Representational drift as a result of implicit regularization.

Recent studies show that, even in constant environments, the tuning of single neurons changes over time in a variety of brain regions. This representational drift has been suggested to be a consequence of continuous learning under noise, but its properties are still not fully understood. To investigate the underlying mechanism, we trained an artificial network on a simplified navigational task. The network quickly reached a state of high performance, and many units exhibited spatial tuning. We then continued training the network and noticed that the activity became sparser with time. Initial learning was orders of magnitude faster than ensuing sparsification. This sparsification is consistent with recent results in machine learning, in which networks slowly move within their solution space until they reach a flat area of the loss function. We analyzed four datasets from different labs, all demonstrating that CA1 neurons become sparser and more spatially informative with exposure to the same environment. We conclude that learning is divided into three overlapping phases: (i) Fast familiarity with the environment; (ii) slow implicit regularization; and (iii) a steady state of null drift. The variability in drift dynamics opens the possibility of inferring learning algorithms from observations of drift statistics.

Ventral tegmental area dopamine projections to the hippocampus trigger long-term potentiation and contextual learning.

In most models of neuronal plasticity and memory, dopamine is thought to promote the long-term maintenance of Long-Term Potentiation (LTP) underlying memory processes, but not the initiation of plasticity or new information storage. Here, we used optogenetic manipulation of midbrain dopamine neurons in male DAT::Cre mice, and discovered that stimulating the Schaffer collaterals - the glutamatergic axons connecting CA3 and CA1 regions - of the dorsal hippocampus concomitantly with midbrain dopamine terminals within a 200 millisecond time-window triggers LTP at glutamatergic synapses. Moreover, we showed that the stimulation of this dopaminergic pathway facilitates contextual learning in awake behaving mice, while its inhibition hinders it. Thus, activation of midbrain dopamine can operate as a teaching signal that triggers NeoHebbian LTP and promotes supervised learning.

Primacy of vision shapes behavioral strategies and neural substrates of spatial navigation in marmoset hippocampus.

The role of the hippocampus in spatial navigation has been primarily studied in nocturnal mammals, such as rats, that lack many adaptations for daylight vision. Here we demonstrate that during 3D navigation, the common marmoset, a new world primate adapted to daylight, predominantly uses rapid head-gaze shifts for visual exploration while remaining stationary. During active locomotion marmosets stabilize the head, in contrast to rats that use low-velocity head movements to scan the environment as they locomote. Pyramidal neurons in the marmoset hippocampus CA3/CA1 regions predominantly show mixed selectivity for 3D spatial view, head direction, and place. Exclusive place selectivity is scarce. Inhibitory interneurons are predominantly mixed selective for angular head velocity and translation speed. Finally, we found theta phase resetting of local field potential oscillations triggered by head-gaze shifts. Our findings indicate that marmosets adapted to their daylight ecological niche by modifying exploration/navigation strategies and their corresponding hippocampal specializations.

A non-canonical visual cortical-entorhinal pathway contributes to spatial navigation.

Visual information is important for accurate spatial coding and memory-guided navigation. As a crucial area for spatial cognition, the medial entorhinal cortex (MEC) harbors diverse spatially tuned cells and functions as the major gateway relaying sensory inputs to the hippocampus containing place cells. However, how visual information enters the MEC has not been fully understood. Here, we identify a pathway originating in the secondary visual cortex (V2) and directly targeting MEC layer 5a (L5a). L5a neurons served as a network hub for visual processing in the MEC by routing visual inputs from multiple V2 areas to other local neurons and hippocampal CA1. Interrupting this pathway severely impaired visual stimulus-evoked neural activity in the MEC and performance of mice in navigation tasks. These observations reveal a visual cortical-entorhinal pathway highlighting the role of MEC L5a in sensory information transmission, a function typically attributed to MEC superficial layers before.

Multiplexed representation of others in the hippocampal CA1 subfield of female mice.

Hippocampal place cells represent the position of a rodent within an environment. In addition, recent experiments show that the CA1 subfield of a passive observer also represents the position of a conspecific performing a spatial task. However, whether this representation is allocentric, egocentric or mixed is less clear. In this study we investigated the representation of others during free behavior and in a task where female mice learned to follow a conspecific for a reward. We found that most cells represent the position of others relative to self-position (social-vector cells) rather than to the environment, with a prevalence of purely egocentric coding modulated by context and mouse identity. Learning of a pursuit task improved the tuning of social-vector cells, but their number remained invariant. Collectively, our results suggest that the hippocampus flexibly codes the position of others in multiple coordinate systems, albeit favoring the self as a reference point.

Synaptic Information Storage Capacity Measured With Information Theory.

Variation in the strength of synapses can be quantified by measuring the anatomical properties of synapses. Quantifying precision of synaptic plasticity is fundamental to understanding information storage and retrieval in neural circuits. Synapses from the same axon onto the same dendrite have a common history of coactivation, making them ideal candidates for determining the precision of synaptic plasticity based on the similarity of their physical dimensions. Here, the precision and amount of information stored in synapse dimensions were quantified with Shannon information theory, expanding prior analysis that used signal detection theory (Bartol et al., 2015). The two methods were compared using dendritic spine head volumes in the middle of the stratum radiatum of hippocampal area CA1 as well-defined measures of synaptic strength. Information theory delineated the number of distinguishable synaptic strengths based on nonoverlapping bins of dendritic spine head volumes. Shannon entropy was applied to measure synaptic information storage capacity (SISC) and resulted in a lower bound of 4.1 bits and upper bound of 4.59 bits of information based on 24 distinguishable sizes. We further compared the distribution of distinguishable sizes and a uniform distribution using Kullback-Leibler divergence and discovered that there was a nearly uniform distribution of spine head volumes across the sizes, suggesting optimal use of the distinguishable values. Thus, SISC provides a new analytical measure that can be generalized to probe synaptic strengths and capacity for plasticity in different brain regions of different species and among animals raised in different conditions or during learning. How brain diseases and disorders affect the precision of synaptic plasticity can also be probed.

Loose patch clamp membrane current measurements in cornus ammonis 1 neurons in murine hippocampal slices.

Hippocampal pyramidal neuronal activity has been previously studied using conventional patch clamp in isolated cells and brain slices. We here introduce the loose patch clamping study of voltage-activated currents from in situ pyramidal neurons in murine cornus ammonis 1 hippocampal coronal slices. Depolarizing pulses of 15-ms duration elicited early transient inward, followed by transient and prolonged outward currents in the readily identifiable junctional region between the stratum pyramidalis (SP) and oriens (SO) containing pyramidal cell somas and initial segments. These resembled pyramidal cell currents previously recorded using conventional patch clamp. Shortening the depolarizing pulses to >1-2 ms continued to evoke transient currents; hyperpolarizing pulses to varying voltages evoked decays whose time constants could be shortened to <1 ms, clarifying the speed of clamping in this experimental system. The inward and outward currents had distinct pharmacological characteristics and voltage-dependent inactivation and recovery from inactivation. Comparative recordings from the SP, known to contain pyramidal cell somas, demonstrated similar current properties. Recordings from the SO and stratum radiatum demonstrated smaller inward and outward current magnitudes and reduced transient outward currents, consistent with previous conventional patch clamp results from their different interneuron types. The loose patch clamp method is thus useful for in situ studies of neurons in hippocampal brain slices.

Morpho-electric diversity of human hippocampal CA1 pyramidal neurons.

Hippocampal pyramidal neuron activity underlies episodic memory and spatial navigation. Although extensively studied in rodents, extremely little is known about human hippocampal pyramidal neurons, even though the human hippocampus underwent strong evolutionary reorganization and shows lower theta rhythm frequencies. To test whether biophysical properties of human Cornu Amonis subfield 1 (CA1) pyramidal neurons can explain observed rhythms, we map the morpho-electric properties of individual CA1 pyramidal neurons in human, non-pathological hippocampal slices from neurosurgery. Human CA1 pyramidal neurons have much larger dendritic trees than mouse CA1 pyramidal neurons, have a large number of oblique dendrites, and resonate at 2.9 Hz, optimally tuned to human theta frequencies. Morphological and biophysical properties suggest cellular diversity along a multidimensional gradient rather than discrete clustering. Across the population, dendritic architecture and a large number of oblique dendrites consistently boost memory capacity in human CA1 pyramidal neurons by an order of magnitude compared to mouse CA1 pyramidal neurons.

Electrophysiological Properties of the Medial Mammillary Bodies across the Sleep-Wake Cycle.

The medial mammillary bodies (MBs) play an important role in the formation of spatial memories; their dense inputs from hippocampal and brainstem regions makes them well placed to integrate movement-related and spatial information, which is then extended to the anterior thalamic nuclei and beyond to the cortex. While the anatomical connectivity of the medial MBs has been well studied, much less is known about their physiological properties, particularly in freely moving animals. We therefore carried out a comprehensive characterization of medial MB electrophysiology across arousal states by concurrently recording from the medial MB and the CA1 field of the hippocampus in male rats. In agreement with previous studies, we found medial MB neurons to have firing rates modulated by running speed and angular head velocity, as well as theta-entrained firing. We extended the characterization of MB neuron electrophysiology in three key ways: (1) we identified a subset of neurons (25%) that exhibit dominant bursting activity; (2) we showed that ∼30% of theta-entrained neurons exhibit robust theta cycle skipping, a firing characteristic that implicates them in a network for prospective coding of position; and (3) a considerable proportion of medial MB units showed sharp-wave ripple (SWR) responsive firing (∼37%). The functional heterogeneity of MB electrophysiology reinforces their role as an integrative node for mnemonic processing and identifies potential roles for the MBs in memory consolidation through propagation of SWR-responsive activity to the anterior thalamus and prospective coding in the form of theta cycle skipping.

Mismatch novelty exploration training shifts VPAC1 receptor-mediated modulation of hippocampal synaptic plasticity by endogenous VIP in male rats.

Novelty influences hippocampal-dependent memory through metaplasticity. Mismatch novelty detection activates the human hippocampal CA1 area and enhances rat hippocampal-dependent learning and exploration. Remarkably, mismatch novelty training (NT) also enhances rodent hippocampal synaptic plasticity while inhibition of VIP interneurons promotes rodent exploration. Since VIP, acting on VPAC1 receptors (Rs), restrains hippocampal LTP and depotentiation by modulating disinhibition, we now investigated the impact of NT on VPAC1 modulation of hippocampal synaptic plasticity in male Wistar rats. NT enhanced both CA1 hippocampal LTP and depotentiation unlike exploring an empty holeboard (HT) or a fixed configuration of objects (FT). Blocking VIP VPAC1Rs with PG 97269 (100 nM) enhanced both LTP and depotentiation in naïve animals, but this effect was less effective in NT rats. Altered endogenous VIP modulation of LTP was absent in animals exposed to the empty environment (HT). HT and FT animals showed mildly enhanced synaptic VPAC1R levels, but neither VIP nor VPAC1R levels were altered in NT animals. Conversely, NT enhanced the GluA1/GluA2 AMPAR ratio and gephyrin synaptic content but not PSD-95 excitatory synaptic marker. In conclusion, NT influences hippocampal synaptic plasticity by reshaping brain circuits modulating disinhibition and its control by VIP-expressing hippocampal interneurons while upregulation of VIP VPAC1Rs is associated with the maintenance of VIP control of LTP in FT and HT animals. This suggests VIP receptor ligands may be relevant to co-adjuvate cognitive recovery therapies in aging or epilepsy, where LTP/LTD imbalance occurs.

Modeling realistic synaptic inputs of CA1 hippocampal pyramidal neurons and interneurons via Adaptive Generalized Leaky Integrate-and-Fire models.

Computational models of brain regions are crucial for understanding neuronal network dynamics and the emergence of cognitive functions. However, current supercomputing limitations hinder the implementation of large networks with millions of morphological and biophysical accurate neurons. Consequently, research has focused on simplified spiking neuron models, ranging from the computationally fast Leaky Integrate and Fire (LIF) linear models to more sophisticated non-linear implementations like Adaptive Exponential (AdEX) and Izhikevic models, through Generalized Leaky Integrate and Fire (GLIF) approaches. However, in almost all cases, these models are tuned (and can be validated) only under constant current injections and they may not, in general, also reproduce experimental findings under variable currents. This study introduces an Adaptive GLIF (A-GLIF) approach that addresses this limitation by incorporating a new set of update rules. The extended A-GLIF model successfully reproduces both constant and variable current inputs, and it was validated against the results obtained using a biophysical accurate model neuron. This enhancement provides researchers with a tool to optimize spiking neuron models using classic experimental traces under constant current injections, reliably predicting responses to synaptic inputs, which can be confidently used for large-scale network implementations.

Mouse hippocampal CA1 VIP interneurons detect novelty in the environment and support recognition memory.

In the CA1 hippocampus, vasoactive intestinal polypeptide-expressing interneurons (VIP-INs) play a prominent role in disinhibitory circuit motifs. However, the specific behavioral conditions that lead to circuit disinhibition remain uncertain. To investigate the behavioral relevance of VIP-IN activity, we employed wireless technologies allowing us to monitor and manipulate their function in freely behaving mice. Our findings reveal that, during spatial exploration in new environments, VIP-INs in the CA1 hippocampal region become highly active, facilitating the rapid encoding of novel spatial information. Remarkably, both VIP-INs and pyramidal neurons (PNs) exhibit increased activity when encountering novel changes in the environment, including context- and object-related alterations. Concurrently, somatostatin- and parvalbumin-expressing inhibitory populations show an inverse relationship with VIP-IN and PN activity, revealing circuit disinhibition that occurs on a timescale of seconds. Thus, VIP-IN-mediated disinhibition may constitute a crucial element in the rapid encoding of novelty and the acquisition of recognition memory.

GADD45B in the ventral hippocampal CA1 modulates aversive memory acquisition and spatial cognition.

AIMS: This study was designed to investigate the role of growth arrest and DNA damage-inducible ß (GADD45B) in modulating fear memory acquisition and elucidate its underlying mechanisms. MAIN METHODS: Adeno-associated virus (AAV) that knockdown or overexpression GADD45B were injected into ventral hippocampal CA1 (vCA1) by stereotactic, and verified by fluorescence and Western blot. The contextual fear conditioning paradigm was employed to examine the involvement of GADD45B in modulating aversive memory acquisition. The Y-maze and novel location recognition (NLR) tests were used to examine non-aversive cognition. The synaptic plasticity and electrophysiological properties of neurons were measured by slice patch clamp. KEY FINDINGS: Knockdown of GADD45B in the vCA1 significantly enhanced fear memory acquisition, accompanied by an upregulation of long-term potentiation (LTP) expression and intrinsic excitability of vCA1 pyramidal neurons (PNs). Conversely, overexpression of GADD45B produced the opposite effects. Notably, silencing the activity of vCA1 neurons abolished the impact of GADD45B knockdown on fear memory development. Moreover, mice with vCA1 GADD45B overexpression exhibited impaired spatial cognition, whereas mice with GADD45B knockdown did not display such impairment. SIGNIFICANCE: These results provided compelling evidence for the crucial involvement of GADD45B in the formation of aversive memory and spatial cognition.

Mathematical generation of data-driven hippocampal CA1 pyramidal neurons and interneurons copies via A-GLIF models for large-scale networks covering the experimental variability range.

Efficient and accurate large-scale networks are a fundamental tool in modeling brain areas, to advance our understanding of neuronal dynamics. However, their implementation faces two key issues: computational efficiency and heterogeneity. Computational efficiency is achieved using simplified neurons, whereas there are no practical solutions available to solve the problem of reproducing in a large-scale network the experimentally observed heterogeneity of the intrinsic properties of neurons. This is important, because the use of identical nodes in a network can generate artifacts which can hinder an adequate representation of the properties of a real network. To this aim, we introduce a mathematical procedure to generate an arbitrary large number of copies of simplified hippocampal CA1 pyramidal neurons and interneurons models, which exhibit the full range of firing dynamics observed in these cells - including adapting, non-adapting and bursting. For this purpose, we rely on a recently published adaptive generalized leaky integrate-and-fire (A-GLIF) modeling approach, leveraging on its ability to reproduce the rich set of electrophysiological behaviors of these types of neurons under a variety of different stimulation currents. The generation procedure is based on a perturbation of model's parameters related to the initial data, firing block, and internal dynamics, and suitably validated against experimental data to ensure that the firing dynamics of any given cell copy remains within the experimental range. A classification procedure confirmed that the firing behavior of most of the pyramidal/interneuron copies was consistent with the experimental data. This approach allows to obtain heterogeneous copies with mathematically controlled firing properties. A full set of heterogeneous neurons composing the CA1 region of a rat hippocampus (approximately 1.2 million neurons), are provided in a database freely available in the live paper section of the EBRAINS platform. By adapting the underlying A-GLIF framework, it will be possible to extend the numerical approach presented here to create, in a mathematically controlled manner, an arbitrarily large number of non-identical copies of cell populations with firing properties related to other brain areas.

Dynamics of neuronal firing modulated by high-frequency electrical pulse stimulations at axons in rat hippocampus.

Objective. The development of electrical pulse stimulations in brain, including deep brain stimulation, is promising for treating various brain diseases. However, the mechanisms of brain stimulations are not yet fully understood. Previous studies have shown that the commonly used high-frequency stimulation (HFS) can increase the firing of neurons and modulate the pattern of neuronal firing. Because the generation of neuronal firing in brain is a nonlinear process, investigating the characteristics of nonlinear dynamics induced by HFS could be helpful to reveal more mechanisms of brain stimulations. The aim of present study is to investigate the fractal properties in the neuronal firing generated by HFS.Approach. HFS pulse sequences with a constant frequency 100 Hz were applied in the afferent fiber tracts of rat hippocampal CA1 region. Unit spikes of both the pyramidal cells and the interneurons in the downstream area of stimulations were recorded. Two fractal indexes-the Fano factor and Hurst exponent were calculated to evaluate the changes of long-range temporal correlations (LRTCs), a typical characteristic of fractal process, in spike sequences of neuronal firing.Mainresults. Neuronal firing at both baseline and during HFS exhibited LRTCs over multiple time scales. In addition, the LRTCs significantly increased during HFS, which was confirmed by simulation data of both randomly shuffled sequences and surrogate sequences.Conclusion. The purely periodic stimulation of HFS pulses, a non-fractal process without LRTCs, can increase rather than decrease the LRTCs in neuronal firing.Significance. The finding provides new nonlinear mechanisms of brain stimulation and suggests that LRTCs could be a new biomarker to evaluate the nonlinear effects of HFS.

A voltage-based Event-Timing-Dependent Plasticity rule accounts for LTP subthreshold and suprathreshold for dendritic spikes in CA1 pyramidal neurons.

Long-term potentiation (LTP) is a synaptic mechanism involved in learning and memory. Experiments have shown that dendritic sodium spikes (Na-dSpikes) are required for LTP in the distal apical dendrites of CA1 pyramidal cells. On the other hand, LTP in perisomatic dendrites can be induced by synaptic input patterns that can be both subthreshold and suprathreshold for Na-dSpikes. It is unclear whether these results can be explained by one unifying plasticity mechanism. Here, we show in biophysically and morphologically realistic compartmental models of the CA1 pyramidal cell that these forms of LTP can be fully accounted for by a simple plasticity rule. We call it the voltage-based Event-Timing-Dependent Plasticity (ETDP) rule. The presynaptic event is the presynaptic spike or release of glutamate. The postsynaptic event is the local depolarization that exceeds a certain plasticity threshold. Our model reproduced the experimentally observed LTP in a variety of protocols, including local pharmacological inhibition of dendritic spikes by tetrodotoxin (TTX). In summary, we have provided a validation of the voltage-based ETDP, suggesting that this simple plasticity rule can be used to model even complex spatiotemporal patterns of long-term synaptic plasticity in neuronal dendrites.

Silencing CA1 pyramidal cells output reveals the role of feedback inhibition in hippocampal oscillations.

The precise temporal coordination of neural activity is crucial for brain function. In the hippocampus, this precision is reflected in the oscillatory rhythms observed in CA1. While it is known that a balance between excitatory and inhibitory activity is necessary to generate and maintain these oscillations, the differential contribution of feedforward and feedback inhibition remains ambiguous. Here we use conditional genetics to chronically silence CA1 pyramidal cell transmission, ablating the ability of these neurons to recruit feedback inhibition in the local circuit, while recording physiological activity in mice. We find that this intervention leads to local pathophysiological events, with ripple amplitude and intrinsic frequency becoming significantly larger and spatially triggered local population spikes locked to the trough of the theta oscillation appearing during movement. These phenotypes demonstrate that feedback inhibition is crucial in maintaining local sparsity of activation and reveal the key role of lateral inhibition in CA1 in shaping circuit function.

Formation of memory assemblies through the DNA-sensing TLR9 pathway.

As hippocampal neurons respond to diverse types of information1, a subset assembles into microcircuits representing a memory2. Those neurons typically undergo energy-intensive molecular adaptations, occasionally resulting in transient DNA damage3-5. Here we found discrete clusters of excitatory hippocampal CA1 neurons with persistent double-stranded DNA (dsDNA) breaks, nuclear envelope ruptures and perinuclear release of histone and dsDNA fragments hours after learning. Following these early events, some neurons acquired an inflammatory phenotype involving activation of TLR9 signalling and accumulation of centrosomal DNA damage repair complexes6. Neuron-specific knockdown of Tlr9 impaired memory while blunting contextual fear conditioning-induced changes of gene expression in specific clusters of excitatory CA1 neurons. Notably, TLR9 had an essential role in centrosome function, including DNA damage repair, ciliogenesis and build-up of perineuronal nets. We demonstrate a novel cascade of learning-induced molecular events in discrete neuronal clusters undergoing dsDNA damage and TLR9-mediated repair, resulting in their recruitment to memory circuits. With compromised TLR9 function, this fundamental memory mechanism becomes a gateway to genomic instability and cognitive impairments implicated in accelerated senescence, psychiatric disorders and neurodegenerative disorders. Maintaining the integrity of TLR9 inflammatory signalling thus emerges as a promising preventive strategy for neurocognitive deficits.

Excitability mediates allocation of pre-configured ensembles to a hippocampal engram supporting contextual conditioned threat in mice.

Little is understood about how engrams, sparse groups of neurons that store memories, are formed endogenously. Here, we combined calcium imaging, activity tagging, and optogenetics to examine the role of neuronal excitability and pre-existing functional connectivity on the allocation of mouse cornu ammonis area 1 (CA1) hippocampal neurons to an engram ensemble supporting a contextual threat memory. Engram neurons (high activity during recall or TRAP2-tagged during training) were more active than non-engram neurons 3 h (but not 24 h to 5 days) before training. Consistent with this, optogenetically inhibiting scFLARE2-tagged neurons active in homecage 3 h, but not 24 h, before conditioning disrupted memory retrieval, indicating that neurons with higher pre-training excitability were allocated to the engram. We also observed stable pre-configured functionally connected sub-ensembles of neurons whose activity cycled over days. Sub-ensembles that were more active before training were allocated to the engram, and their functional connectivity increased at training. Therefore, both neuronal excitability and pre-configured functional connectivity mediate allocation to an engram ensemble.

Selection of experience for memory by hippocampal sharp wave ripples.

Experiences need to be tagged during learning for further consolidation. However, neurophysiological mechanisms that select experiences for lasting memory are not known. By combining large-scale neural recordings in mice with dimensionality reduction techniques, we observed that successive maze traversals were tracked by continuously drifting populations of neurons, providing neuronal signatures of both places visited and events encountered. When the brain state changed during reward consumption, sharp wave ripples (SPW-Rs) occurred on some trials, and their specific spike content decoded the trial blocks that surrounded them. During postexperience sleep, SPW-Rs continued to replay those trial blocks that were reactivated most frequently during waking SPW-Rs. Replay content of awake SPW-Rs may thus provide a neurophysiological tagging mechanism to select aspects of experience that are preserved and consolidated for future use.