Time cells in the hippocampus: a new dimension for mapping memories

Cognitive deficits and course of recovery in transient global amnesia: a systematic review

OBJECTIVE

Published evidence suggests that cognitive impairment during a TGA (transient global amnesia) spell may not be confined to episodic memory. We undertook a systematic review to determine the pattern of cognitive deficits during a TGA episode. As a secondary objective, we aimed to delineate the course of cognitive recovery.

METHODS

MEDLINE, EMBASE, CENTRAL, and Google scholar were systematically searched up to October 2023. Observational controlled studies including 10 or more TGA patients (Hodges and Warlow criteria) were retrieved. Data from case-control, cross-sectional, and cohort studies were reviewed and qualitatively synthesized.

RESULTS

Literature search yielded 1302 articles. After the screening of titles and abstracts, 115 full texts were retrieved and 17 of them were included in the present systematic review. During the acute phase, spatiotemporal disorientation, dense anterograde and variable retrograde amnesia, semantic memory retrieval difficulties, and working memory deficits comprised the neuropsychological profile of patients with TGA. Visuospatial abilities, attention and psychomotor speed, semantic memory, confrontation naming, and other measures of executive function (apart from semantic fluency and working memory) were consistently found normal. In the course of recovery, after the resolution of repetitive questioning, the restoration of spatiotemporal orientation follows, working memory and semantic memory retrieval ensue, while episodic memory impairment persists for longer. Meticulous evaluations may reveal subtle residual memory (especially recognition) deficits even after 24 h.

CONCLUSIONS

Μemory impairment, spatiotemporal disorientation, and working memory deficits constitute the pattern of cognitive impairment during a TGA spell. Residual memory deficits may persist even after 24 h.

Learning sequence attractors in recurrent networks with hidden neurons

The brain is targeted for processing temporal sequence information. It remains largely unclear how the brain learns to store and retrieve sequence memories. Here, we study how recurrent networks of binary neurons learn sequence attractors to store predefined pattern sequences and retrieve them robustly. We show that to store arbitrary pattern sequences, it is necessary for the network to include hidden neurons even though their role in displaying sequence memories is indirect. We develop a local learning algorithm to learn sequence attractors in the networks with hidden neurons. The algorithm is proven to converge and lead to sequence attractors. We demonstrate that the network model can store and retrieve sequences robustly on synthetic and real-world datasets. We hope that this study provides new insights in understanding sequence memory and temporal information processing in the brain.

Learning temporal relationships between symbols with Laplace Neural Manifolds

Firing across populations of neurons in many regions of the mammalian brain maintains a temporal memory, a neural timeline of the recent past. Behavioral results demonstrate that people can both remember the past and anticipate the future over an analogous internal timeline. This paper presents a mathematical framework for building this timeline of the future. We assume that the input to the system is a time series of symbols-sparse tokenized representations of the present-in continuous time. The goal is to record pairwise temporal relationships between symbols over a wide range of time scales. We assume that the brain has access to a temporal memory in the form of the real Laplace transform. Hebbian associations with a diversity of synaptic time scales are formed between the past timeline and the present symbol. The associative memory stores the convolution between the past and the present. Knowing the temporal relationship between the past and the present allows one to infer relationships between the present and the future. With appropriate normalization, this Hebbian associative matrix can store a Laplace successor representation and a Laplace predecessor representation from which measures of temporal contingency can be evaluated. The diversity of synaptic time constants allows for learning of non-stationary statistics as well as joint statistics between triplets of symbols. This framework synthesizes a number of recent neuroscientific findings including results from dopamine neurons in the mesolimbic forebrain.

2P-NucTag: on-demand phototagging for molecular analysis of functionally identified cortical neurons

Neural circuits are characterized by genetically and functionally diverse cell types. A mechanistic understanding of circuit function is predicated on linking the genetic and physiological properties of individual neurons. However, it remains highly challenging to map the transcriptional properties to functionally heterogeneous neuronal subtypes in mammalian cortical circuits in vivo. Here, we introduce a high-throughput two-photon nuclear phototagging (2P-NucTag) approach optimized for on-demand and indelible labeling of single neurons via a photoactivatable red fluorescent protein following in vivo functional characterization in behaving mice. We demonstrate the utility of this function-forward pipeline by selectively labeling and transcriptionally profiling previously inaccessible 'place' and 'silent' cells in the mouse hippocampus. Our results reveal unexpected differences in gene expression between these hippocampal pyramidal neurons with distinct spatial coding properties. Thus, 2P-NucTag opens a new way to uncover the molecular principles that govern the functional organization of neural circuits.

Time cells in the retrosplenial cortex

The retrosplenial cortex (RSC) is a key component of the brain's memory systems, with anatomical connections to the hippocampus, anterior thalamus, and entorhinal cortex. This circuit has been implicated in episodic memory and many of these structures have been shown to encode temporal information, which is critical for episodic memory. For example, hippocampal time cells reliably fire during specific segments of time during a delay period. Although RSC lesions are known to disrupt temporal memory, time cells have not been observed there. In this study, we reanalyzed archival RSC neuronal firing data during the intertrial delay period from two previous experiments involving different behavioral tasks, a blocked alternation task and a cued T-maze task. For the blocked alternation task, rats were required to approach the east or west arm of a plus maze for reward during different blocks of trials. Because the reward locations were not cued, the rat had to remember the goal location for each trial. In the cued T-maze task, the reward location was explicitly cued with a light and the rats simply had to approach the light for reward, so there was no requirement to hold a memory during the intertrial delay. Time cells were prevalent in the blocked alternation task, and most time cells clearly differentiated the east and west trials. We also found that RSC neurons could exhibit off-response time fields, periods of reliably inhibited firing. Time cells were also observed in the cued T-maze, but they were less prevalent and they did not differentiate left and right trials as well as in the blocked alternation task, suggesting that RSC time cells are sensitive to the memory demands of the task. These results suggest that temporal coding is a prominent feature of RSC firing patterns, consistent with an RSC role in episodic memory.

Non-spatial hippocampal behavioral timescale synaptic plasticity during working memory is gated by entorhinal inputs

Behavioral timescale synaptic plasticity (BTSP) is a form of synaptic potentiation where the occurrence of a single large plateau potential in CA1 hippocampal neurons leads to the formation of reliable place fields during spatial learning tasks. We asked whether BTSP could also be a plasticity mechanism for generation of non-spatial responses in the hippocampus and what roles the medial and lateral entorhinal cortex (MEC and LEC) play in driving non-spatial BTSP. By performing simultaneous calcium imaging of dorsal CA1 neurons and chemogenetic inhibition of LEC or MEC while mice performed an olfactory working memory task' we discovered BTSP-like events which formed stable odor-specific fields. Critically' the success rate of calcium events generating a significant odor-field increased with event amplitude' and large events exhibited asymmetrical formation with the newly formed odor-fields preceding the timepoint of their induction event. We found that MEC and LEC play distinct roles in modulating BTSP: MEC inhibition reduced the frequency of large calcium events' while LEC inhibition reduced the success rate of odor-field generation. Using two-photon calcium imaging of LEC and MEC temporammonic axons projecting to CA1 we found that LEC projections to CA1 were strongly odor selective even early in task learning' while MEC projection odor-selectivity increased with task learning but remained weaker than LEC. Finally' we found that LEC and MEC inhibition both slowed representational drift of odor representations in CA1 across 48 hours. Altogether' odor-specific information from LEC and strong odor-timed activity from MEC are crucial for driving BTSP in CA1 which is a synaptic plasticity mechanism for generation of both spatial and non-spatial responses in the hippocampus that may play a role in explaining representational drift and one-shot learning of non-spatial information.

Predictive sequence learning in the hippocampal formation

The hippocampus receives sequences of sensory inputs from the cortex during exploration and encodes the sequences with millisecond precision. We developed a predictive autoencoder model of the hippocampus including the trisynaptic and monosynaptic circuits from the entorhinal cortex (EC). CA3 was trained as a self-supervised recurrent neural network to predict its next input. We confirmed that CA3 is predicting ahead by analyzing the spike coupling between simultaneously recorded neurons in the dentate gyrus, CA3, and CA1 of the mouse hippocampus. In the model, CA1 neurons signal prediction errors by comparing CA3 predictions to the next direct EC input. The model exhibits the rapid appearance and slow fading of CA1 place cells and displays replay and phase precession from CA3. The model could be learned in a biologically plausible way with error-encoding neurons. Similarities between the hippocampal and thalamocortical circuits suggest that such computation motif could also underlie self-supervised sequence learning in the cortex.

Scene construction processes in the anterior hippocampus during temporal episodic memory retrieval

Although the hippocampus has been implicated in both the temporal organization of memories and association of scene elements, some theoretical accounts posit that the role of the hippocampus in episodic memory is largely atemporal. In this study, we set out to explore this discrepancy by identifying hippocampal activity patterns related to scene construction while participants performed a temporal order memory task. Participants in the fMRI scanner were shown a sequence of photographs, each consisting of a central object and a contextual background scene. On each retrieval trial, participants were shown a pair of the original photographs (FULL), objects from the scenes without the background (OBJ), or background contexts without the main foreground object (BACK). In the temporal order judgment (TOJ) task, participants judged the temporal order of the pair of scenes; in the Viewing trials, two identical scenes were shown without any task. First, we found that the anterior hippocampus-particularly the CA1 and subiculum-showed similar patterns of activation between the BACK and OBJ conditions, suggesting that scene construction occurred spontaneously during both TOJ and Viewing. Furthermore, neural markers of scene construction in the anterior hippocampus did not apply to incorrect trials, showing that successful temporal memory retrieval was functionally linked to scene construction. In the cortex, time-processing areas, such as the supplementary motor area and the precuneus, and scene-processing areas, such as the parahippocampal cortex, were activated and functionally connected with the hippocampus. Together, these results support the view that the hippocampus is concurrently involved in scene construction and temporal organization of memory and propose a model of hippocampal episodic memory that takes both processes into account.

Learning, Fast and Slow: Single- and Many-Shot Learning in the Hippocampus

The hippocampus is critical for memory and spatial navigation. The ability to map novel environments, as well as more abstract conceptual relationships, is fundamental to the cognitive flexibility that humans and other animals require to survive in a dynamic world. In this review, we survey recent advances in our understanding of how this flexibility is implemented anatomically and functionally by hippocampal circuitry, during both active exploration (online) and rest (offline). We discuss the advantages and limitations of spike timing-dependent plasticity and the more recently discovered behavioral timescale synaptic plasticity in supporting distinct learning modes in the hippocampus. Finally, we suggest complementary roles for these plasticity types in explaining many-shot and single-shot learning in the hippocampus and discuss how these rules could work together to support the learning of cognitive maps.

A theory of hippocampal function: New developments

We develop further here the only quantitative theory of the storage of information in the hippocampal episodic memory system and its recall back to the neocortex. The theory is upgraded to account for a revolution in understanding of spatial representations in the primate, including human, hippocampus, that go beyond the place where the individual is located, to the location being viewed in a scene. This is fundamental to much primate episodic memory and navigation: functions supported in humans by pathways that build 'where' spatial view representations by feature combinations in a ventromedial visual cortical stream, separate from those for 'what' object and face information to the inferior temporal visual cortex, and for reward information from the orbitofrontal cortex. Key new computational developments include the capacity of the CA3 attractor network for storing whole charts of space; how the correlations inherent in self-organizing continuous spatial representations impact the storage capacity; how the CA3 network can combine continuous spatial and discrete object and reward representations; the roles of the rewards that reach the hippocampus in the later consolidation into long-term memory in part via cholinergic pathways from the orbitofrontal cortex; and new ways of analysing neocortical information storage using Potts networks.

The memory systems of the human brain and generative artificial intelligence

Generative Artificial Intelligence foundation models (for example Generative Pre-trained Transformer - GPT - models) can generate the next token given a sequence of tokens. How can this 'generative AI' be compared with the 'real' intelligence of the human brain, when for example a human generates a whole memory in response to an incomplete retrieval cue, and then generates further prospective thoughts? Here these two types of generative intelligence, artificial in machines and real in the human brain are compared, and it is shown how when whole memories are generated by hippocampal recall in response to an incomplete retrieval cue, what the human brain computes, and how it computes it, are very different from generative AI. Key differences are the use of local associative learning rules in the hippocampal memory system, and of non-local backpropagation of error learning in AI. Indeed, it is argued that the whole operation of the human brain is performed computationally very differently to what is implemented in generative AI. Moreover, it is emphasized that the primate including human hippocampal system includes computations about spatial view and where objects and people are in scenes, whereas in rodents the emphasis is on place cells and path integration by movements between places. This comparison with generative memory and processing in the human brain has interesting implications for the further development of generative AI and for neuroscience research.

Mental navigation in the primate entorhinal cortex

A cognitive map is a suitably structured representation that enables novel computations using previous experience; for example, planning a new route in a familiar space1. Work in mammals has found direct evidence for such representations in the presence of exogenous sensory inputs in both spatial2,3 and non-spatial domains4-10. Here we tested a foundational postulate of the original cognitive map theory1,11: that cognitive maps support endogenous computations without external input. We recorded from the entorhinal cortex of monkeys in a mental navigation task that required the monkeys to use a joystick to produce one-dimensional vectors between pairs of visual landmarks without seeing the intermediate landmarks. The ability of the monkeys to perform the task and generalize to new pairs indicated that they relied on a structured representation of the landmarks. Task-modulated neurons exhibited periodicity and ramping that matched the temporal structure of the landmarks and showed signatures of continuous attractor networks12,13. A continuous attractor network model of path integration14 augmented with a Hebbian-like learning mechanism provided an explanation of how the system could endogenously recall landmarks. The model also made an unexpected prediction that endogenous landmarks transiently slow path integration, reset the dynamics and thereby reduce variability. This prediction was borne out in a reanalysis of firing rate variability and behaviour. Our findings link the structured patterns of activity in the entorhinal cortex to the endogenous recruitment of a cognitive map during mental navigation.

Neuronal activation sequences in lateral prefrontal cortex encode visuospatial working memory during virtual navigation

Working memory (WM) is the ability to maintain and manipulate information 'in mind'. The neural codes underlying WM have been a matter of debate. We simultaneously recorded the activity of hundreds of neurons in the lateral prefrontal cortex of male macaque monkeys during a visuospatial WM task that required navigation in a virtual 3D environment. Here, we demonstrate distinct neuronal activation sequences (NASs) that encode remembered target locations in the virtual environment. This NAS code outperformed the persistent firing code for remembered locations during the virtual reality task, but not during a classical WM task using stationary stimuli and constraining eye movements. Finally, blocking NMDA receptors using low doses of ketamine deteriorated the NAS code and behavioral performance selectively during the WM task. These results reveal the versatility and adaptability of neural codes supporting working memory function in the primate lateral prefrontal cortex.

Continuous decision to wait for a future reward is guided by fronto-hippocampal anticipatory dynamics

Deciding whether to wait for a future reward is crucial for surviving in an uncertain world. While seeking rewards, agents anticipate a reward in the present environment and constantly face a trade-off between staying in their environment or leaving it. It remains unclear, however, how humans make continuous decisions in such situations. Here, we show that anticipatory activity in the anterior prefrontal cortex, ventrolateral prefrontal cortex, and hippocampus underpins continuous stay-leave decision-making. Participants awaited real liquid rewards available after tens of seconds, and their continuous decision was tracked by dynamic brain activity associated with the anticipation of a reward. Participants stopped waiting more frequently and sooner after they experienced longer delays and received smaller rewards. When the dynamic anticipatory brain activity was enhanced in the anterior prefrontal cortex, participants remained in their current environment, but when this activity diminished, they left the environment. Moreover, while experiencing a delayed reward in a novel environment, the ventrolateral prefrontal cortex and hippocampus showed anticipatory activity. Finally, the activity in the anterior prefrontal cortex and ventrolateral prefrontal cortex was enhanced in participants adopting a leave strategy, whereas those remaining stationary showed enhanced hippocampal activity. Our results suggest that fronto-hippocampal anticipatory dynamics underlie continuous decision-making while anticipating a future reward.

Integrating and fragmenting memories under stress and alcohol

Stress can powerfully influence the way we form memories, particularly the extent to which they are integrated or situated within an underlying spatiotemporal and broader knowledge architecture. These different representations in turn have significant consequences for the way we use these memories to guide later behavior. Puzzlingly, although stress has historically been argued to promote fragmentation, leading to disjoint memory representations, more recent work suggests that stress can also facilitate memory binding and integration. Understanding the circumstances under which stress fosters integration will be key to resolving this discrepancy and unpacking the mechanisms by which stress can shape later behavior. Here, we examine memory integration at multiple levels: linking together the content of an individual experience, threading associations between related but distinct events, and binding an experience into a pre-existing schema or sense of causal structure. We discuss neural and cognitive mechanisms underlying each form of integration as well as findings regarding how stress, aversive learning, and negative affect can modulate each. In this analysis, we uncover that stress can indeed promote each level of integration. We also show how memory integration may apply to understanding effects of alcohol, highlighting extant clinical and preclinical findings and opportunities for further investigation. Finally, we consider the implications of integration and fragmentation for later memory-guided behavior, and the importance of understanding which type of memory representation is potentiated in order to design appropriate interventions.

Contribution of the medial entorhinal cortex to performance on the Traveling Salesperson Problem in rats

In order to successfully navigate through space, animals must rely on multiple cognitive processes, including orientation in space, memory of object locations, and navigational decisions based on that information. Although highly-controlled behavioral tasks are valuable for isolating and targeting specific processes, they risk producing a narrow understanding of complex behavior in natural contexts. The Traveling Salesperson Problem (TSP) is an optimization problem that can be used to study naturalistic foraging behaviors, in which subjects select routes between multiple baited targets. Foraging is a spontaneous, yet complex, behavior, involving decision-making, attention, course planning, and memory. Previous research found that hippocampal lesions in rats impaired TSP task performance, particularly on measures of spatial memory. Although traditional laboratory tests have shown the medial entorhinal cortex (MEC) to play an important role in spatial memory, if and how the MEC is involved in finding efficient solutions to the TSP remains unknown. In the current study, rats were trained on the TSP, learning to retrieve bait from targets in a variety of spatial configurations. After recovering from either an MEC lesion or control sham surgery, the rats were tested on eight new configurations. Our results showed that, similar to rats with hippocampal lesions, MEC-lesioned rats were impaired on measures of spatial memory, but not spatial decision-making, with greatest impairments on configurations requiring a global navigational strategy for selecting the optimal route. These findings suggest that the MEC is important for effective spatial navigation, especially when global cue processing is required.

Mystery of the memory engram: History, current knowledge, and unanswered questions

The quest to understand the memory engram has intrigued humans for centuries. Recent technological advances, including genetic labelling, imaging, optogenetic and chemogenetic techniques, have propelled the field of memory research forward. These tools have enabled researchers to create and erase memory components. While these innovative techniques have yielded invaluable insights, they often focus on specific elements of the memory trace. Genetic labelling may rely on a particular immediate early gene as a marker of activity, optogenetics may activate or inhibit one specific type of neuron, and imaging may capture activity snapshots in a given brain region at specific times. Yet, memories are multifaceted, involving diverse arrays of neuronal subpopulations, circuits, and regions that work in concert to create, store, and retrieve information. Consideration of contributions of both excitatory and inhibitory neurons, micro and macro circuits across brain regions, the dynamic nature of active ensembles, and representational drift is crucial for a comprehensive understanding of the complex nature of memory.

Beyond the ears: A review exploring the interconnected brain behind the hierarchical memory of music

Music is a ubiquitous element of daily life. Understanding how music memory is represented and expressed in the brain is key to understanding how music can influence human daily cognitive tasks. Current music-memory literature is built on data from very heterogeneous tasks for measuring memory, and the neural correlates appear to differ depending on different forms of memory function targeted. Such heterogeneity leaves many exceptions and conflicts in the data underexplained (e.g., hippocampal involvement in music memory is debated). This review provides an overview of existing neuroimaging results from music-memory related studies and concludes that although music is a special class of event in our lives, the memory systems behind it do in fact share neural mechanisms with memories from other modalities. We suggest that dividing music memory into different levels of a hierarchy (structural level and semantic level) helps understand overlap and divergence in neural networks involved. This is grounded in the fact that memorizing a piece of music recruits brain clusters that separately support functions including-but not limited to-syntax storage and retrieval, temporal processing, prediction versus reality comparison, stimulus feature integration, personal memory associations, and emotion perception. The cross-talk between frontal-parietal music structural processing centers and the subcortical emotion and context encoding areas explains why music is not only so easily memorable but can also serve as strong contextual information for encoding and retrieving nonmusic information in our lives.

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.

Working memory features are embedded in hippocampal place fields

Hippocampal principal neurons display both spatial tuning properties and memory features. Whether this distinction corresponds to separate neuron types or a context-dependent continuum has been debated. We report here that the task-context ("splitter") feature is highly variable along both trial and spatial position axes. Neurons acquire or lose splitter features across trials even when place field features remain unaltered. Multiple place fields of the same neuron can individually encode both past or future run trajectories, implying that splitter fields are under the control of assembly activity. Place fields can be differentiated into subfields by the behavioral choice of the animal, and splitting within subfields evolves across trials. Interneurons also differentiate choices by integrating inputs from pyramidal cells. Finally, bilateral optogenetic inactivation of the medial entorhinal cortex reversibly decreases the fraction of splitter fields. Our findings suggest that place or splitter features are different manifestations of the same hippocampal computation.

The hippocampus contributes to retroactive stimulus associations during trace fear conditioning

Binding events that occur at different times are essential for memory formation. In trace fear conditioning, animals associate a tone and footshock despite no temporal overlap. The hippocampus is thought to mediate this learning by maintaining a memory of the tone until shock occurrence, however, evidence for sustained hippocampal tone representations is lacking. Here, we demonstrate a retrospective role for the hippocampus in trace fear conditioning. Bulk calcium imaging revealed sustained increases in CA1 activity after footshock that were not observed after tone termination. Optogenetic silencing of CA1 immediately after footshock impaired subsequent memory. Additionally, footshock increased the number of sharp-wave ripples compared to baseline during conditioning. Therefore, post-shock hippocampal activity likely supports learning by reactivating and linking latent tone and shock representations. These findings highlight an underappreciated function of post-trial hippocampal activity in enabling retroactive temporal associations during new learning, as opposed to persistent maintenance of stimulus representations.

Event Integration and Temporal Differentiation: How Hierarchical Knowledge Emerges in Hippocampal Subfields through Learning

Everyday life is composed of events organized by changes in contexts, with each event containing an unfolding sequence of occurrences. A major challenge facing our memory systems is how to integrate sequential occurrences within events while also maintaining their details and avoiding over-integration across different contexts. We asked if and how distinct hippocampal subfields come to hierarchically and, in parallel, represent both event context and subevent occurrences with learning. Female and male human participants viewed sequential events defined as sequences of objects superimposed on shared color frames while undergoing high-resolution fMRI. Importantly, these events were repeated to induce learning. Event segmentation, as indexed by increased reaction times at event boundaries, was observed in all repetitions. Temporal memory decisions were quicker for items from the same event compared to across different events, indicating that events shaped memory. With learning, hippocampal CA3 multivoxel activation patterns clustered to reflect the event context, with more clustering correlated with behavioral facilitation during event transitions. In contrast, in the dentate gyrus (DG), temporally proximal items that belonged to the same event became associated with more differentiated neural patterns. A computational model explained these results by dynamic inhibition in the DG. Additional similarity measures support the notion that CA3 clustered representations reflect shared voxel populations, while DG's distinct item representations reflect different voxel populations. These findings suggest an interplay between temporal differentiation in the DG and attractor dynamics in CA3. They advance our understanding of how knowledge is structured through integration and separation across time and context.

Time Cells in the Retrosplenial Cortex

The retrosplenial cortex (RSC) is a key component of the brain's memory systems, with anatomical connections to the hippocampus, anterior thalamus, and entorhinal cortex. This circuit has been implicated in episodic memory and many of these structures have been shown to encode temporal information, which is critical for episodic memory. For example, hippocampal time cells reliably fire during specific segments of time during a delay period. Although RSC lesions are known to disrupt temporal memory, time cells have not been observed there. In the present study, we examined the firing patterns of RSC neurons during the intertrial delay period of two behavioral tasks, a blocked alternation task and a cued T-maze task. For the blocked alternation task, rats were required to approach the east or west arm of a plus maze for reward during different blocks of trials. Because the reward locations were not cued, the rat had to remember the goal location for each trial. In the cued T-maze task, the reward location was explicitly cued with a light and the rats simply had to approach the light for reward, so there was no requirement to hold a memory during the intertrial delay. Time cells were prevalent in the blocked alternation task, and most time cells clearly differentiated the east and west trials. We also found that RSC neurons could exhibit off-response time fields, periods of reliably inhibited firing. Time cells were also observed in the cued T-maze, but they were less prevalent and they did not differentiate left and right trials as well as in the blocked alternation task, suggesting that RSC time cells are sensitive to the memory demands of the task. These results suggest that temporal coding is a prominent feature of RSC firing patterns, consistent with an RSC role in episodic memory.

A generative model of memory construction and consolidation

Episodic memories are (re)constructed, share neural substrates with imagination, combine unique features with schema-based predictions and show schema-based distortions that increase with consolidation. Here we present a computational model in which hippocampal replay (from an autoassociative network) trains generative models (variational autoencoders) to (re)create sensory experiences from latent variable representations in entorhinal, medial prefrontal and anterolateral temporal cortices via the hippocampal formation. Simulations show effects of memory age and hippocampal lesions in agreement with previous models, but also provide mechanisms for semantic memory, imagination, episodic future thinking, relational inference and schema-based distortions including boundary extension. The model explains how unique sensory and predictable conceptual elements of memories are stored and reconstructed by efficiently combining both hippocampal and neocortical systems, optimizing the use of limited hippocampal storage for new and unusual information. Overall, we believe hippocampal replay training generative models provides a comprehensive account of memory construction, imagination and consolidation.

Knockout of NMDARs in CA1 and dentate gyrus fails to impair temporal control of conditioned behavior in mice

The hippocampus has been implicated in temporal learning. Plasticity within the hippocampus requires NMDA receptor-dependent glutamatergic neurotransmission. We tested the prediction that hippocampal NMDA receptors are required for learning about time by testing mice that lack postembryonal NMDARs in the CA1 and dentate gyrus (DG) hippocampal subfields on three different appetitive temporal learning procedures. The conditional knockout mice (Grin1ΔDCA1 ) showed normal sensitivity to cue duration, responding at a higher level to a short duration cue than compared to a long duration cue. Knockout mice also showed normal precision and accuracy of response timing in the peak procedure in which reinforcement occurred after 10 s delay within a 30 s cue presentation. Mice were tested on the matching of response rates to reinforcement rates on instrumental conditioning with two levers reinforced on a concurrent variable interval schedule. Pressing on one lever was reinforced at a higher rate than the other lever. Grin1ΔDGCA1 mice showed normal sensitivity to the relative reinforcement rates of the levers. In contrast to the lack of effect of hippocampal NMDAR deletion on measures of temporal sensitivity, Grin1ΔDGCA1 mice showed increased baseline measures of magazine activity and lever pressing. Furthermore, reversal learning was enhanced when the reward contingencies were switched in the lever pressing task, but this was true only for mice trained with a large difference between relative reinforcement rates between the levers. The results failed to demonstrate a role for NMDARs in excitatory CA1 and DG neurons in learning about temporal information.

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.

Grid cells: the missing link in understanding Parkinson's disease?

The mechanisms underlying Parkinson's disease (PD) are complex and not fully understood, and the box-and-arrow model among other current models present significant challenges. This paper explores the potential role of the allocentric brain and especially its grid cells in several PD motor symptoms, including bradykinesia, kinesia paradoxa, freezing of gait, the bottleneck phenomenon, and their dependency on cueing. It is argued that central hubs, like the locus coeruleus and the pedunculopontine nucleus, often narrowly interpreted in the context of PD, play an equally important role in governing the allocentric brain as the basal ganglia. Consequently, the motor and secondary motor (e.g., spatially related) symptoms of PD linked with dopamine depletion may be more closely tied to erroneous computation by grid cells than to the basal ganglia alone. Because grid cells and their associated central hubs introduce both spatial and temporal information to the brain influencing velocity perception they may cause bradykinesia or hyperkinesia as well. In summary, PD motor symptoms may primarily be an allocentric disturbance resulting from virtual faulty computation by grid cells revealed by dopamine depletion in PD.

Hippocampal sequences span experience relative to rewards

Hippocampal place cells fire in sequences that span spatial environments and non-spatial modalities, suggesting that hippocampal activity can anchor to the most behaviorally salient aspects of experience. As reward is a highly salient event, we hypothesized that sequences of hippocampal activity can anchor to rewards. To test this, we performed two-photon imaging of hippocampal CA1 neurons as mice navigated virtual environments with changing hidden reward locations. When the reward moved, the firing fields of a subpopulation of cells moved to the same relative position with respect to reward, constructing a sequence of reward-relative cells that spanned the entire task structure. The density of these reward-relative sequences increased with task experience as additional neurons were recruited to the reward-relative population. Conversely, a largely separate subpopulation maintained a spatially-based place code. These findings thus reveal separate hippocampal ensembles can flexibly encode multiple behaviorally salient reference frames, reflecting the structure of the experience.

The Feeling of Time Passing Is Associated with Recurrent Sustained Activity and Theta Rhythms Across the Cortex

Introduction: We are constantly estimating how much time has passed, and yet know little about the brain mechanisms through which this process occurs. In this pilot study, we evaluated so-called subjective time estimation with the temporal bisection task, while recording brain activity from electroencephalography (EEG). Methods: Nine adult participants were trained to distinguish between two durations of visual stimuli as either "short" (400 msec) or "long" (1600 msec). They were then presented with stimulus durations in between the long and short stimuli. EEG data from 128 electrodes were examined with a novel analytical method that identifies segments of sustained cortical activity during the task. Results: Participants tended to categorize intermediate durations as "long" more frequently than "short" and were thus experiencing time as moving faster while overestimating the amount of time passing. Their mean bisection point (during which frequency of selecting short vs. long is equal) was closer to the geometric mean of task stimuli (800 msec) rather than the arithmetic mean (1000 msec). In contrast, sustained brain activity occurred closer to the arithmetic mean. The recurrence rate of this activity was highly related to the bisection point, especially when analyzed within naturally occurring theta oscillations (4-8 Hz) (r = -0.90). Discussion: Sustained activity across the cortex within the theta range may reflect temporal durations, whereas its repeated appearance relates to the subjective feeling of time passing.

Multiplexing of temporal and spatial information in the lateral entorhinal cortex

Episodic memory involves the processing of spatial and temporal aspects of personal experiences. The lateral entorhinal cortex (LEC) plays an essential role in subserving memory. However, the specific mechanism by which LEC integrates spatial and temporal information remains elusive. Here, we recorded LEC neurons while rats performed foraging and shuttling behaviors on one-dimensional, linear or circular tracks. Unlike open-field foraging tasks, many LEC cells displayed spatial firing fields in these tasks and demonstrated selectivity for traveling directions. Furthermore, some LEC neurons displayed changes in the firing rates of their spatial rate maps during a session, a phenomenon referred to as rate remapping. Importantly, this temporal modulation was consistent across sessions, even when the spatial environment was altered. Notably, the strength of temporal modulation was found to be greater in LEC compared to other brain regions, such as the medial entorhinal cortex (MEC), CA1, and CA3. Thus, the spatial rate mapping observed in LEC neurons may serve as a coding mechanism for temporal context, allowing for flexible multiplexing of spatial and temporal information.

Cardiorespiratory fitness is associated with cortical thickness of medial temporal brain areas associated with spatial cognition in young but not older adults

Cardiorespiratory fitness has a potent effect on neurocognitive health, especially regarding the hippocampal memory system. However, less is known about the impact of cardiorespiratory fitness on medial temporal lobe extrahippocampal neocortical regions. Specifically, it is unclear how cardiorespiratory fitness modulates these brain regions in young adulthood and if these regions are differentially related to cardiorespiratory fitness in young versus older adults. The primary goal of this study was to investigate if cardiorespiratory fitness predicted medial temporal lobe cortical thickness which, with the hippocampus, are critical for spatial learning and memory. Additionally, given the established role of these cortices in spatial navigation, we sought to determine if cardiorespiratory fitness and medial temporal lobe cortical thickness would predict greater subjective sense of direction in both young and older adults. Cross-sectional data from 56 young adults (20-35 years) and 44 older adults (55-85 years) were included. FreeSurfer 6.0 was used to automatically segment participants' 3T T1-weighted images. Using hierarchical multiple regression analyses, we confirmed significant associations between greater cardiorespiratory fitness and greater left entorhinal, left parahippocampal, and left perirhinal cortical thickness in young, but not older, adults. Left parahippocampal cortical thickness interacted with age group to differentially predict subjective sense of direction in young and older adults. Young adults displayed a positive, and older adults a negative, correlation between left parahippocampal cortical thickness and sense of direction. Our findings extend previous work on the association between cardiorespiratory fitness and hippocampal subfield structure in young adults to left medial temporal lobe neocortical regions.

Neurocomputational Models of Interval Timing: Seeing the Forest for the Trees

Extracting temporal regularities and relations from experience/observation is critical for organisms' adaptiveness (communication, foraging, predation, prediction) in their ecological niches. Therefore, it is not surprising that the internal clock that enables the perception of seconds-to-minutes-long intervals (interval timing) is evolutionarily well-preserved across many species of animals. This comparative claim is primarily supported by the fact that the timing behavior of many vertebrates exhibits common statistical signatures (e.g., on-average accuracy, scalar variability, positive skew). These ubiquitous statistical features of timing behaviors serve as empirical benchmarks for modelers in their efforts to unravel the processing dynamics of the internal clock (namely answering how internal clock "ticks"). In this chapter, we introduce prominent (neuro)computational approaches to modeling interval timing at a level that can be understood by general audience. These models include Treisman's pacemaker accumulator model, the information processing variant of scalar expectancy theory, the striatal beat frequency model, behavioral expectancy theory, the learning to time model, the time-adaptive opponent Poisson drift-diffusion model, time cell models, and neural trajectory models. Crucially, we discuss these models within an overarching conceptual framework that categorizes different models as threshold vs. clock-adaptive models and as dedicated clock/ramping vs. emergent time/population code models.

Engrams: From Behavior to Brain-Wide Networks

Animals utilize a repertoire of behavioral responses during everyday experiences. During a potentially dangerous encounter, defensive actions such as "fight, flight, or freeze" are selected for survival. The successful use of behavior is determined by a series of real-time computations combining an animal's internal (i.e., body) and external (i.e., environment) state. Brain-wide neural pathways are engaged throughout this process to detect stimuli, integrate information, and command behavioral output. The hippocampus, in particular, plays a role in the encoding and storing of the episodic information surrounding these encounters as putative "engram" or experience-modified cellular ensembles. Recalling a negative experience then reactivates a dedicated engram ensemble and elicits a behavioral response. How hippocampus-based engrams modulate brain-wide states and an animal's internal/external milieu to influence behavior is an exciting area of investigation for contemporary neuroscience. In this chapter, we provide an overview of recent technological advancements that allow researchers to tag, manipulate, and visualize putative engram ensembles, with an overarching goal of casually connecting their brain-wide underpinnings to behavior. We then discuss how hippocampal fear engrams alter behavior in a manner that is contingent on an environment's physical features as well as how they influence brain-wide patterns of cellular activity. Overall, we propose here that studies on memory engrams offer an exciting avenue for contemporary neuroscience to casually link the activity of cells to cognition and behavior while also offering testable theoretical and experimental frameworks for how the brain organizes experience.

Cognition of Time and Thinking Beyond

A common research protocol in cognitive neuroscience is to train subjects to perform deliberately designed experiments while recording brain activity, with the aim of understanding the brain mechanisms underlying cognition. However, how the results of this protocol of research can be applied in technology is seldom discussed. Here, I review the studies on time processing of the brain as examples of this research protocol, as well as two main application areas of neuroscience (neuroengineering and brain-inspired artificial intelligence). Time processing is a fundamental dimension of cognition, and time is also an indispensable dimension of any real-world signal to be processed in technology. Therefore, one may expect that the studies of time processing in cognition profoundly influence brain-related technology. Surprisingly, I found that the results from cognitive studies on timing processing are hardly helpful in solving practical problems. This awkward situation may be due to the lack of generalizability of the results of cognitive studies, which are under well-controlled laboratory conditions, to real-life situations. This lack of generalizability may be rooted in the fundamental unknowability of the world (including cognition). Overall, this paper questions and criticizes the usefulness and prospect of the abovementioned research protocol of cognitive neuroscience. I then give three suggestions for future research. First, to improve the generalizability of research, it is better to study brain activity under real-life conditions instead of in well-controlled laboratory experiments. Second, to overcome the unknowability of the world, we can engineer an easily accessible surrogate of the object under investigation, so that we can predict the behavior of the object under investigation by experimenting on the surrogate. Third, the paper calls for technology-oriented research, with the aim of technology creation instead of knowledge discovery.

Multidimensional assessment of time perception along the continuum of Alzheimer's Disease and evidence of alterations in subjective cognitive decline

Timing alterations occur in Alzheimer's disease (AD), even in early stages (mild cognitive impairment, MCI). Moreover, a stage named subjective cognitive decline (SCD), in which individuals perceive a change in cognitive performance not revealed by neuropsychological tests, has been identified as a preclinical phase of AD. However, no study to date has investigated different dimensions of time processing along the continuum from physiological to pathological aging, and whether timing alterations occur in SCD. Here a sample of participants with SCD, MCI, AD and healthy controls (HC) performed tasks assessing prospective duration estimation, production, reproduction, implicit temporal learning in conditions dependent from external cues (externally-cued learning, ECL) or independent from external cues (internally-based learning, IBL), retrospective duration estimation, the subjective experience of time and the temporal collocation of events. AD patients performed worse than HC and SCD in prospective timing, and in collocating events in time. The subjective experience of time did not differ between groups. Concerning temporal learning, AD performed worse in ECL than in IBL, whereas SCD performed worse in IBL than in ECL. SCD, MCI and AD patients all showed errors greater than HC in retrospective duration estimation. Results point to implicit temporal learning in externally-cued conditions and retrospective time estimation as possible early markers of cognitive decline.

Learning of object-in-context sequences in freely-moving macaques

Flexible learning is a hallmark of primate cognition, which arises through interactions with changing environments. Studies of the neural basis for this flexibility are typically limited by laboratory settings that use minimal environmental cues and restrict interactions with the environment, including active sensing and exploration. To address this, we constructed a 3-D enclosure containing touchscreens on its walls, for studying cognition in freely moving macaques. To test flexible learning, two monkeys completed trials consisting of a regular sequence of object selections across four touchscreens. On each screen, the monkeys had to select by touching the sole correct object item ('target') among a set of four items, irrespective of their positions on the screen. Each item was the target on exactly one screen of the sequence, making correct performance conditioned on the spatiotemporal sequence rule across screens. Both monkeys successfully learned multiple 4-item sets (N=14 and 22 sets), totaling over 50 and 80 unique, conditional item-context memoranda, with no indication of capacity limits. The enclosure allowed freedom of movements leading up to and following the touchscreen interactions. To determine whether movement economy changed with learning, we reconstructed 3D position and movement dynamics using markerless tracking software and gyroscopic inertial measurements. Whereas general body positions remained consistent across repeated sequences, fine head movements varied as monkeys learned, within and across sequence sets, demonstrating learning set or "learning to learn". These results demonstrate monkeys' rapid, capacious, and flexible learning within an integrated, multisensory 3-D space. Furthermore, this approach enables the measurement of continuous behavior while ensuring precise experimental control and behavioral repetition of sequences over time. Overall, this approach harmonizes the design features that are needed for electrophysiological studies with tasks that showcase fully situated, flexible cognition.

A neural code for time and space in the human brain

Time and space are primary dimensions of human experience. Separate lines of investigation have identified neural correlates of time and space, yet little is known about how these representations converge during self-guided experience. Here, 10 subjects with intracranially implanted microelectrodes play a timed, virtual navigation game featuring object search and retrieval tasks separated by fixed delays. Time cells and place cells activate in parallel during timed navigation intervals, whereas a separate time cell sequence spans inter-task delays. The prevalence, firing rates, and behavioral coding strengths of time cells and place cells are indistinguishable-yet time cells selectively remap between search and retrieval tasks, while place cell responses remain stable. Thus, the brain can represent time and space as overlapping but dissociable dimensions. Time cells and place cells may constitute a biological basis for the cognitive map of spatiotemporal context onto which memories are written.

Goal-Dependent Hippocampal Representations Facilitate Self-Control

Hippocampal activity linking past experiences and simulations of the future with current goals can play an important role in decision-making. The representation of information within the hippocampus may be especially critical in situations where one needs to overcome past rewarding experiences and exert self-control. Self-control success or failure may depend on how information is represented in the hippocampus and how effectively the representation process can be modified to achieve a specific goal. We test this hypothesis using representational similarity analyses of human (female/male) neuroimaging data during a dietary self-control task in which individuals must overcome taste temptations to choose healthy foods. We find that self-control is indeed associated with the way individuals represent taste information (valance) in the hippocampus and how taste representations there adapt to align with different goals/contexts. Importantly, individuals who were able to shift their hippocampal representations to a larger degree to align with the current motivation were better able to exert self-control when facing a dietary challenge. These results suggest an alternative or complementary neurobiological pathway leading to self-control success and indicate the need to update the classical view of self-control to continue to advance our understanding of its behavioral and neural underpinnings.SIGNIFICANCE STATEMENT The paper provides a new perspective on what leads to successful self-control at the behavioral and neurobiological levels. Our data suggest that self-control is enhanced when individuals adjust hippocampal processing to align with current goals.

Sharpening the blades of the dentate gyrus: how adult-born neurons differentially modulate diverse aspects of hippocampal learning and memory

For decades, the mammalian hippocampus has been the focus of cellular, anatomical, behavioral, and computational studies aimed at understanding the fundamental mechanisms underlying cognition. Long recognized as the brain's seat for learning and memory, a wealth of knowledge has been accumulated on how the hippocampus processes sensory input, builds complex associations between objects, events, and space, and stores this information in the form of memories to be retrieved later in life. However, despite major efforts, our understanding of hippocampal cognitive function remains fragmentary, and models trying to explain it are continually revisited. Here, we review the literature across all above-mentioned domains and offer a new perspective by bringing attention to the most distinctive, and generally neglected, feature of the mammalian hippocampal formation, namely, the structural separability of the two blades of the dentate gyrus into "supra-pyramidal" and "infra-pyramidal". Next, we discuss recent reports supporting differential effects of adult neurogenesis in the regulation of mature granule cell activity in these two blades. We propose a model for how differences in connectivity and adult neurogenesis in the two blades can potentially provide a substrate for subtly different cognitive functions.

Time for Memories

The ability to store information about the past to dynamically predict and prepare for the future is among the most fundamental tasks the brain performs. To date, the problems of understanding how the brain stores and organizes information about the past (memory) and how the brain represents and processes temporal information for adaptive behavior have generally been studied as distinct cognitive functions. This Symposium explores the inherent link between memory and temporal cognition, as well as the potential shared neural mechanisms between them. We suggest that working memory and implicit timing are interconnected and may share overlapping neural mechanisms. Additionally, we explore how temporal structure is encoded in associative and episodic memory and, conversely, the influences of episodic memory on subsequent temporal anticipation and the perception of time. We suggest that neural sequences provide a general computational motif that contributes to timing and working memory, as well as the spatiotemporal coding and recall of episodes.

Influence of amyloid and diagnostic syndrome on non-traditional memory scores in early-onset Alzheimer's disease

INTRODUCTION

The Rey Auditory Verbal Learning Test (RAVLT) is a useful neuropsychological test for describing episodic memory impairment in dementia. However, there is limited research on its utility in early-onset Alzheimer's disease (EOAD). We assess the influence of amyloid and diagnostic syndrome on several memory scores in EOAD.

METHODS

We transcribed RAVLT recordings from 303 subjects in the Longitudinal Early-Onset Alzheimer's Disease Study. Subjects were grouped by amyloid status and syndrome. Primacy, recency, J-curve, duration, stopping time, and speed score were calculated and entered into linear mixed effects models as dependent variables.

RESULTS

Compared with amyloid negative subjects, positive subjects exhibited effects on raw score, primacy, recency, and stopping time. Inter-syndromic differences were noted with raw score, primacy, recency, J-curve, and stopping time.

DISCUSSION

RAVLT measures are sensitive to the effects of amyloid and syndrome in EOAD. Future work is needed to quantify the predictive value of these scores.

HIGHLIGHTS

RAVLT patterns characterize various presentations of EOAD and EOnonAD Amyloid impacts raw score, primacy, recency, and stopping time Timing-based scores add value over traditional count-based scores.

Adult neurogenesis and "immature" neurons in mammals: an evolutionary trade-off in plasticity?

Neuronal plasticity can vary remarkably in its form and degree across animal species. Adult neurogenesis, namely the capacity to produce new neurons from neural stem cells through adulthood, appears widespread in non-mammalian vertebrates, whereas it is reduced in mammals. A growing body of comparative studies also report variation in the occurrence and activity of neural stem cell niches between mammals, with a general trend of reduction from small-brained to large-brained species. Conversely, recent studies have shown that large-brained mammals host large amounts of neurons expressing typical markers of neurogenesis in the absence of cell division. In layer II of the cerebral cortex, populations of prenatally generated, non-dividing neurons continue to express molecules indicative of immaturity throughout life (cortical immature neurons; cINs). After remaining in a dormant state for a very long time, these cINs retain the potential of differentiating into mature neurons that integrate within the preexisting neural circuits. They are restricted to the paleocortex in small-brained rodents, while extending into the widely expanded neocortex of highly gyrencephalic, large-brained species. The current hypothesis is that these populations of non-newly generated "immature" neurons might represent a reservoir of developmentally plastic cells for mammalian species that are characterized by reduced stem cell-driven adult neurogenesis. This indicates that there may be a trade-off between various forms of plasticity that coexist during brain evolution. This balance may be necessary to maintain a "reservoir of plasticity" in brain regions that have distinct roles in species-specific socioecological adaptations, such as the neocortex and olfactory structures.

Neurophysiological correlates of altered time awareness in Alzheimer's disease and frontotemporal dementia

BACKGROUND

Alterations in time awareness have been reported in dementia, particularly in Alzheimer's disease (AD) and frontotemporal dementia (FTD). However, the neurophysiological correlates underlying these alterations remain largely unexplored. This study aimed to investigate the neurophysiological correlates of altered time awareness in AD and FTD patients.

METHODS

A total of 150 participants (50 AD patients, 50 FTD patients, and 50 healthy controls [HC]) underwent a standardized neuropsychological assessment, an altered time awareness survey, and transcranial magnetic stimulation (TMS) to assess cholinergic (short latency afferent inhibition-SAI), GABAergic (short interval intracortical inhibition-SICI), and glutamatergic (intracortical facilitation-ICF) circuits.

RESULTS

In AD patients, the most frequent symptom was difficulty in ordering past events (52.0%), while FTD patients primarily struggled with estimating temporal intervals between events (40.0%). Significant differences were observed between HC and both patient groups, as well as between AD and FTD patients in their tendency to re-live past events. Binomial logistic regression analysis revealed that impairments in glutamatergic and cholinergic circuits significantly predicted the likelihood of participants manifesting altered time awareness symptoms.

CONCLUSIONS

This study provides novel insights into the neurophysiological correlates of altered time awareness in AD and FTD patients, highlighting the involvement of specific neurotransmitter circuits, particularly glutamatergic and cholinergic circuits. Further research is needed to explore the potential clinical implications and therapeutic targets arising from these findings.

Lost in time: Relocating the perception of duration outside the brain

It is well-accepted in neuroscience that animals process time internally to estimate the duration of intervals lasting between one and several seconds. More than 100 years ago, Henri Bergson nevertheless remarked that, because animals have memory, their inner experience of time is ever-changing, making duration impossible to measure internally and time a source of change. Bergson proposed that quantifying the inner experience of time requires its externalization in movements (observed or self-generated), as their unfolding leaves measurable traces in space. Here, studies across species are reviewed and collectively suggest that, in line with Bergson's ideas, animals spontaneously solve time estimation tasks through a movement-based spatialization of time. Moreover, the well-known scalable anticipatory responses of animals to regularly spaced rewards can be explained by the variable pressure of time on reward-oriented actions. Finally, the brain regions linked with time perception overlap with those implicated in motor control, spatial navigation and motivation. Thus, instead of considering time as static information processed by the brain, it might be fruitful to conceptualize it as a kind of force to which animals are more or less sensitive depending on their internal state and environment.

Common population codes produce extremely nonlinear neural manifolds

Populations of neurons represent sensory, motor, and cognitive variables via patterns of activity distributed across the population. The size of the population used to encode a variable is typically much greater than the dimension of the variable itself, and thus, the corresponding neural population activity occupies lower-dimensional subsets of the full set of possible activity states. Given population activity data with such lower-dimensional structure, a fundamental question asks how close the low-dimensional data lie to a linear subspace. The linearity or nonlinearity of the low-dimensional structure reflects important computational features of the encoding, such as robustness and generalizability. Moreover, identifying such linear structure underlies common data analysis methods such as Principal Component Analysis (PCA). Here, we show that for data drawn from many common population codes the resulting point clouds and manifolds are exceedingly nonlinear, with the dimension of the best-fitting linear subspace growing at least exponentially with the true dimension of the data. Consequently, linear methods like PCA fail dramatically at identifying the true underlying structure, even in the limit of arbitrarily many data points and no noise.

Neuromodulation of the anterior thalamus: Current approaches and opportunities for the future

The role of thalamocortical circuits in memory has driven a recent burst of scholarship, especially in animal models. Investigating this circuitry in humans is more challenging. And yet, the development of new recording and stimulation technologies deployed for clinical indications has created novel opportunities for data collection to elucidate the cognitive roles of thalamic structures. These technologies include stereoelectroencephalography (SEEG), deep brain stimulation (DBS), and responsive neurostimulation (RNS), all of which have been applied to memory-related thalamic regions, specifically for seizure localization and treatment. This review seeks to summarize the existing applications of neuromodulation of the anterior thalamic nuclei (ANT) and highlight several devices and their capabilities that can allow cognitive researchers to design experiments to assay its functionality. Our goal is to introduce to investigators, who may not be familiar with these clinical devices, the capabilities, and limitations of these tools for understanding the neurophysiology of the ANT as it pertains to memory and other behaviors. We also briefly cover the targeting of other thalamic regions including the centromedian (CM) nucleus, dorsomedial (DM) nucleus, and pulvinar, with associated potential avenues of experimentation.

Emerging many-to-one weighted mapping in hippocampus-amygdala network underlies memory formation

Memories are crucial for our daily lives, yet the network-level organizing principle that governs neural representations of our experiences remains to be determined. Employing dual-site electrophysiology recording in freely behaving mice, we discovered that hippocampal dorsal CA1 (dCA1) and basolateral amygdala (BLA) utilize distinct coding strategies to represent novel experiences. A small assembly of BLA neurons rapidly emerged during memory acquisition and remained active during subsequent consolidation, whereas the majority of dCA1 neurons engaged in the same processes. Machine learning decoding revealed that dCA1 population spikes predicted the BLA assembly firing rate. This suggests that most dCA1 neurons concurrently index an episodic event by rapidly establishing weighted communications with a specific BLA assembly, a process we call "many-to-one weighted mapping." Furthermore, we demonstrated that closed-loop optoinhibition of BLA activity triggered by dCA1 ripples after new learning resulted in impaired memory. These findings highlight a new principle of hippocampus-amygdala communication underlying memory formation and provide new insights into how the brain creates and stores memories.

Localization of a Medial Temporal Lobe-Precuneus Network for Time Orientation

OBJECTIVE

Time orientation is a fundamental cognitive process in which one's personal sense of time is matched with a universal reference. Time orientation is commonly assessed through mental status examination, yet its neural correlates remain unclear. Large lesions have been associated with deficits in time orientation, but the regional anatomy implicated in time disorientation is not well established. The current study investigates the anatomy of time disorientation and its network correlates in patients with focal brain lesions.

METHODS

Time orientation was assessed 3 months or more after lesion onset using the Benton Temporal Orientation Test (BTOT) in 550 patients with acquired, focal brain lesions, 39 of whom were impaired. Multivariate lesion-symptom mapping and lesion network mapping were used to evaluate the anatomy and networks associated with time disorientation. Performance on a variety of neuropsychological tests was compared between the time oriented and time disoriented group.

RESULTS

Lesion-symptom mapping showed that lesions of the precuneus, medial temporal lobes (MTL), and occipito-temporal cortex were associated with time disorientation (r = 0.264, p < 0.001). Lesion network mapping using normative connectome data demonstrated that these regional findings occurred along a network that includes white and gray matter connecting the precuneus and MTL. There was a strong behavioral and anatomical association of time disorientation with memory impairment, such that the 2 processes could not be fully disentangled.

INTERPRETATION

We interpret these findings as novel evidence for a network involving the precuneus and the medial temporal lobe in supporting time orientation. ANN NEUROL 2023;94:421-433.

Linking temporal coordination of hippocampal activity to memory function

Oscillations in neural activity are widespread throughout the brain and can be observed at the population level through the local field potential. These rhythmic patterns are associated with cycles of excitability and are thought to coordinate networks of neurons, in turn facilitating effective communication both within local circuits and across brain regions. In the hippocampus, theta rhythms (4-12 Hz) could contribute to several key physiological mechanisms including long-range synchrony, plasticity, and at the behavioral scale, support memory encoding and retrieval. While neurons in the hippocampus appear to be temporally coordinated by theta oscillations, they also tend to fire in sequences that are developmentally preconfigured. Although loss of theta rhythmicity impairs memory, these sequences of spatiotemporal representations persist in conditions of altered hippocampal oscillations. The focus of this review is to disentangle the relative contribution of hippocampal oscillations from single-neuron activity in learning and memory. We first review cellular, anatomical, and physiological mechanisms underlying the generation and maintenance of hippocampal rhythms and how they contribute to memory function. We propose candidate hypotheses for how septohippocampal oscillations could support memory function while not contributing directly to hippocampal sequences. In particular, we explore how theta rhythms could coordinate the integration of upstream signals in the hippocampus to form future decisions, the relevance of such integration to downstream regions, as well as setting the stage for behavioral timescale synaptic plasticity. Finally, we leverage stimulation-based treatment in Alzheimer's disease conditions as an opportunity to assess the sufficiency of hippocampal oscillations for memory function.

Hippocampal orchestration of associative and sequential memory networks for episodic retrieval

Episodic memory involves the recollection of contextual details replayed mentally across time. Here, we propose the association-sequence network (ASN) model, characterizing complementary cortico-hippocampal networks underlying the retrieval of simultaneously associated and sequentially ordered events. Participants viewed objects, presented singly or in pairs, and later reported whether two objects were shown simultaneously, consecutively, or farther apart in time. Behavioral results and hippocampal activation reveal a correlation between the two sequential conditions but not the simultaneous condition, despite the temporal proximity of consecutive pairs. We also find that anterior hippocampal activity is modulated by temporal distance. Distinct cortical networks are engaged during simultaneous and sequential memory (prefrontal cortex and angular gyrus for association; supplementary motor cortex and precuneus for sequence); notably, these regions show differential connectivity with the hippocampus. The ASN model provides a comprehensive framework for how we reconstruct memories that are both rich in associative detail and temporally dynamic in nature.