A non-memory-based functional neural framework for animal caching behavior.

The brain's extraordinary abilities are often attributed to its capacity to learn and adapt. But memory has its limitations, especially when faced with tasks such as retrieving thousands of food items-a common behavior in scatter-hoarding animals. Here, we propose a brain mechanism that may facilitate caching and retrieval behaviors, with a focus on hippocampal spatial cells. Rather than memorizing the locations of their caches, as previously hypothesized, we suggest that cache-hoarding animals employ a static mechanism akin to hash functions commonly used in computing. Our mathematical model aligns with the activity of hippocampal spatial cells, which respond to an animal's positional attention. We know that the region that activates each spatial cell remains consistent across subsequent visits to the same area but not between areas. This remapping, combined with the uniqueness of cognitive maps, produces persistent hash functions that can serve both food caching and retrieval. We present a simple neural network architecture that can generate such a probabilistic hash that is unique to the animal and not sensitive to environmental changes. This mechanism could serve a virtually boundless capacity for the encoding of any structured data.

Modeling the contribution of theta-gamma coupling to sequential memory, imagination, and dreaming.

Gamma oscillations nested in a theta rhythm are observed in the hippocampus, where are assumed to play a role in sequential episodic memory, i.e., memorization and retrieval of events that unfold in time. In this work, we present an original neurocomputational model based on neural masses, which simulates the encoding of sequences of events in the hippocampus and subsequent retrieval by exploiting the theta-gamma code. The model is based on a three-layer structure in which individual Units oscillate with a gamma rhythm and code for individual features of an episode. The first layer (working memory in the prefrontal cortex) maintains a cue in memory until a new signal is presented. The second layer (CA3 cells) implements an auto-associative memory, exploiting excitatory and inhibitory plastic synapses to recover an entire episode from a single feature. Units in this layer are disinhibited by a theta rhythm from an external source (septum or Papez circuit). The third layer (CA1 cells) implements a hetero-associative net with the previous layer, able to recover a sequence of episodes from the first one. During an encoding phase, simulating high-acetylcholine levels, the network is trained with Hebbian (synchronizing) and anti-Hebbian (desynchronizing) rules. During retrieval (low-acetylcholine), the network can correctly recover sequences from an initial cue using gamma oscillations nested inside the theta rhythm. Moreover, in high noise, the network isolated from the environment simulates a mind-wandering condition, randomly replicating previous sequences. Interestingly, in a state simulating sleep, with increased noise and reduced synapses, the network can "dream" by creatively combining sequences, exploiting features shared by different episodes. Finally, an irrational behavior (erroneous superimposition of features in various episodes, like "delusion") occurs after pathological-like reduction in fast inhibitory synapses. The model can represent a straightforward and innovative tool to help mechanistically understand the theta-gamma code in different mental states.

Hippocampus and striatum show distinct contributions to longitudinal changes in value-based learning in middle childhood.

The hippocampal-dependent memory system and striatal-dependent memory system modulate reinforcement learning depending on feedback timing in adults, but their contributions during development remain unclear. In a 2-year longitudinal study, 6-to-7-year-old children performed a reinforcement learning task in which they received feedback immediately or with a short delay following their response. Children's learning was found to be sensitive to feedback timing modulations in their reaction time and inverse temperature parameter, which quantifies value-guided decision-making. They showed longitudinal improvements towards more optimal value-based learning, and their hippocampal volume showed protracted maturation. Better delayed model-derived learning covaried with larger hippocampal volume longitudinally, in line with the adult literature. In contrast, a larger striatal volume in children was associated with both better immediate and delayed model-derived learning longitudinally. These findings show, for the first time, an early hippocampal contribution to the dynamic development of reinforcement learning in middle childhood, with neurally less differentiated and more cooperative memory systems than in adults.

Neurofeedback training can modulate task-relevant memory replay rate in rats.

Hippocampal replay - the time-compressed, sequential reactivation of ensembles of neurons related to past experience - is a key neural mechanism of memory consolidation. Replay typically coincides with a characteristic pattern of local field potential activity, the sharp-wave ripple (SWR). Reduced SWR rates are associated with cognitive impairment in multiple models of neurodegenerative disease, suggesting that a clinically viable intervention to promote SWRs and replay would prove beneficial. We therefore developed a neurofeedback paradigm for rat subjects in which SWR detection triggered rapid positive feedback in the context of a memory-dependent task. This training protocol increased the prevalence of task-relevant replay during the targeted neurofeedback period by changing the temporal dynamics of SWR occurrence. This increase was also associated with neural and behavioral forms of compensation after the targeted period. These findings reveal short-timescale regulation of SWR generation and demonstrate that neurofeedback is an effective strategy for modulating hippocampal replay.

Blood-brain barrier integrity is linked to cognitive function, but not to cerebral arterial pulsatility, among elderly.

Blood-brain barrier (BBB) disruption may contribute to cognitive decline, but questions remain whether this association is more pronounced for certain brain regions, such as the hippocampus, or represents a whole-brain mechanism. Further, whether human BBB leakage is triggered by excessive vascular pulsatility, as suggested by animal studies, remains unknown. In a prospective cohort (N = 50; 68-84 years), we used contrast-enhanced MRI to estimate the permeability-surface area product (PS) and fractional plasma volume ( v p ), and 4D flow MRI to assess cerebral arterial pulsatility. Cognition was assessed by the Montreal Cognitive Assessment (MoCA) score. We hypothesized that high PS would be associated with high arterial pulsatility, and that links to cognition would be specific to hippocampal PS. For 15 brain regions, PS ranged from 0.38 to 0.85 (·10-3 min-1) and v p from 0.79 to 1.78%. Cognition was related to PS (·10-3 min-1) in hippocampus (ß = - 2.9; p = 0.006), basal ganglia (ß = - 2.3; p = 0.04), white matter (ß = - 2.6; p = 0.04), whole-brain (ß = - 2.7; p = 0.04) and borderline-related for cortex (ß = - 2.7; p = 0.076). Pulsatility was unrelated to PS for all regions (p > 0.19). Our findings suggest PS-cognition links mainly reflect a whole-brain phenomenon with only slightly more pronounced links for the hippocampus, and provide no evidence of excessive pulsatility as a trigger of BBB disruption.

Induction of LTP mechanisms in dually innervated dendritic spines.

Dendritic spines are the postsynaptic compartments of excitatory synapses, however, a substantial subset of spines additionally receives inhibitory input. In such dually innervated spines (DiSs), excitatory long-term potentiation (LTP) mechanisms are suppressed, but can be enabled by blocking tonic inhibitory GABAB receptor signaling. Here we show that LTP mechanisms at DiSs are also enabled by two other excitatory LTP stimuli. In hippocampal neurons, these chemical LTP (cLTP) stimuli induced robust movement of the Ca2+/calmodulin-dependent protein kinase II (CaMKII) to DiSs. Such synaptic CaMKII accumulation is an essential LTP mechanism at singly innervated spines (SiSs). Indeed, CaMKII accumulation at DiSs was also accompanied by other readouts for successful LTP induction: spine growth and surface insertion of GluA1. Thus, DiSs are capable of the same LTP mechanisms as SiSs, although induction of these mechanism additionally requires either reduced inhibitory signaling or increased excitatory stimulation. This additional regulation may provide further computational control.

Functional architecture of intracellular oscillations in hippocampal dendrites.

Fast electrical signaling in dendrites is central to neural computations that support adaptive behaviors. Conventional techniques lack temporal and spatial resolution and the ability to track underlying membrane potential dynamics present across the complex three-dimensional dendritic arbor in vivo. Here, we perform fast two-photon imaging of dendritic and somatic membrane potential dynamics in single pyramidal cells in the CA1 region of the mouse hippocampus during awake behavior. We study the dynamics of subthreshold membrane potential and suprathreshold dendritic events throughout the dendritic arbor in vivo by combining voltage imaging with simultaneous local field potential recording, post hoc morphological reconstruction, and a spatial navigation task. We systematically quantify the modulation of local event rates by locomotion in distinct dendritic regions, report an advancing gradient of dendritic theta phase along the basal-tuft axis, and describe a predominant hyperpolarization of the dendritic arbor during sharp-wave ripples. Finally, we find that spatial tuning of dendritic representations dynamically reorganizes following place field formation. Our data reveal how the organization of electrical signaling in dendrites maps onto the anatomy of the dendritic tree across behavior, oscillatory network, and functional cell states.

Brain oscillations: Hippocampal-prefrontal ripples unfolded.

Memory consolidation is the process of translating memory traces from the hippocampus to the cortex. Hippocampal ripples are key in driving this transfer. A new study now shows that independent cortical ripples can suppress this communication. What could be the underlying mechanisms?

Lifespan differences in hippocampal subregion connectivity patterns during movie watching.

Age-related episodic memory decline is attributed to functional alternations in the hippocampus. Less clear is how aging affects the functional connections of the hippocampus to the rest of the brain during episodic memory processing. We examined fMRI data from the CamCAN dataset, in which a large cohort of participants watched a movie (N = 643; 18-88 years), a proxy for naturalistic episodic memory encoding. We examined connectivity profiles across the lifespan both within the hippocampus (anterior, posterior), and between the hippocampal subregions and cortical networks. Aging was associated with reductions in contralateral (left, right) but not ipsilateral (anterior, posterior) hippocampal subregion connectivity. Aging was primarily associated with increased coupling between the anterior hippocampus and regions affiliated with Control, Dorsal Attention and Default Mode networks, yet decreased coupling between the posterior hippocampus and a selection of these regions. Differences in age-related hippocampal-cortical, but not within-hippocampus circuitry selectively predicted worse memory performance. Our findings comprehensively characterize hippocampal functional topography in relation to cognition in older age, suggesting that shifts in cortico-hippocampal connectivity may be sensitive markers of age-related episodic memory decline.

Using synchronized brain rhythms to bias memory-guided decisions.

Functional interactions between the prefrontal cortex and hippocampus, as revealed by strong oscillatory synchronization in the theta (6-11 Hz) frequency range, correlate with memory-guided decision-making. However, the degree to which this form of long-range synchronization influences memory-guided choice remains unclear. We developed a brain-machine interface that initiated task trials based on the magnitude of prefrontal-hippocampal theta synchronization, then measured choice outcomes. Trials initiated based on strong prefrontal-hippocampal theta synchrony were more likely to be correct compared to control trials on both working memory-dependent and -independent tasks. Prefrontal-thalamic neural interactions increased with prefrontal-hippocampal synchrony and optogenetic activation of the ventral midline thalamus primarily entrained prefrontal theta rhythms, but dynamically modulated synchrony. Together, our results show that prefrontal-hippocampal theta synchronization leads to a higher probability of a correct choice and strengthens prefrontal-thalamic dialogue. Our findings reveal new insights into the neural circuit dynamics underlying memory-guided choices and highlight a promising technique to potentiate cognitive processes or behavior via brain-machine interfacing.

Distinct neural mechanisms for heading retrieval and context recognition in the hippocampus during spatial reorientation.

Reorientation, the process of regaining one's bearings after becoming lost, requires identification of a spatial context (context recognition) and recovery of facing direction within that context (heading retrieval). We previously showed that these processes rely on the use of features and geometry, respectively. Here, we examine reorientation behavior in a task that creates contextual ambiguity over a long timescale to demonstrate that male mice learn to combine both featural and geometric cues to recover heading. At the neural level, most CA1 neurons persistently align to geometry, and this alignment predicts heading behavior. However, a small subset of cells remaps coherently in a context-sensitive manner, which serves to predict context. Efficient heading retrieval and context recognition correlate with rate changes reflecting integration of featural and geometric information in the active ensemble. These data illustrate how context recognition and heading retrieval are coded in CA1 and how these processes change with experience.

Extended Poisson Gaussian-Process Latent Variable Model for Unsupervised Neural Decoding.

Dimension reduction on neural activity paves a way for unsupervised neural decoding by dissociating the measurement of internal neural pattern reactivation from the measurement of external variable tuning. With assumptions only on the smoothness of latent dynamics and of internal tuning curves, the Poisson gaussian-process latent variable model (P-GPLVM; Wu et al., 2017) is a powerful tool to discover the low-dimensional latent structure for high-dimensional spike trains. However, when given novel neural data, the original model lacks a method to infer their latent trajectories in the learned latent space, limiting its ability for estimating the neural reactivation. Here, we extend the P-GPLVM to enable the latent variable inference of new data constrained by previously learned smoothness and mapping information. We also describe a principled approach for the constrained latent variable inference for temporally compressed patterns of activity, such as those found in population burst events during hippocampal sharp-wave ripples, as well as metrics for assessing the validity of neural pattern reactivation and inferring the encoded experience. Applying these approaches to hippocampal ensemble recordings during active maze exploration, we replicate the result that P-GPLVM learns a latent space encoding the animal's position. We further demonstrate that this latent space can differentiate one maze context from another. By inferring the latent variables of new neural data during running, certain neural patterns are observed to reactivate, in accordance with the similarity of experiences encoded by its nearby neural trajectories in the training data manifold. Finally, reactivation of neural patterns can be estimated for neural activity during population burst events as well, allowing the identification for replay events of versatile behaviors and more general experiences. Thus, our extension of the P-GPLVM framework for unsupervised analysis of neural activity can be used to answer critical questions related to scientific discovery.

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.

Hippocampal Engrams and Contextual Memory.

Memories are not formed in a vacuum and often include rich details about the time and place in which events occur. Contextual stimuli promote the retrieval of events that have previously occurred in the encoding context and limit the retrieval of context-inappropriate information. Contexts that are associated with traumatic or harmful events both directly elicit fear and serve as reminders of aversive events associated with trauma. It has long been appreciated that the hippocampus is involved in contextual learning and memory and is central to contextual fear conditioning. However, little is known about the underlying neuronal mechanisms underlying the encoding and retrieval of contextual fear memories. Recent advancements in neuronal labeling methods, including activity-dependent tagging of cellular ensembles encoding memory ("engrams"), provide unique insight into the neural substrates of memory in the hippocampus. Moreover, these methods allow for the selective manipulation of memory ensembles. Attenuating or erasing fear memories may have considerable therapeutic value for patients with post-traumatic stress disorder or other trauma- or stressor-related conditions. In this chapter, we review the role of the hippocampus in contextual fear conditioning in rodents and explore recent work implicating hippocampal ensembles in the encoding and retrieval of aversive memories.

The Role of Prefrontal Ensembles in Memory Across Time: Time-Dependent Transformations of Prefrontal Memory Ensembles.

The medial prefrontal cortex (mPFC) plays a critical role in recalling recent and remote fearful memories. Modern neuroscience techniques, such as projection-specific circuit manipulation and activity-dependent labeling, have illuminated how mPFC memory ensembles are reorganized over time. This chapter discusses the implications of new findings for traditional theories of memory, such as the systems consolidation theory and theories of memory engrams. It also examines the specific contributions of mPFC subregions, like the prelimbic and infralimbic cortices, in fear memory, highlighting how their distinct connections influence memory recall. Further, it elaborates on the cellular and molecular changes within the mPFC that support memory persistence and how these are influenced by interactions with the hippocampus. Ultimately, this chapter provides insights into how lasting memories are dynamically encoded in prefrontal circuits, arguing for a key role of memory ensembles that extend beyond strict definitions of the engram.

What Can Hippocampal Engrams Tell Us About Encoding Spatial Navigation?

The hippocampus is indispensable for episodic memories, but its particular role in the process is still unclear. This chapter briefly overviews past studies focusing on place cells and memory engrams, highlighting their potential roles in spatial navigation. Future work reconciling these two lines of studies would provide a comprehensive view of the specific contribution of the hippocampus and a better understanding of how memory engrams support memory.

Adult Neurogenesis, Context Encoding, and Pattern Separation: A Pathway for Treating Overgeneralization.

In mammals, the subgranular zone of the dentate gyrus is one of two brain regions (with the subventricular zone of the olfactory bulb) that continues to generate new neurons throughout adulthood, a phenomenon known as adult hippocampal neurogenesis (AHN) (Eriksson et al., Nat Med 4:1313-1317, 1998; García-Verdugo et al., J Neurobiol 36:234-248, 1998). The integration of these new neurons into the dentate gyrus (DG) has implications for memory encoding, with unique firing and wiring properties of immature neurons that affect how the hippocampal network encodes and stores attributes of memory. In this chapter, we will describe the process of AHN and properties of adult-born cells as they integrate into the hippocampal circuit and mature. Then, we will discuss some methodological considerations before we review evidence for the role of AHN in two major processes supporting memory that are performed by the DG. First, we will discuss encoding of contextual information for episodic memories and how this is facilitated by AHN. Second, will discuss pattern separation, a major role of the DG that reduces interference for the formation of new memories. Finally, we will review clinical and translational considerations, suggesting that stimulation of AHN may help decrease overgeneralization-a common endophenotype of mood, anxiety, trauma-related, and age-related disorders.

Exploring the Effect of Arsenic-Containing Hydrocarbon on the Bidirectional Synaptic Plasticity of the Dorsal Hippocampus.

Arsenic-containing hydrocarbons (AsHCs) are common in marine organisms. However, there is little research on their effects on the central nervous system's advanced activities, such as cognition. Bidirectional synaptic plasticity dynamically regulates cognition through the balance of long-term potentiation (LTP) and long-term depression (LTD). However, the effects of AsHCs on bidirectional synaptic plasticity and the underlying molecular mechanisms remain unexplored. This study provides the first evidence that 15 µg As L-1 AsHC 360 enhances bidirectional synaptic plasticity, occurring during the maintenance phase rather than the baseline phase. Further calcium gradient experiments hypothesize that AsHC 360 may enhance bidirectional synaptic plasticity by affecting calcium ion levels. The enhancement of bidirectional synaptic plasticity by 15 µg As L-1 AsHC 360 holds significant implications in improving cognitive function, treating neuro-psychiatric disorders, promoting neural recovery, and enhancing brain adaptability.

Cross-regional coordination of activity in the human brain during autobiographical self-referential processing.

For the human brain to operate, populations of neurons across anatomical structures must coordinate their activity within milliseconds. To date, our understanding of such interactions has remained limited. We recorded directly from the hippocampus (HPC), posteromedial cortex (PMC), ventromedial/orbital prefrontal cortex (OFC), and the anterior nuclei of the thalamus (ANT) during two experiments of autobiographical memory processing that are known from decades of neuroimaging work to coactivate these regions. In 31 patients implanted with intracranial electrodes, we found that the presentation of memory retrieval cues elicited a significant increase of low frequency (LF < 6 Hz) activity followed by cross-regional phase coherence of this LF activity before select populations of neurons within each of the four regions increased high-frequency (HF > 70 Hz) activity. The power of HF activity was modulated by memory content, and its onset followed a specific temporal order of ANT→HPC/PMC→OFC. Further, we probed cross-regional causal effective interactions with repeated electrical pulses and found that HPC stimulations cause the greatest increase in LF-phase coherence across all regions, whereas the stimulation of any region caused the greatest LF-phase coherence between that particular region and ANT. These observations support the role of the ANT in gating, and the HPC in synchronizing, the activity of cortical midline structures when humans retrieve self-relevant memories of their past. Our findings offer a fresh perspective, with high temporal fidelity, about the dynamic signaling and underlying causal connections among distant regions when the brain is actively involved in retrieving self-referential memories from the past.