The Nonclassic Psychedelic Ibogaine Disrupts Cognitive Maps.

Background: The ability of psychedelic compounds to profoundly alter mental function has been long known, but the underlying changes in cellular-level information encoding remain poorly understood. Methods: We used two-photon microscopy to record from the retrosplenial cortex in head-fixed mice running on a treadmill before and after injection of the nonclassic psychedelic ibogaine (40 mg/kg intraperitoneally). Results: We found that the cognitive map, formed by the representation of position encoded by ensembles of individual neurons in the retrosplenial cortex, was destabilized by ibogaine when mice had to infer position between tactile landmarks. This corresponded with increased neural activity rates, loss of correlation structure, and increased responses to cues. Ibogaine had surprisingly little effect on the size-frequency distribution of network activity events, suggesting that signal propagation within the retrosplenial cortex was largely unaffected. Conclusions: Taken together, these data support proposals that compounds with psychedelic properties disrupt representations that are important for constraining neocortical activity, thereby increasing the entropy of neural signaling. Furthermore, the loss of expected position encoding between landmarks recapitulated effects of hippocampal impairment, suggesting that disruption of cognitive maps or other hippocampal processing may be a contributing mechanism of discoordinated neocortical activity in psychedelic states.

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.

An Integrated Platform for In Vivo Electrophysiology in Spatial Cognition Experiments.

Spatial cognition research requires behavioral paradigms that can distinguish between different navigational elements, such as allocentric (map-like) navigation and egocentric (e.g., body centered) navigation. To fill this need, we developed a flexible experimental platform that can be quickly modified without the need for significant changes to software and hardware. In this paper, we present this inexpensive and flexible behavioral platform paired with software which we are making freely available. Our behavioral platform serves as the foundation for a range of experiments, and although developed for assessing spatial cognition, it also has applications in the nonspatial domain of behavioral testing. There are two components of the software platform, "Maze" and "Stim Trigger." While intended as a general platform, presently both programs can work in conjunction with Neuralynx and Open Ephys electrophysiology acquisition systems, allowing for precise time stamping of neural events. The Maze program includes functionality for automatic reward delivery based on user defined zones. "Stim Trigger" permits control of brain stimulation via any equipment that can be paired with an Arduino board. We seek to share our software and leverage the potential by expanding functionality in the future to meet the needs of a larger community of researchers.

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.

Consolidation of cellular memory representations in superficial neocortex.

Systems-level memory consolidation, a key concept in memory research, involves the conversion of memories that depend on the hippocampus for their formation into efficient hippocampus-independent forms, presumably encoded by cortico-cortical connections. Yet, little is understood about the nature of consolidated neural codes at the cellular ensemble level. Mice require an intact hippocampus for "virtual" spatial learning and to develop neocortical representations of the corresponding experiences. We find that, whereas a novel virtual environment is neither learned nor represented in superficial cortex following severe damage to hippocampus, pre-operatively learned memories and their corresponding sparse and widespread neural ensemble representations in cortical layers II-III are preserved, a sine qua non of memory consolidation. These findings provide a new window for future study of the cellular mechanisms of memory consolidation.

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.

A consensus statement on detection of hippocampal sharp wave ripples and differentiation from other fast oscillations.

Decades of rodent research have established the role of hippocampal sharp wave ripples (SPW-Rs) in consolidating and guiding experience. More recently, intracranial recordings in humans have suggested their role in episodic and semantic memory. Yet, common standards for recording, detection, and reporting do not exist. Here, we outline the methodological challenges involved in detecting ripple events and offer practical recommendations to improve separation from other high-frequency oscillations. We argue that shared experimental, detection, and reporting standards will provide a solid foundation for future translational discovery.

A rodent obstacle course procedure controls delivery of enrichment and enhances complex cognitive functions.

Enrichment in rodents affects brain structure, improves behavioral performance, and is neuroprotective. Similarly, in humans, according to the cognitive reserve concept, enriched experience is functionally protective against neuropathology. Despite this parallel, the ability to translate rodent studies to human clinical situations is limited. This limitation is likely due to the simple cognitive processes probed in rodent studies and the inability to control, with existing methods, the degree of rodent engagement with enrichment material. We overcome these two difficulties with behavioral tasks that probe, in a fine-grained manner, aspects of higher-order cognition associated with deterioration with aging and dementia, and a new enrichment protocol, the 'Obstacle Course' (OC), which enables controlled enrichment delivery, respectively. Together, these two advancements will enable better specification (and comparisons) of the nature of impairments in animal models of complex mental disorders and the potential for remediation from various types of intervention (e.g., enrichment, drugs). We found that two months of OC enrichment produced substantial and sustained enhancements in categorization memory, perceptual object invariance, and cross-modal sensory integration in mice. We also tested mice on behavioral tasks previously shown to benefit from traditional enrichment: spontaneous object recognition, object location memory, and pairwise visual discrimination. OC enrichment improved performance relative to standard housing on all six tasks and was in most cases superior to conventional home-cage enrichment and exercise track groups.

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.

Neurons learn by predicting future activity.

Understanding how the brain learns may lead to machines with human-like intellectual capacities. It was previously proposed that the brain may operate on the principle of predictive coding. However, it is still not well understood how a predictive system could be implemented in the brain. Here we demonstrate that the ability of a single neuron to predict its future activity may provide an effective learning mechanism. Interestingly, this predictive learning rule can be derived from a metabolic principle, where neurons need to minimize their own synaptic activity (cost), while maximizing their impact on local blood supply by recruiting other neurons. We show how this mathematically derived learning rule can provide a theoretical connection between diverse types of brain-inspired algorithms, thus, offering a step toward development of a general theory of neuronal learning. We tested this predictive learning rule in neural network simulations and in data recorded from awake animals. Our results also suggest that spontaneous brain activity provides "training data" for neurons to learn to predict cortical dynamics. Thus, the ability of a single neuron to minimize surprise: i.e. the difference between actual and expected activity, could be an important missing element to understand computation in the brain.

Learning in deep neural networks and brains with similarity-weighted interleaved learning.

Understanding how the brain learns throughout a lifetime remains a long-standing challenge. In artificial neural networks (ANNs), incorporating novel information too rapidly results in catastrophic interference, i.e., abrupt loss of previously acquired knowledge. Complementary Learning Systems Theory (CLST) suggests that new memories can be gradually integrated into the neocortex by interleaving new memories with existing knowledge. This approach, however, has been assumed to require interleaving all existing knowledge every time something new is learned, which is implausible because it is time-consuming and requires a large amount of data. We show that deep, nonlinear ANNs can learn new information by interleaving only a subset of old items that share substantial representational similarity with the new information. By using such similarity-weighted interleaved learning (SWIL), ANNs can learn new information rapidly with a similar accuracy level and minimal interference, while using a much smaller number of old items presented per epoch (fast and data-efficient). SWIL is shown to work with various standard classification datasets (Fashion-MNIST, CIFAR10, and CIFAR100), deep neural network architectures, and in sequential learning frameworks. We show that data efficiency and speedup in learning new items are increased roughly proportionally to the number of nonoverlapping classes stored in the network, which implies an enormous possible speedup in human brains, which encode a high number of separate categories. Finally, we propose a theoretical model of how SWIL might be implemented in the brain.

Route selection with a cognitive map.

In this issue of Neuron, Widloski and Foster (2022) show that, in a complex maze with changing barrier configurations, rat hippocampal neurons maintain their location-specific firing but learn to generate activity sequences representing possible routes to rewards, that respect the locations of barriers, and to rapidly adapt to barrier reconfiguration.

Spatiotemporal structure of sensory-evoked and spontaneous activity revealed by mesoscale imaging in anesthetized and awake mice.

Stimuli-evoked and spontaneous brain activity propagates across the cortex in diverse spatiotemporal patterns. Despite extensive studies, the relationship between spontaneous and evoked activity is poorly understood. We investigate this relationship by comparing the amplitude, speed, direction, and complexity of propagation trajectories of spontaneous and evoked activity elicited with visual, auditory, and tactile stimuli using mesoscale wide-field imaging in mice. For both spontaneous and evoked activity, the speed and direction of propagation is modulated by the amplitude. However, spontaneous activity has a higher complexity of the propagation trajectories. For low stimulus strengths, evoked activity amplitude and speed is similar to that of spontaneous activity but becomes dissimilar at higher stimulus strengths. These findings are consistent with observations that primary sensory areas receive widespread inputs from other cortical regions, and during rest, the cortex tends to reactivate traces of complex multisensory experiences that might have occurred in exhibition of different behaviors.

Coupling between slow waves and sharp-wave ripples engages distributed neural activity during sleep in humans.

Hippocampal-dependent memory consolidation during sleep is hypothesized to depend on the synchronization of distributed neuronal ensembles, organized by the hippocampal sharp-wave ripples (SWRs, 80 to 150 Hz), subcortical/cortical slow-wave activity (SWA, 0.5 to 4 Hz), and sleep spindles (SP, 7 to 15 Hz). However, the precise role of these interactions in synchronizing subcortical/cortical neuronal activity is unclear. Here, we leverage intracranial electrophysiological recordings from the human hippocampus, amygdala, and temporal and frontal cortices to examine activity modulation and cross-regional coordination during SWRs. Hippocampal SWRs are associated with widespread modulation of high-frequency activity (HFA, 70 to 200 Hz), a measure of local neuronal activation. This peri-SWR HFA modulation is predicted by the coupling between hippocampal SWRs and local subcortical/cortical SWA or SP. Finally, local cortical SWA phase offsets and SWR amplitudes predicted functional connectivity between the frontal and temporal cortex during individual SWRs. These findings suggest a selection mechanism wherein hippocampal SWR and cortical slow-wave synchronization governs the transient engagement of distributed neuronal populations supporting hippocampal-dependent memory consolidation.

Spatial Information Encoding across Multiple Neocortical Regions Depends on an Intact Hippocampus.

There has been considerable research showing populations of neurons encoding for different aspects of space in the brain. Recently, several studies using two-photon calcium imaging and virtual navigation have identified "spatially" modulated neurons in the posterior cortex. We enquire here whether the presence of such spatial representations may be a cortex-wide phenomenon and, if so, whether these representations can be organized in the absence of the hippocampus. To this end, we imaged the dorsal cortex of mice running on a treadmill populated with tactile cues. A high percentage (40-80%) of the detected neurons exhibited sparse, spatially localized activity, with activity fields uniformly localized over the track. The development of this location specificity was impaired by hippocampal damage. Thus, there is a substantial population of neurons distributed widely over the cortex that collectively form a continuous representation of the explored environment, and hippocampal outflow is necessary to organize this phenomenon.SIGNIFICANCE STATEMENT Increasing evidence points to the role of the neocortex in encoding spatial information. Whether this feature is linked to hippocampal functions is largely unknown. Here, we systematically surveyed multiple regions in the dorsal cortex of the same animal for the presence of signals encoding for spatial position. We described populations of cortical neurons expressing sequential patterns of activity localized in space in primary, secondary, and associational areas. Furthermore, we showed that the formation of these spatial representations was impacted by hippocampal lesion. Our results indicate that hippocampal inputs are necessary to maintain a precise cortical representation of space.

Assessment of Sleep, K-Complexes, and Sleep Spindles in a T21 Light-Dark Cycle.

Circadian rhythm misalignment has a deleterious impact on the brain and the body. In rats, exposure to a 21-hour day length impairs hippocampal dependent memory. Sleep, and particularly K-complexes and sleep spindles in the cortex, have been hypothesized to be involved in memory consolidation. Altered K-complexes, sleep spindles, or interaction between the cortex and hippocampus could be a mechanism for the memory consolidation failure but has yet to be assessed in any circadian misalignment paradigm. In the current study, continuous local field potential recordings from five rats were used to assess the changes in aspects of behavior and sleep, including wheel running activity, quiet wakefulness, motionless sleep, slow wave sleep, REM sleep, K-complexes and sleep spindles, in rats exposed to six consecutive days of a T21 light-dark cycle (L9:D12). Except for a temporal redistribution of sleep and activity during the T21, there were no changes in period, or total amount for any aspect of sleep or activity. These data suggest that the memory impairment elicited from 6 days of T21 exposure is likely not due to changes in sleep architecture. It remains possible that hippocampal plasticity is affected by experiencing light when subjective circadian phase is calling for dark. However, if there is a reduction in hippocampal plasticity, changes in sleep appear not to be driving this effect.

Limitations of the GENSAT Egr1-EGFP transgenic mouse strain for neural circuit activity mapping.

Transgenic immediate-early gene reporter mouse strains are valuable tools for studying activity-dependent neural cell populations in vivo. However, routine characterization of the Gene Expression Nervous System Atlas (GENSAT) "Egr1-EGFP" reporter mouse strain produced results that were highly inconsistent with endogenous Egr1 expression. Activity-dependent EGFP expression was not observed, and EGFP protein did not co-localize with native Egr1 protein. This precautionary study outlines the limitations of the Egr1-EGFP transgenic line as a tool to study the activity-dependent expression of Egr1 and emphasizes the necessity of taking into account the potential loss of regulatory elements, stability determinants, or translational modulation in transgenic reporter strains.

Impaired Hippocampal-Cortical Interactions during Sleep in a Mouse Model of Alzheimer's Disease.

Spatial learning is impaired in humans with preclinical Alzheimer's disease (AD). We reported similar impairments in 3xTg-AD mice learning a spatial reorientation task. Memory reactivation during sleep is critical for learning-related plasticity, and memory consolidation is correlated with hippocampal sharp wave ripple (SWR) density, cortical delta waves (DWs), cortical spindles, and the temporal coupling of these events-postulated as physiological substrates for memory consolidation. Further, hippocampal-cortical discoordination is prevalent in individuals with AD. Thus, we hypothesized that impaired memory consolidation mechanisms in hippocampal-cortical networks could account for spatial memory deficits. We assessed sleep architecture, SWR-DW dynamics, and memory reactivation in a mouse model of tauopathy and amyloidosis implanted with a recording array targeting isocortex and hippocampus. Mice underwent daily recording sessions of rest-task-rest while learning the spatial reorientation task. We assessed memory reactivation by matching activity patterns from the approach to the unmarked reward zone to patterns during slow-wave sleep (SWS). AD mice had more SWS, but reduced SWR density. The increased SWS compensated for reduced SWR density so there was no reduction in SWR number. In control mice, spindles were phase-coupled with DWs, and hippocampal SWR-cortical DW coupling was strengthened in post-task sleep and was correlated with performance on the spatial reorientation task the following day. However, in AD mice, SWR-DW and spindle-DW coupling were impaired. Thus, reduced SWR-DW coupling may cause impaired learning in AD, and spindle-DW coupling during short rest-task-rest sessions may serve as a biomarker for early AD-related changes in these brain dynamics.