enable episodic memory encoding and consolidation, impacting on subsequent recall.

Cortical ripples mediate top-down suppression of hippocampal reactivation during sleep memory consolidation

Consolidation of initially encoded hippocampal representations in the neocortex through reactivation is crucial for long-term memory formation, and is facilitated by the coordination of hippocampal sharp-wave ripples (SWRs) with cortical oscillations during non-REM sleep. However, the contribution of high-frequency cortical ripples to consolidation is still unclear. We used continuous recordings in the hippocampus and prefrontal cortex (PFC) over the course of spatial learning and show that independent PFC ripples, when dissociated from SWRs, predominantly suppress hippocampal activity in non-REM sleep. PFC ripples paradoxically mediate top-down suppression of hippocampal reactivation, which is inversely related to reactivation strength during coordinated CA1-PFC ripples. Further, we show non-canonical, serial coordination of ripples with cortical slow and spindle oscillations. These results establish a role for cortical ripples in regulating consolidation.

Sensory cortical ensembles exhibit differential coupling to ripples in distinct hippocampal subregions

Cortical neurons activated during recent experiences often reactivate with dorsal hippocampal CA1 ripples during subsequent rest. Less is known about cortical interactions with intermediate hippocampal CA1, whose connectivity, functions, and ripple events differ from dorsal CA1. We identified three clusters of putative excitatory neurons in mouse visual cortex that are preferentially excited together with either dorsal or intermediate CA1 ripples or suppressed before both ripples. Neurons in each cluster were evenly distributed across primary and higher visual cortices and co-active even in the absence of ripples. These ensembles exhibited similar visual responses but different coupling to thalamus and pupil-indexed arousal. We observed a consistent activity sequence preceding and predicting ripples: (1) suppression of ripple-suppressed cortical neurons, (2) thalamic silence, and (3) activation of intermediate CA1-ripple-activated cortical neurons. We propose that coordinated dynamics of these ensembles relay visual experiences to distinct hippocampal subregions for incorporation into different cognitive maps.

Restoring neuronal chloride extrusion reverses cognitive decline linked to Alzheimer's disease mutations

Disinhibition during early stages of Alzheimer's disease is postulated to cause network dysfunction and hyperexcitability leading to cognitive deficits. However, the underlying molecular mechanism remains unknown. Here we show that, in mouse lines carrying Alzheimer's disease-related mutations, a loss of neuronal membrane potassium-chloride cotransporter KCC2, responsible for maintaining the robustness of GABAA-mediated inhibition, occurs pre-symptomatically in the hippocampus and prefrontal cortex. KCC2 downregulation was inversely correlated with the age-dependent increase in amyloid-β 42 (Aβ42). Acute administration of Aβ42 caused a downregulation of membrane KCC2. Loss of KCC2 resulted in impaired chloride homeostasis. Preventing the decrease in KCC2 using long term treatment with CLP290 protected against deterioration of learning and cortical hyperactivity. In addition, restoring KCC2, using short term CLP290 treatment, following the transporter reduction effectively reversed spatial memory deficits and social dysfunction, linking chloride dysregulation with Alzheimer's disease-related cognitive decline. These results reveal KCC2 hypofunction as a viable target for treatment of Alzheimer's disease-related cognitive decline; they confirm target engagement, where the therapeutic intervention takes place, and its effectiveness.

Cortical reactivation of spatial and non-spatial features coordinates with hippocampus to form a memory dialogue

Episodic memories comprise diverse attributes of experience distributed across neocortical areas. The hippocampus is integral to rapidly binding these diffuse representations, as they occur, to be later reinstated. However, the nature of the information exchanged during this hippocampal-cortical dialogue remains poorly understood. A recent study has shown that the secondary motor cortex carries two types of representations: place cell-like activity, which were impaired by hippocampal lesions, and responses tied to visuo-tactile cues, which became more pronounced following hippocampal lesions. Using two-photon Ca2+ imaging to record neuronal activities in the secondary motor cortex of male Thy1-GCaMP6s mice, we assessed the cortical retrieval of spatial and non-spatial attributes from previous explorations in a virtual environment. We show that, following navigation, spontaneous resting state reactivations convey varying degrees of spatial (trajectory sequences) and non-spatial (visuo-tactile attributes) information, while reactivations of non-spatial attributes tend to precede reactivations of spatial representations surrounding hippocampal sharp-wave ripples.

Mesotrode chronic simultaneous mesoscale cortical imaging and subcortical or peripheral nerve spiking activity recording in mice

Brain function originates from hierarchical spatial-temporal neural dynamics distributed across cortical and subcortical networks. However, techniques available to assess large-scale brain network activity with single-neuron resolution in behaving animals remain limited. Here, we present Mesotrode that integrates chronic wide-field mesoscale cortical imaging and compact multi-site cortical/subcortical cellular electrophysiology in head-fixed mice that undergo self-initiated running or orofacial movements. Specifically, we harnessed the flexibility of chronic multi-site tetrode recordings to monitor single-neuron activity in multiple subcortical structures while simultaneously imaging the mesoscale activity of the entire dorsal cortex. A mesoscale spike-triggered averaging procedure allowed the identification of cortical activity motifs preferentially associated with single-neuron spiking. Using this approach, we were able to characterize chronic single-neuron-related functional connectivity maps for up to 60 days post-implantation. Neurons recorded from distinct subcortical structures display diverse but segregated cortical maps, suggesting that neurons of different origins participate in distinct cortico-subcortical pathways. We extended the capability of Mesotrode by implanting the micro-electrode at the facial motor nerve and found that facial nerve spiking is functionally associated with the PTA, RSP, and M2 network, and optogenetic inhibition of the PTA area significantly reduced the facial movement of the mice. These findings demonstrate that Mesotrode can be used to sample different combinations of cortico-subcortical networks over prolonged periods, generating multimodal and multi-scale network activity from a single implant, offering new insights into the neural mechanisms underlying specific behaviors.

How far neuroscience is from understanding brains

The cellular biology of brains is relatively well-understood, but neuroscientists have not yet generated a theory explaining how brains work. Explanations of how neurons collectively operate to produce what brains can do are tentative and incomplete. Without prior assumptions about the brain mechanisms, I attempt here to identify major obstacles to progress in neuroscientific understanding of brains and central nervous systems. Most of the obstacles to our understanding are conceptual. Neuroscience lacks concepts and models rooted in experimental results explaining how neurons interact at all scales. The cerebral cortex is thought to control awake activities, which contrasts with recent experimental results. There is ambiguity distinguishing task-related brain activities from spontaneous activities and organized intrinsic activities. Brains are regarded as driven by external and internal stimuli in contrast to their considerable autonomy. Experimental results are explained by sensory inputs, behavior, and psychological concepts. Time and space are regarded as mutually independent variables for spiking, post-synaptic events, and other measured variables, in contrast to experimental results. Dynamical systems theory and models describing evolution of variables with time as the independent variable are insufficient to account for central nervous system activities. Spatial dynamics may be a practical solution. The general hypothesis that measurements of changes in fundamental brain variables, action potentials, transmitter releases, post-synaptic transmembrane currents, etc., propagating in central nervous systems reveal how they work, carries no additional assumptions. Combinations of current techniques could reveal many aspects of spatial dynamics of spiking, post-synaptic processing, and plasticity in insects and rodents to start with. But problems defining baseline and reference conditions hinder interpretations of the results. Furthermore, the facts that pooling and averaging of data destroy their underlying dynamics imply that single-trial designs and statistics are necessary.

Theta mediated dynamics of human hippocampal-neocortical learning systems in memory formation and retrieval

Episodic memory arises as a function of dynamic interactions between the hippocampus and the neocortex, yet the mechanisms have remained elusive. Here, using human intracranial recordings during a mnemonic discrimination task, we report that 4-5 Hz (theta) power is differentially recruited during discrimination vs. overgeneralization, and its phase supports hippocampal-neocortical when memories are being formed and correctly retrieved. Interactions were largely bidirectional, with small but significant net directional biases; a hippocampus-to-neocortex bias during acquisition of new information that was subsequently correctly discriminated, and a neocortex-to-hippocampus bias during accurate discrimination of new stimuli from similar previously learned stimuli. The 4-5 Hz rhythm may facilitate the initial stages of information acquisition by neocortex during learning and the recall of stored information from cortex during retrieval. Future work should further probe these dynamics across different types of tasks and stimuli and computational models may need to be expanded accordingly to accommodate these findings.

Accounting for multiscale processing in adaptive real-world decision-making via the hippocampus

For adaptive real-time behavior in real-world contexts, the brain needs to allow past information over multiple timescales to influence current processing for making choices that create the best outcome as a person goes about making choices in their everyday life. The neuroeconomics literature on value-based decision-making has formalized such choice through reinforcement learning models for two extreme strategies. These strategies are model-free (MF), which is an automatic, stimulus-response type of action, and model-based (MB), which bases choice on cognitive representations of the world and causal inference on environment-behavior structure. The emphasis of examining the neural substrates of value-based decision making has been on the striatum and prefrontal regions, especially with regards to the "here and now" decision-making. Yet, such a dichotomy does not embrace all the dynamic complexity involved. In addition, despite robust research on the role of the hippocampus in memory and spatial learning, its contribution to value-based decision making is just starting to be explored. This paper aims to better appreciate the role of the hippocampus in decision-making and advance the successor representation (SR) as a candidate mechanism for encoding state representations in the hippocampus, separate from reward representations. To this end, we review research that relates hippocampal sequences to SR models showing that the implementation of such sequences in reinforcement learning agents improves their performance. This also enables the agents to perform multiscale temporal processing in a biologically plausible manner. Altogether, we articulate a framework to advance current striatal and prefrontal-focused decision making to better account for multiscale mechanisms underlying various real-world time-related concepts such as the self that cumulates over a person's life course.

Hippocampal memory reactivation during sleep is correlated with specific cortical states of the retrosplenial and prefrontal cortices

Episodic memories are thought to be stabilized through the coordination of cortico-hippocampal activity during sleep. However, the timing and mechanism of this coordination remain unknown. To investigate this, we studied the relationship between hippocampal reactivation and slow-wave sleep up and down states of the retrosplenial cortex (RTC) and prefrontal cortex (PFC). We found that hippocampal reactivations are strongly correlated with specific cortical states. Reactivation occurred during sustained cortical Up states or during the transition from up to down state. Interestingly, the most prevalent interaction with memory reactivation in the hippocampus occurred during sustained up states of the PFC and RTC, while hippocampal reactivation and cortical up-to-down state transition in the RTC showed the strongest coordination. Reactivation usually occurred within 150-200 msec of a cortical Up state onset, indicating that a buildup of excitation during cortical Up state activity influences the probability of memory reactivation in CA1. Conversely, CA1 reactivation occurred 30-50 msec before the onset of a cortical down state, suggesting that memory reactivation affects down state initiation in the RTC and PFC, but the effect in the RTC was more robust. Our findings provide evidence that supports and highlights the complexity of bidirectional communication between cortical regions and the hippocampus during sleep.

The neurophysiologic landscape of the sleep onset: a systematic review

Background

The sleep onset process is an ill-defined complex process of transition from wakefulness to sleep, characterized by progressive modifications at the subjective, behavioural, cognitive, and physiological levels. To this date, there is no international consensus which could aid a principled characterisation of this process for clinical research purposes. The current review aims to systemise the current knowledge about the underlying mechanisms of the natural heterogeneity of this process.

Methods

In this systematic review, studies investigating the process of the sleep onset from 1970 to 2022 were identified using electronic database searches of PsychINFO, MEDLINE, and Embase.

Results

A total of 139 studies were included; 110 studies in healthy participants and 29 studies in participants with sleep disorders. Overall, there is a limited consensus across a body of research about what distinct biomarkers of the sleep onset constitute. Only sparse data exists on the physiology, neurophysiology and behavioural mechanisms of the sleep onset, with majority of studies concentrating on the non-rapid eye movement stage 2 (NREM 2) as a potentially better defined and a more reliable time point that separates sleep from the wake, on the sleep wake continuum.

Conclusions

The neurophysiologic landscape of sleep onset bears a complex pattern associated with a multitude of behavioural and physiological markers and remains poorly understood. The methodological variation and a heterogenous definition of the wake-sleep transition in various studies to date is understandable, given that sleep onset is a process that has fluctuating and ill-defined boundaries. Nonetheless, the principled characterisation of the sleep onset process is needed which will allow for a greater conceptualisation of the mechanisms underlying this process, further influencing the efficacy of current treatments for sleep disorders.

Hippocampo-cortical circuits for selective memory encoding, routing, and replay

Traditionally considered a homogeneous cell type, hippocampal pyramidal cells have been recently shown to be highly diverse. However, how this cellular diversity relates to the different hippocampal network computations that support memory-guided behavior is not yet known. We show that the anatomical identity of pyramidal cells is a major organizing principle of CA1 assembly dynamics, the emergence of memory replay, and cortical projection patterns in rats. Segregated pyramidal cell subpopulations encoded trajectory and choice-specific information or tracked changes in reward configuration respectively, and their activity was selectively read out by different cortical targets. Furthermore, distinct hippocampo-cortical assemblies coordinated the reactivation of complementary memory representations. These findings reveal the existence of specialized hippocampo-cortical subcircuits and provide a cellular mechanism that supports the computational flexibility and memory capacities of these structures.

The human brain reactivates context-specific past information at event boundaries of naturalistic experiences

Although we perceive the world in a continuous manner, our experience is partitioned into discrete events. However, to make sense of these events, they must be stitched together into an overarching narrative-a model of unfolding events. It has been proposed that such a stitching process happens in offline neural reactivations when rodents build models of spatial environments. Here we show that, while understanding a natural narrative, humans reactivate neural representations of past events. Similar to offline replay, these reactivations occur in the hippocampus and default mode network, where reactivations are selective to relevant past events. However, these reactivations occur, not during prolonged offline periods, but at the boundaries between ongoing narrative events. These results, replicated across two datasets, suggest reactivations as a candidate mechanism for binding temporally distant information into a coherent understanding of ongoing experience.

Hippocampal sharp wave-ripple dynamics in NREM sleep encode motivation for anticipated physical activity

Physical activity is an integral part of every mammal's daily life, and as a driver of Darwinian fitness, required coordinated evolution of the body and brain. The decision to engage in physical activity is driven either by survival needs or by motivation for the rewarding qualities of physical activity itself. Rodents exhibit innate and learned motivation for voluntary wheel running, and over time run longer and farther, reflecting increased incentive salience and motivation for this consummatory behavior. Dynamic coordination of neural and somatic physiology are necessary to ensure the ability to perform behaviors that are motivationally variable. Hippocampal sharp wave-ripples (SWRs) have evolved both cognitive and metabolic functions, which in modern mammals may facilitate body-brain coordination. To determine if SWRs encode aspects of exercise motivation we monitored hippocampal CA1 SWRs and running behaviors in adult mice, while manipulating the incentive salience of the running experience. During non-REM (NREM) sleep, the duration of SWRs before (but not after) running positively correlated with future running duration, and larger pyramidal cell assemblies were activated in longer SWRs, suggesting that the CA1 network encodes exercise motivation at the level of neuronal spiking dynamics. Inter-Ripple-intervals (IRI) before but not after running were negatively correlated with running duration, reflecting more SWR bursting, which increases with learning. In contrast, SWR rates before and after running were positively correlated with running duration, potentially reflecting a tuning of metabolic demand for that day's anticipated and actual energy expenditure rather than motivation. These results suggest a novel role for CA1 in exercise behaviors and specifically that cell assembly activity during SWRs encodes motivation for anticipated physical activity.

SIGNIFICANCE STATEMENT

Darwinian fitness is increased by body-brain coordination through internally generated motivation, though neural substrates are poorly understood. Specific hippocampal rhythms (i.e., CA1 SWRs), which have a well-established role in reward learning, action planning and memory consolidation, have also been shown to modulate systemic [glucose]. Using a mouse model of voluntary physical activity that requires body-brain coordination, we monitored SWR dynamics when animals were highly motivated and anticipated rewarding exercise (i.e., when body-brain coordination is of heightened importance). We found that during non-REM sleep before exercise, SWR dynamics (which reflect cognitive and metabolic functions) were correlated with future time spent exercising. This suggests that SWRs support cognitive and metabolic facets that motivate behavior by coordinating the body and brain.

Regional variation in cholinergic terminal activity determines the non-uniform occurrence of cortical slow waves during REM sleep in mice

Sleep consists of two basic stages: non-rapid eye movement (NREM) and rapid eye movement (REM) sleep. NREM sleep is characterized by slow high-amplitude cortical electroencephalogram (EEG) signals, while REM sleep is characterized by desynchronized cortical rhythms. Despite this, recent electrophysiological studies have suggested the presence of slow waves (SWs) in local cortical areas during REM sleep. Electrophysiological techniques, however, have been unable to resolve the regional structure of these activities because of relatively sparse sampling. Here, we map functional gradients in cortical activity during REM sleep using mesoscale imaging in mice and show local SW patterns occurring mainly in somatomotor and auditory cortical regions with minimum presence within the default mode network. The role of the cholinergic system in local desynchronization during REM sleep is also explored by calcium imaging of cholinergic activity within the cortex and analyzing structural data. We demonstrate weaker cholinergic projections and terminal activity in regions exhibiting frequent SWs during REM sleep.

Distinct mesoscale cortical dynamics encode search strategies during spatial navigation

Spatial navigation is a complex cognitive process that involves neural computations in distributed regions of the brain. Little is known about how cortical regions are coordinated when animals navigate novel spatial environments or how that coordination changes as environments become familiar. We recorded mesoscale calcium (Ca2+) dynamics across large swathes of the dorsal cortex in mice solving the Barnes maze, a 2D spatial navigation task where mice used random, serial, and spatial search strategies to navigate to the goal. Cortical dynamics exhibited patterns of repeated calcium activity with rapid and abrupt shifts between cortical activation patterns at sub-second time scales. We used a clustering algorithm to decompose the spatial patterns of cortical calcium activity in a low dimensional state space, identifying 7 states, each corresponding to a distinct spatial pattern of cortical activation, sufficient to describe the cortical dynamics across all the mice. When mice used serial or spatial search strategies to navigate to the goal, the frontal regions of the cortex were reliably activated for prolonged durations of time (> 1s) shortly after trial initiation. These frontal cortex activation events coincided with mice approaching the edge of the maze from the center and were preceded by temporal sequences of cortical activation patterns that were distinct for serial and spatial search strategies. In serial search trials, frontal cortex activation events were preceded by activation of the posterior regions of the cortex followed by lateral activation of one hemisphere. In spatial search trials, frontal cortical events were preceded by activation of posterior regions of the cortex followed by broad activation of the lateral regions of the cortex. Our results delineated cortical components that differentiate goal- and non-goal oriented spatial navigation strategies.

Sleep fMRI with simultaneous electrophysiology at 9.4 T in male mice

Sleep is ubiquitous and essential, but its mechanisms remain unclear. Studies in animals and humans have provided insights of sleep at vastly different spatiotemporal scales. However, challenges remain to integrate local and global information of sleep. Therefore, we developed sleep fMRI based on simultaneous electrophysiology at 9.4 T in male mice. Optimized un-anesthetized mouse fMRI setup allowed manifestation of NREM and REM sleep, and a large sleep fMRI dataset was collected and openly accessible. State dependent global patterns were revealed, and state transitions were found to be global, asymmetrical and sequential, which can be predicted up to 17.8 s using LSTM models. Importantly, sleep fMRI with hippocampal recording revealed potentiated sharp-wave ripple triggered global patterns during NREM than awake state, potentially attributable to co-occurrence of spindle events. To conclude, we established mouse sleep fMRI with simultaneous electrophysiology, and demonstrated its capability by revealing global dynamics of state transitions and neural events.

Sensory cortical ensembles exhibit differential coupling to ripples in distinct hippocampal subregions

Cortical neurons activated during recent experiences often reactivate with dorsal hippocampal CA1 sharp-wave ripples (SWRs) during subsequent rest. Less is known about cortical interactions with intermediate hippocampal CA1, whose connectivity, functions, and SWRs differ from those of dorsal CA1. We identified three clusters of visual cortical excitatory neurons that are excited together with either dorsal or intermediate CA1 SWRs, or suppressed before both SWRs. Neurons in each cluster were distributed across primary and higher visual cortices and co-active even in the absence of SWRs. These ensembles exhibited similar visual responses but different coupling to thalamus and pupil-indexed arousal. We observed a consistent activity sequence: (i) suppression of SWR-suppressed cortical neurons, (ii) thalamic silence, and (iii) activation of the cortical ensemble preceding and predicting intermediate CA1 SWRs. We propose that the coordinated dynamics of these ensembles relay visual experiences to distinct hippocampal subregions for incorporation into different cognitive maps.

Sharp cell-type-identity changes differentiate the retrosplenial cortex from the neocortex

The laminae of the neocortex are fundamental processing layers of the mammalian brain. Notably, such laminae are believed to be relatively stereotyped across short spatial scales such that shared laminae between nearby brain regions exhibit similar constituent cells. Here, we consider a potential exception to this rule by studying the retrosplenial cortex (RSC), a brain region known for sharp cytoarchitectonic differences across its granular-dysgranular border. Using a variety of transcriptomics techniques, we identify, spatially map, and interpret the excitatory cell-type landscape of the mouse RSC. In doing so, we uncover that RSC gene expression and cell types change sharply at the granular-dysgranular border. Additionally, supposedly homologous laminae between the RSC and the neocortex are effectively wholly distinct in their cell-type composition. In collection, the RSC exhibits a variety of intrinsic cell-type specializations and embodies an organizational principle wherein cell-type identities can vary sharply within and between brain regions.

How our understanding of memory replay evolves

Memory reactivations and replay, widely reported in the hippocampus and cortex across species, have been implicated in memory consolidation, planning, and spatial and skill learning. Technological advances in electrophysiology, calcium imaging, and human neuroimaging techniques have enabled neuroscientists to measure large-scale neural activity with increasing spatiotemporal resolution and have provided opportunities for developing robust analytic methods to identify memory replay. In this article, we first review a large body of historically important and representative memory replay studies from the animal and human literature. We then discuss our current understanding of memory replay functions in learning, planning, and memory consolidation and further discuss the progress in computational modeling that has contributed to these improvements. Next, we review past and present analytic methods for replay analyses and discuss their limitations and challenges. Finally, looking ahead, we discuss some promising analytic methods for detecting nonstereotypical, behaviorally nondecodable structures from large-scale neural recordings. We argue that seamless integration of multisite recordings, real-time replay decoding, and closed-loop manipulation experiments will be essential for delineating the role of memory replay in a wide range of cognitive and motor functions.

Sleep loss diminishes hippocampal reactivation and replay

Memories benefit from sleep, and sleep loss immediately following learning has a negative impact on subsequent memory storage. Several prominent hypotheses ascribe a central role to hippocampal sharp-wave ripples (SWRs), and the concurrent reactivation and replay of neuronal patterns from waking experience, in the offline memory consolidation process that occurs during sleep. However, little is known about how SWRs, reactivation, and replay are affected when animals are subjected to sleep deprivation. We performed long duration (~12 h), high-density silicon probe recordings from rat hippocampal CA1 neurons, in animals that were either sleeping or sleep deprived following exposure to a novel maze environment. We found that SWRs showed a sustained rate of activity during sleep deprivation, similar to or higher than in natural sleep, but with decreased amplitudes for the sharp-waves combined with higher frequencies for the ripples. Furthermore, while hippocampal pyramidal cells showed a log-normal distribution of firing rates during sleep, these distributions were negatively skewed with a higher mean firing rate in both pyramidal cells and interneurons during sleep deprivation. During SWRs, however, firing rates were remarkably similar between both groups. Despite the abundant quantity of SWRs and the robust firing activity during these events in both groups, we found that reactivation of neurons was either completely abolished or significantly diminished during sleep deprivation compared to sleep. Interestingly, reactivation partially rebounded upon recovery sleep, but failed to reach the levels characteristic of natural sleep. Similarly, the number of replays were significantly lower during sleep deprivation and recovery sleep compared to natural sleep. These results provide a network-level account for the negative impact of sleep loss on hippocampal function and demonstrate that sleep loss impacts memory storage by causing a dissociation between the amount of SWRs and the replays and reactivations that take place during these events.

Relating Pupil Diameter and Blinking to Cortical Activity and Hemodynamics across Arousal States

Arousal state affects neural activity and vascular dynamics in the cortex, with sleep associated with large changes in the local field potential and increases in cortical blood flow. We investigated the relationship between pupil diameter and blink rate with neural activity and blood volume in the somatosensory cortex in male and female unanesthetized, head-fixed mice. We monitored these variables while the mice were awake, during periods of rapid eye movement (REM), and non-rapid eye movement (NREM) sleep. Pupil diameter was smaller during sleep than in the awake state. Changes in pupil diameter were coherent with both gamma-band power and blood volume in the somatosensory cortex, but the strength and sign of this relationship varied with arousal state. We observed a strong negative correlation between pupil diameter and both gamma-band power and blood volume during periods of awake rest and NREM sleep, although the correlations between pupil diameter and these signals became positive during periods of alertness, active whisking, and REM. Blinking was associated with increases in arousal and decreases in blood volume when the mouse was asleep. Bilateral coherence in gamma-band power and in blood volume dropped following awake blinking, indicating a reset of neural and vascular activity. Using only eye metrics (pupil diameter and eye motion), we could determine the arousal state of the mouse ('Awake,' 'NREM,' 'REM') with >90% accuracy with a 5 s resolution. There is a strong relationship between pupil diameter and hemodynamics signals in mice, reflecting the pronounced effects of arousal on cerebrovascular dynamics.SIGNIFICANCE STATEMENT Determining arousal state is a critical component of any neuroscience experiment. Pupil diameter and blinking are influenced by arousal state, as are hemodynamics signals in the cortex. We investigated the relationship between cortical hemodynamics and pupil diameter and found that pupil diameter was strongly related to the blood volume in the cortex. Mice were more likely to be awake after blinking than before, and blinking resets neural activity. Pupil diameter and eye motion can be used as a reliable, noninvasive indicator of arousal state. As mice transition from wake to sleep and back again over a timescale of seconds, monitoring pupil diameter and eye motion permits the noninvasive detection of sleep events during behavioral or resting-state experiments.

Rethinking retrosplenial cortex: Perspectives and predictions

The last decade has produced exciting new ideas about retrosplenial cortex (RSC) and its role in integrating diverse inputs. Here, we review the diversity in forms of spatial and directional tuning of RSC activity, temporal organization of RSC activity, and features of RSC interconnectivity with other brain structures. We find that RSC anatomy and dynamics are more consistent with roles in multiple sensorimotor and cognitive processes than with any isolated function. However, two more generalized categories of function may best characterize roles for RSC in complex cognitive processes: (1) shifting and relating perspectives for spatial cognition and (2) prediction and error correction for current sensory states with internal representations of the environment. Both functions likely take advantage of RSC's capacity to encode conjunctions among sensory, motor, and spatial mapping information streams. Together, these functions provide the scaffold for intelligent actions, such as navigation, perspective taking, interaction with others, and error detection.

Inhibition is a prevalent mode of activity in the neocortex around awake hippocampal ripples in mice

Coordinated peri-ripple activity in the hippocampal-neocortical network is essential for mnemonic information processing in the brain. Hippocampal ripples likely serve different functions in sleep and awake states. Thus, the corresponding neocortical activity patterns may differ in important ways. We addressed this possibility by conducting voltage and glutamate wide-field imaging of the neocortex with concurrent hippocampal electrophysiology in awake mice. Contrary to our previously published sleep results, deactivation and activation were dominant in post-ripple neocortical voltage and glutamate activity, respectively, especially in the agranular retrosplenial cortex (aRSC). Additionally, the spiking activity of aRSC neurons, estimated by two-photon calcium imaging, revealed the existence of two subpopulations of excitatory neurons with opposite peri-ripple modulation patterns: one increases and the other decreases firing rate. These differences in peri-ripple spatiotemporal patterns of neocortical activity in sleep versus awake states might underlie the reported differences in the function of sleep versus awake ripples.

Fast network oscillations during non-REM sleep support memory consolidation

The neocortex is disconnected from the outside world during sleep, which has been hypothesized to be relevant for synaptic reorganization involved in memory consolidation. Fast network oscillations, such as hippocampal sharp-wave ripples, cortical ripples, and amygdalar high-frequency oscillations, are prominent during non-REM sleep. Although these oscillations are thought to be generated by local circuit mechanisms, their occurrence rates and amplitudes are modulated by thalamocortical spindles and neocortical slow oscillations during non-REM sleep, suggesting that fast network oscillations and slower oscillations cooperatively work to facilitate memory consolidation. This review discusses the recent progress in understanding the generation, coordination, and functional roles of fast network oscillations. Further, it outlines how fast network oscillations in distinct brain regions synergistically support memory consolidation and retrieval by hosting cross-regional coactivation of memory-related neuronal ensembles.

Hippocampal gamma and sharp wave/ripples mediate bidirectional interactions with cortical networks during sleep

During sleep, brain is bustling with activity: Different brain structures such as the hippocampus and the cortex interact, and this interplay is thought to be important to stabilize and reprocess memories, in the so-called systems consolidation. We show that during nonrapid eye movement sleep, cortical activity organizes in transient bursts of widely varying size, with a dynamic that may help remote areas communicate with one another. With a data-driven analysis of activity transients we identified three functional networks, one of which, namely the default mode network, most actively interacts with the hippocampus. This interaction is bidirectional and involves multiple patterns of hippocampal activity. We speculate that this information exchange loop subserves complex computational operations that are key to memory functionality.

Hippocampus–neocortex interactions during sleep are critical for memory processes: Hippocampally initiated replay contributes to memory consolidation in the neocortex and hippocampal sharp wave/ripples modulate cortical activity. Yet, the spatial and temporal patterns of this interaction are unknown. With voltage imaging, electrocorticography, and laminarly resolved hippocampal potentials, we characterized cortico-hippocampal signaling during anesthesia and nonrapid eye movement sleep. We observed neocortical activation transients, with statistics suggesting a quasi-critical regime, may be helpful for communication across remote brain areas. From activity transients, we identified, in a data-driven fashion, three functional networks. A network overlapping with the default mode network and centered on retrosplenial cortex was the most associated with hippocampal activity. Hippocampal slow gamma rhythms were strongly associated to neocortical transients, even more than ripples. In fact, neocortical activity predicted hippocampal slow gamma and followed ripples, suggesting that consolidation processes rely on bidirectional signaling between hippocampus and neocortex.

Retrosplenial and Hippocampal Synchrony during Retrieval of Old Memories in Macaques

Memory for events from the distant past relies on multiple brain regions, but little is known about the underlying neural dynamics that give rise to such abilities. We recorded neural activity in the hippocampus and retrosplenial cortex of two female rhesus macaques as they visually selected targets in year-old and newly acquired object-scene associations. Whereas hippocampal activity was unchanging with memory age, the retrosplenial cortex responded with greater magnitude alpha oscillations (10-15 Hz) and greater phase locking to memory-guided eye movements during retrieval of old events. A similar old-memory enhancement was observed in the anterior cingulate cortex but in a beta2/gamma band (28-35 Hz). In contrast, remote retrieval was associated with decreased gamma-band synchrony between the hippocampus and each neocortical area. The increasing retrosplenial alpha oscillation and decreasing hippocampocortical synchrony with memory age may signify a shift in frank memory allocation or, alternatively, changes in selection among distributed memory representations in the primate brain.SIGNIFICANCE STATEMENT Memory depends on multiple brain regions, whose involvement is thought to change with time. Here, we recorded neuronal population activity from the hippocampus and retrosplenial cortex as nonhuman primates searched for objects embedded in scenes. These memoranda were either newly presented or a year old. Remembering old material drove stronger oscillations in the retrosplenial cortex and led to a greater locking of neural activity to search movements. Remembering new material revealed stronger oscillatory synchrony between the hippocampus and retrosplenial cortex. These results suggest that with age, memories may come to rely more exclusively on neocortical oscillations for retrieval and search guidance and less on long-range coupling with the hippocampus.

Generalized Simultaneous Localization and Mapping (G-SLAM) as unification framework for natural and artificial intelligences: towards reverse engineering the hippocampal/entorhinal system and principles of high-level cognition

Simultaneous localization and mapping (SLAM) represents a fundamental problem for autonomous embodied systems, for which the hippocampal/entorhinal system (H/E-S) has been optimized over the course of evolution. We have developed a biologically-inspired SLAM architecture based on latent variable generative modeling within the Free Energy Principle and Active Inference (FEP-AI) framework, which affords flexible navigation and planning in mobile robots. We have primarily focused on attempting to reverse engineer H/E-S "design" properties, but here we consider ways in which SLAM principles from robotics may help us better understand nervous systems and emergent minds. After reviewing LatentSLAM and notable features of this control architecture, we consider how the H/E-S may realize these functional properties not only for physical navigation, but also with respect to high-level cognition understood as generalized simultaneous localization and mapping (G-SLAM). We focus on loop-closure, graph-relaxation, and node duplication as particularly impactful architectural features, suggesting these computational phenomena may contribute to understanding cognitive insight (as proto-causal-inference), accommodation (as integration into existing schemas), and assimilation (as category formation). All these operations can similarly be describable in terms of structure/category learning on multiple levels of abstraction. However, here we adopt an ecological rationality perspective, framing H/E-S functions as orchestrating SLAM processes within both concrete and abstract hypothesis spaces. In this navigation/search process, adaptive cognitive equilibration between assimilation and accommodation involves balancing tradeoffs between exploration and exploitation; this dynamic equilibrium may be near optimally realized in FEP-AI, wherein control systems governed by expected free energy objective functions naturally balance model simplicity and accuracy. With respect to structure learning, such a balance would involve constructing models and categories that are neither too inclusive nor exclusive. We propose these (generalized) SLAM phenomena may represent some of the most impactful sources of variation in cognition both within and between individuals, suggesting that modulators of H/E-S functioning may potentially illuminate their adaptive significances as fundamental cybernetic control parameters. Finally, we discuss how understanding H/E-S contributions to G-SLAM may provide a unifying framework for high-level cognition and its potential realization in artificial intelligences.

Local neuronal excitation and global inhibition during epileptic fast ripples in humans

Understanding the neuronal basis of epileptic activity is a major challenge in neurology. Cellular integration into larger scale networks is all the more challenging. In the local field potential, interictal epileptic discharges can be associated with fast ripples (200-600 Hz), which are a promising marker of the epileptogenic zone. Yet, how neuronal populations in the epileptogenic zone and in healthy tissue are affected by fast ripples remain unclear. Here, we used a novel 'hybrid' macro-micro depth electrode in nine drug-resistant epileptic patients, combining classic depth recording of local field potentials (macro-contacts) and two or three tetrodes (four micro-wires bundled together) enabling up to 15 neurons in local circuits to be simultaneously recorded. We characterized neuronal responses (190 single units) with the timing of fast ripples (2233 fast ripples) on the same hybrid and other electrodes that target other brain regions. Micro-wire recordings reveal signals that are not visible on macro-contacts. While fast ripples detected on the closest macro-contact to the tetrodes were always associated with fast ripples on the tetrodes, 82% of fast ripples detected on tetrodes were associated with detectable fast ripples on the nearest macro-contact. Moreover, neuronal recordings were taken in and outside the epileptogenic zone of implanted epileptic subjects and they revealed an interlay of excitation and inhibition across anatomical scales. While fast ripples were associated with increased neuronal activity in very local circuits only, they were followed by inhibition in large-scale networks (beyond the epileptogenic zone, even in healthy cortex). Neuronal responses to fast ripples were homogeneous in local networks but differed across brain areas. Similarly, post-fast ripple inhibition varied across recording locations and subjects and was shorter than typical inter-fast ripple intervals, suggesting that this inhibition is a fundamental refractory process for the networks. These findings demonstrate that fast ripples engage local and global networks, including healthy tissue, and point to network features that pave the way for new diagnostic and therapeutic strategies. They also reveal how even localized pathological brain dynamics can affect a broad range of cognitive functions.

Flexibility of memory for future-oriented cognition

Memories of daily experiences contain incidental details unique to each experience as well as common latent patterns shared with others. Neural representations focusing on the latter aspect can be reinstated by similar new experiences even though their perceptual features do not match the original experiences perfectly. Such flexible memory use allows for faster learning and better decision-making in novel situations. Here, I review evidence from rodent and primate electrophysiological studies to discuss how memory flexibility is implemented in the spiking activity of neuronal ensembles. These findings uncovered innate and learned coding properties and their potential refinement during sleep that support flexible integration and application of memories for better future adaptation.

Replay, the default mode network and the cascaded memory systems model

The spontaneous replay of patterns of activity related to past experiences and memories is a striking feature of brain activity, as is the coherent activation of sets of brain areas - particularly those comprising the default mode network (DMN) - during rest. We propose that these two phenomena are strongly intertwined and that their potential functions overlap. In the 'cascaded memory systems model' that we outline here, we hypothesize that the DMN forms the backbone for the propagation of replay, mediating interactions between the hippocampus and the neocortex that enable the consolidation of new memories. The DMN may also independently ignite replay cascades, which support reactivation of older memories or high-level semantic representations. We suggest that transient cortical activations, inducing long-range correlations across the neocortex, are a key mechanism supporting a hierarchy of representations that progresses from simple percepts to semantic representations of causes and, finally, to whole episodes.

Cell-type-specific silence in thalamocortical circuits precedes hippocampal sharp-wave ripples

Evidence suggests that the hippocampus conveys memory-related neural patterns across distributed cortical circuits during high-frequency oscillations called sharp-wave ripples (SWRs). We investigate how circuit activity in the retrosplenial cortex (RSC), a primary hippocampal target, could aid in processing SWR-related input. Using patch-clamp recordings from awake mice, we find that SWR-aligned membrane potential modulation is widespread but weak, and that spiking responses are sparse. However, using cell-type-specific two-photon Ca²⁺ imaging and optogenetics, we show that, 1-2 s before SWRs, superficial inhibition and thalamocortical input in RSC is reduced. We propose that pyramidal dendrites experience decreased local inhibition and subcortical interference in a seconds-long time window preceding SWRs. This may aid communication of weak and sparse SWR-aligned excitation between the hippocampus and neocortex and promote the strengthening of memory-related connections.

Simultaneous Cellular Imaging, Electrical Recording and Stimulation of Hippocampal Activity in Freely Behaving Mice

Hippocampal sharp-wave ripple activity (SWRs) and the associated replay of neural activity patterns are well-known for their role in memory consolidation. This activity has been studied using electrophysiological approaches, as high temporal resolution is required to recognize SWRs in the neuronal signals. However, it has been difficult to analyze the individual contribution of neurons to task-specific SWRs, because it is hard to track neurons across a long time with electrophysiological recording. In this study, we recorded local field potential (LFP) signals in the hippocampal CA1 of freely behaving mice and simultaneously imaged calcium signals in contralateral CA1 to leverage the advantages of both electrophysiological and imaging approaches. We manufactured a custom-designed microdrive array and targeted tetrodes to the left hippocampus CA1 for LFP recording and applied electrical stimulation in the ventral hippocampal commissure (VHC) for closed-loop disruption of SWRs. Neuronal population imaging in the right hippocampal CA1 was performed using a miniature fluorescent microscope (Miniscope) and a genetically encoded calcium indicator. As SWRs show highly synchronized bilateral occurrence, calcium signals of SWR-participating neurons could be identified and tracked in spontaneous or SWR-disrupted conditions. Using this approach, we identified a subpopulation of CA1 neurons showing synchronous calcium elevation to SWRs. Our results showed that SWR-related calcium transients are more disrupted by electrical stimulation than non-SWR-related calcium transients, validating the capability of the system to detect and disrupt SWRs. Our dual recording method can be used to uncover the dynamic participation of individual neurons in SWRs and replay over extended time windows.