Intra-ripple frequency accommodation in an inhibitory network model for hippocampal ripple oscillations.

Hippocampal ripple oscillations have been implicated in important cognitive functions such as memory consolidation and planning. Multiple computational models have been proposed to explain the emergence of ripple oscillations, relying either on excitation or inhibition as the main pacemaker. Nevertheless, the generating mechanism of ripples remains unclear. An interesting dynamical feature of experimentally measured ripples, which may advance model selection, is intra-ripple frequency accommodation (IFA): a decay of the instantaneous ripple frequency over the course of a ripple event. So far, only a feedback-based inhibition-first model, which relies on delayed inhibitory synaptic coupling, has been shown to reproduce IFA. Here we use an analytical mean-field approach and numerical simulations of a leaky integrate-and-fire spiking network to explain the mechanism of IFA. We develop a drift-based approximation for the oscillation dynamics of the population rate and the mean membrane potential of interneurons under strong excitatory drive and strong inhibitory coupling. For IFA, the speed at which the excitatory drive changes is critical. We demonstrate that IFA arises due to a speed-dependent hysteresis effect in the dynamics of the mean membrane potential, when the interneurons receive transient, sharp wave-associated excitation. We thus predict that the IFA asymmetry vanishes in the limit of slowly changing drive, but is otherwise a robust feature of the feedback-based inhibition-first ripple model.

Structure and function of the hippocampal CA3 module.

The hippocampal formation is crucial for learning and memory, with submodule CA3 thought to be the substrate of pattern completion. However, the underlying synaptic and computational mechanisms of this network are not well understood. Here, we perform circuit reconstruction of a CA3 module using three dimensional (3D) electron microscopy data and combine this with functional connectivity recordings and computational simulations to determine possible CA3 network mechanisms. Direct measurements of connectivity schemes with both physiological measurements and structural 3D EM revealed a high connectivity rate, multi-fold higher than previously assumed. Mathematical modelling indicated that such CA3 networks can robustly generate pattern completion and replay memory sequences. In conclusion, our data demonstrate that the connectivity scheme of the hippocampal submodule is well suited for efficient memory storage and retrieval.

Experience-Dependent Plasticity in Nucleus Laminaris of the Barn Owl.

Interaural time differences (ITDs) are a major cue for sound localization and change with increasing head size. Since the barn owl's head width more than doubles in the month after hatching, we hypothesized that the development of their ITD detection circuit might be modified by experience. To test this, we raised owls with unilateral ear inserts that delayed and attenuated the acoustic signal, and then measured the ITD representation in the brainstem nucleus laminaris (NL) when they were adults. The ITD circuit is composed of delay line inputs to coincidence detectors, and we predicted that plastic changes would lead to shorter delays in the axons from the manipulated ear, and complementary shifts in ITD representation on the two sides. In owls that received ear inserts starting around P14, the maps of ITD shifted in the predicted direction, but only on the ipsilateral side, and only in those tonotopic regions that had not experienced auditory stimulation prior to insertion. The contralateral map did not change. Thus, experience-dependent plasticity of the ITD circuit occurs in NL, and our data suggest that ipsilateral and contralateral delays are independently regulated. As a result, altered auditory input during development leads to long-lasting changes in the representation of ITD.Significance Statement The early life of barn owls is marked by increasing sensitivity to sound, and by increasing ITDs. Their prolonged post-hatch development allowed us to examine the role of altered auditory experience in the development of ITD detection circuits. We raised owls with a unilateral ear insert and found that their maps of ITD were altered by experience, but only in those tonotopic regions ipsilateral to the occluded ear that had not experienced auditory stimulation prior to insertion. This experience-induced plasticity allows the sound localization circuits to be customized to individual characteristics, such as the size of the head, and potentially to compensate for imbalanced hearing sensitivities between the left and right ears.

Experience-Dependent Plasticity in Nucleus Laminaris of the Barn Owl.

Barn owls experience increasing interaural time differences (ITDs) during development, because their head width more than doubles in the month after hatching. We therefore hypothesized that their ITD detection circuit might be modified by experience. To test this, we raised owls with unilateral ear inserts that delayed and attenuated the acoustic signal, then measured the ITD representation in the brainstem nucleus laminaris (NL) when they were adult. The ITD circuit is composed of delay line inputs to coincidence detectors, and we predicted that plastic changes would lead to shorter delays in the axons from the manipulated ear, and complementary shifts in ITD representation on the two sides. In owls that received ear inserts starting around P14, the maps of ITD shifted in the predicted direction, but only on the ipsilateral side, and only in those tonotopic regions that had not experienced auditory stimulation prior to insertion. The contralateral map did not change. Experience-dependent plasticity of the ITD circuit occurs in NL, and our data suggest that ipsilateral and contralateral delays are independently regulated. Thus, altered auditory input during development leads to long-lasting changes in the representation of ITD.

Learning accurate path integration in ring attractor models of the head direction system.

Ring attractor models for angular path integration have received strong experimental support. To function as integrators, head direction circuits require precisely tuned connectivity, but it is currently unknown how such tuning could be achieved. Here, we propose a network model in which a local, biologically plausible learning rule adjusts synaptic efficacies during development, guided by supervisory allothetic cues. Applied to the Drosophila head direction system, the model learns to path-integrate accurately and develops a connectivity strikingly similar to the one reported in experiments. The mature network is a quasi-continuous attractor and reproduces key experiments in which optogenetic stimulation controls the internal representation of heading in flies, and where the network remaps to integrate with different gains in rodents. Our model predicts that path integration requires self-supervised learning during a developmental phase, and proposes a general framework to learn to path-integrate with gain-1 even in architectures that lack the physical topography of a ring.

Microcircuits for spatial coding in the medial entorhinal cortex.

The hippocampal formation is critically involved in learning and memory and contains a large proportion of neurons encoding aspects of the organism's spatial surroundings. In the medial entorhinal cortex (MEC), this includes grid cells with their distinctive hexagonal firing fields as well as a host of other functionally defined cell types including head direction cells, speed cells, border cells, and object-vector cells. Such spatial coding emerges from the processing of external inputs by local microcircuits. However, it remains unclear exactly how local microcircuits and their dynamics within the MEC contribute to spatial discharge patterns. In this review we focus on recent investigations of intrinsic MEC connectivity, which have started to describe and quantify both excitatory and inhibitory wiring in the superficial layers of the MEC. Although the picture is far from complete, it appears that these layers contain robust recurrent connectivity that could sustain the attractor dynamics posited to underlie grid pattern formation. These findings pave the way to a deeper understanding of the mechanisms underlying spatial navigation and memory.

Hebbian plasticity in parallel synaptic pathways: A circuit mechanism for systems memory consolidation.

Systems memory consolidation involves the transfer of memories across brain regions and the transformation of memory content. For example, declarative memories that transiently depend on the hippocampal formation are transformed into long-term memory traces in neocortical networks, and procedural memories are transformed within cortico-striatal networks. These consolidation processes are thought to rely on replay and repetition of recently acquired memories, but the cellular and network mechanisms that mediate the changes of memories are poorly understood. Here, we suggest that systems memory consolidation could arise from Hebbian plasticity in networks with parallel synaptic pathways-two ubiquitous features of neural circuits in the brain. We explore this hypothesis in the context of hippocampus-dependent memories. Using computational models and mathematical analyses, we illustrate how memories are transferred across circuits and discuss why their representations could change. The analyses suggest that Hebbian plasticity mediates consolidation by transferring a linear approximation of a previously acquired memory into a parallel pathway. Our modelling results are further in quantitative agreement with lesion studies in rodents. Moreover, a hierarchical iteration of the mechanism yields power-law forgetting-as observed in psychophysical studies in humans. The predicted circuit mechanism thus bridges spatial scales from single cells to cortical areas and time scales from milliseconds to years.

A neural code for egocentric spatial maps in the human medial temporal lobe.

Spatial navigation and memory rely on neural systems that encode places, distances, and directions in relation to the external world or relative to the navigating organism. Place, grid, and head-direction cells form key units of world-referenced, allocentric cognitive maps, but the neural basis of self-centered, egocentric representations remains poorly understood. Here, we used human single-neuron recordings during virtual spatial navigation tasks to identify neurons providing a neural code for egocentric spatial maps in the human brain. Consistent with previous observations in rodents, these neurons represented egocentric bearings toward reference points positioned throughout the environment. Egocentric bearing cells were abundant in the parahippocampal cortex and supported vectorial representations of egocentric space by also encoding distances toward reference points. Beyond navigation, the observed neurons showed activity increases during spatial and episodic memory recall, suggesting that egocentric bearing cells are not only relevant for navigation but also play a role in human memory.

Synaptic learning rules for sequence learning.

Remembering the temporal order of a sequence of events is a task easily performed by humans in everyday life, but the underlying neuronal mechanisms are unclear. This problem is particularly intriguing as human behavior often proceeds on a time scale of seconds, which is in stark contrast to the much faster millisecond time-scale of neuronal processing in our brains. One long-held hypothesis in sequence learning suggests that a particular temporal fine-structure of neuronal activity - termed 'phase precession' - enables the compression of slow behavioral sequences down to the fast time scale of the induction of synaptic plasticity. Using mathematical analysis and computer simulations, we find that - for short enough synaptic learning windows - phase precession can improve temporal-order learning tremendously and that the asymmetric part of the synaptic learning window is essential for temporal-order learning. To test these predictions, we suggest experiments that selectively alter phase precession or the learning window and evaluate memory of temporal order.

Recurrent amplification of grid-cell activity.

High-level cognitive abilities such as navigation and spatial memory are thought to rely on the activity of grid cells in the medial entorhinal cortex (MEC), which encode the animal's position in space with periodic triangular patterns. Yet the neural mechanisms that underlie grid-cell activity are still unknown. Recent in vitro and in vivo experiments indicate that grid cells are embedded in highly structured recurrent networks. But how could recurrent connectivity become structured during development? And what is the functional role of these connections? With mathematical modeling and simulations, we show that recurrent circuits in the MEC could emerge under the supervision of weakly grid-tuned feedforward inputs. We demonstrate that a learned excitatory connectivity could amplify grid patterns when the feedforward sensory inputs are available and sustain attractor states when the sensory cues are lost. Finally, we propose a Fourier-based measure to quantify the spatial periodicity of grid patterns: the grid-tuning index.

Generation of Sharp Wave-Ripple Events by Disinhibition.

Sharp wave-ripple complexes (SWRs) are hippocampal network phenomena involved in memory consolidation. To date, the mechanisms underlying their occurrence remain obscure. Here, we show how the interactions between pyramidal cells, parvalbumin-positive (PV+) basket cells, and an unidentified class of anti-SWR interneurons can contribute to the initiation and termination of SWRs. Using a biophysically constrained model of a network of spiking neurons and a rate-model approximation, we demonstrate that SWRs emerge as a result of the competition between two interneuron populations and the resulting disinhibition of pyramidal cells. Our models explain how the activation of pyramidal cells or PV+ cells can trigger SWRs, as shown in vitro, and suggests that PV+ cell-mediated short-term synaptic depression influences the experimentally reported dynamics of SWR events. Furthermore, we predict that the silencing of anti-SWR interneurons can trigger SWRs. These results broaden our understanding of the microcircuits supporting the generation of memory-related network dynamics.SIGNIFICANCE STATEMENT The hippocampus is a part of the mammalian brain that is crucial for episodic memories. During periods of sleep and inactive waking, the extracellular activity of the hippocampus is dominated by sharp wave-ripple events (SWRs), which have been shown to be important for memory consolidation. The mechanisms regulating the emergence of these events are still unclear. We developed a computational model to study the emergence of SWRs and to explain the roles of different cell types in regulating them. The model accounts for several previously unexplained features of SWRs and thus advances the understanding of memory-related dynamics.

Propofol Modulates Early Memory Consolidation in Humans.

Maintenance of memory across time is crucial for adaptive behavior. Current theories posit that the underlying consolidation process depends on stabilization of synapses and reorganization of interactions between hippocampus and neocortex. However, the temporal properties of hippocampal-neocortical network reconfiguration during consolidation are still a matter of debate. Translational research on this issue is challenged by the paucity of techniques to transiently interfere with memory in the healthy human brain. Here, we report a neuro-pharmacological approach with the GABAAergic anesthetic propofol and a memory task sensitive to hippocampal dysfunction. Patients undergoing minor surgery learned word lists before injection of an anesthetic dose of propofol. Results show that administration of the drug shortly after learning (∼13 min) impairs recall after awakening but spares recognition. By contrast, later administration (∼105 min) has no effect. These findings suggest significant changes in memory networks very early after learning that are decisive for later recall. Propofol general anesthesia provides an experimental tool to modulate the first steps of hippocampus-mediated memory consolidation in humans.

Spikelets in pyramidal neurons: generating mechanisms, distinguishing properties, and functional implications.

Spikelets are small spike-like depolarizations that are found in somatic recordings of many neuron types. Spikelets have been assigned important functions, ranging from neuronal synchronization to the regulation of synaptic plasticity, which are specific to the particular mechanism of spikelet generation. As spikelets reflect spiking activity in neuronal compartments that are electrotonically distinct from the soma, four modes of spikelet generation can be envisaged: (1) dendritic spikes or (2) axonal action potentials occurring in a single cell as well as action potentials transmitted via (3) gap junctions or (4) ephaptic coupling in pairs of neurons. In one of the best studied neuron type, cortical pyramidal neurons, the origins and functions of spikelets are still unresolved; all four potential mechanisms have been proposed, but the experimental evidence remains ambiguous. Here we attempt to reconcile the scattered experimental findings in a coherent theoretical framework. We review in detail the various mechanisms that can give rise to spikelets. For each mechanism, we present the biophysical underpinnings as well as the resulting properties of spikelets and compare these predictions to experimental data from pyramidal neurons. We also discuss the functional implications of each mechanism. On the example of pyramidal neurons, we illustrate that several independent spikelet-generating mechanisms fulfilling vastly different functions might be operating in a single cell.

Dynamics of synaptic extracellular field potentials in the nucleus laminaris of the barn owl.

Synaptic currents are frequently assumed to make a major contribution to the extracellular field potential (EFP). However, in any neuronal population, the explicit separation of synaptic sources from other contributions such as postsynaptic spikes remains a challenge. Here we take advantage of the simple organization of the barn owl nucleus laminaris (NL) in the auditory brain stem to isolate synaptic currents through the iontophoretic application of the α-amino-3-hydroxy-5-methyl-4-isoxazolepropionic acid (AMPA)-receptor antagonist 1,2,3,4-tetrahydro-6-nitro-2,3-dioxo-benzo[ f]quinoxaline-7-sulfonamide (NBQX). Responses to auditory stimulation show that the temporal dynamics of the evoked synaptic contributions to the EFP are consistent with synaptic short-term depression (STD). The estimated time constants of an STD model fitted to the data are similar to the fast time constants reported from in vitro experiments in the chick. Overall, the putative synaptic EFPs in the barn owl NL are significant but small (<1% change of the variance by NBQX). This result supports the hypothesis that the EFP in NL is generated mainly by axonal spikes, in contrast to most other neuronal systems. NEW & NOTEWORTHY Synaptic currents are assumed to make a major contribution to the extracellular field potential in the brain, but it is hard to directly isolate these synaptic components. Here we take advantage of the simple organization of the barn owl nucleus laminaris in the auditory brain stem to isolate synaptic currents through the iontophoretic application of a synaptic blocker. We show that the responses are consistent with a simple model of short-term synaptic depression.

Interneuronal gap junctions increase synchrony and robustness of hippocampal ripple oscillations.

Sharp wave-ripples (SWRs) are important for memory consolidation. Their signature in the hippocampal extracellular field potential can be decomposed into a ≈100 ms long sharp wave superimposed by ≈200 Hz ripple oscillations. How ripple oscillations are generated is currently not well understood. A promising model for the genesis of ripple oscillations is based on recurrent interneuronal networks (INT-INT). According to this hypothesis, the INT-INT network in CA1 receives a burst of excitation from CA3 that generates the sharp wave, and recurrent inhibition leads to an ultrafast synchronization of the CA1 network causing the ripple oscillations; fast-spiking parvalbumin-positive basket cells (PV+  BCs) may constitute the ripple-generating interneuronal network. PV+  BCs are also coupled by gap junctions (GJs) but the function of GJs for ripple oscillations has not been quantified. Using simulations of CA1 hippocampal networks of PV+  BCs, we show that GJs promote synchrony beyond a level that could be obtained by only inhibition. GJs also increase the neuronal firing rate of the interneuronal ensemble, while they affect the ripple frequency only mildly. The promoting effect of GJs on ripple oscillations depends on fast GJ transmission ( ≲ 0.5 ms), which requires proximal GJ coupling ( ≲ 100 µm from soma), but is robust to variability in the delay and the amplitude of GJ coupling.

Extracellular waveforms reveal an axonal origin of spikelets in pyramidal neurons.

Spikelets are small spike-like membrane depolarizations measured at the soma whose origin in pyramidal neurons is still unresolved. We investigated the mechanism of spikelet generation using detailed models of pyramidal neurons. We simulated extracellular waveforms associated with action potentials and spikelets and compared these with experimental data obtained by Chorev and Brecht ( J Neurophysiol 108: 1584-1593, 2012) from hippocampal pyramidal neurons in vivo. We considered spikelets originating in the axon of a single cell as well as spikelets generated in two cells coupled with gap junctions. We found that in both cases the experimental data can be explained by an axonal origin of spikelets: in the single-cell case, action potentials are generated in the axon but fail to activate the soma. Such spikelets can be evoked by dendritic input. Alternatively, spikelets resulting from axoaxonal gap junction coupling with a large (greater than several hundred µm) distance between the somata of the coupled cells are also consistent with the data. Our results demonstrate that a cell firing a somatic spikelet generates a detectable extracellular potential that is different from the action potential-correlated extracellular waveform generated by the same cell and recorded at the same location. This, together with the absence of a refractory period between action potentials and spikelets, implies that spikelets and action potentials generated in one cell may easily get misclassified in extracellular recordings as two different cells, albeit they both constitute the output of a single pyramidal neuron. NEW & NOTEWORTHY We addressed the origin of spikelets, using compartmental models of pyramidal neurons. Comparing our simulation results with published extracellular spikelet recordings revealed an axonal origin of spikelets. Our results imply that action potential- and spikelet-associated extracellular waveforms may easily get misclassified as two different cells, albeit they both constitute the output of a single pyramidal cell.

Hippocampal Ripple Oscillations and Inhibition-First Network Models: Frequency Dynamics and Response to GABA Modulators.

Hippocampal ripples are involved in memory consolidation, but the mechanisms underlying their generation remain unclear. Models relying on interneuron networks in the CA1 region disagree on the predominant source of excitation to interneurons: either "direct," via the Schaffer collaterals that provide feedforward input from CA3 to CA1, or "indirect," via the local pyramidal cells in CA1, which are embedded in a recurrent excitatory-inhibitory network. Here, we used physiologically constrained computational models of basket-cell networks to investigate how they respond to different conditions of transient, noisy excitation. We found that direct excitation of interneurons could evoke ripples (140-220 Hz) that exhibited intraripple frequency accommodation and were frequency-insensitive to GABA modulators, as previously shown in in vitro experiments. In addition, the indirect excitation of the basket-cell network enabled the expression of intraripple frequency accommodation in the fast-gamma range (90-140 Hz), as in vivo In our model, intraripple frequency accommodation results from a hysteresis phenomenon in which the frequency responds differentially to the rising and descending phases of the transient excitation. Such a phenomenon predicts a maximum oscillation frequency occurring several milliseconds before the peak of excitation. We confirmed this prediction for ripples in brain slices from male mice. These results suggest that ripple and fast-gamma episodes are produced by the same interneuron network that is recruited via different excitatory input pathways, which could be supported by the previously reported intralaminar connectivity bias between basket cells and functionally distinct subpopulations of pyramidal cells in CA1. Together, our findings unify competing inhibition-first models of rhythm generation in the hippocampus.SIGNIFICANCE STATEMENT The hippocampus is a part of the brain of humans and other mammals that is critical for the acquisition and consolidation of memories. During deep sleep and resting periods, the hippocampus generates high-frequency (∼200 Hz) oscillations called ripples, which are important for memory consolidation. The mechanisms underlying ripple generation are not well understood. A prominent hypothesis holds that the ripples are generated by local recurrent networks of inhibitory neurons. Using computational models and experiments in brain slices from rodents, we show that the dynamics of interneuron networks clarify several previously unexplained characteristics of ripple oscillations, which advances our understanding of hippocampus-dependent memory consolidation.

Contribution of action potentials to the extracellular field potential in the nucleus laminaris of barn owl.

Extracellular field potentials (EFP) are widely used to evaluate in vivo neural activity, but identification of multiple sources and their relative contributions is often ambiguous, making the interpretation of the EFP difficult. We have therefore analyzed a model EFP from a simple brainstem circuit with separable pre- and postsynaptic components to determine whether we could isolate its sources. Our previous papers had shown that the barn owl neurophonic largely originates with spikes from input axons and synapses that terminate on the neurons in the nucleus laminaris (NL) (Kuokkanen PT, Wagner H, Ashida G, Carr CE, Kempter R. J Neurophysiol 104: 2274-2290, 2010; Kuokkanen PT, Ashida G, Carr CE, Wagner H, Kempter R. J Neurophysiol 110: 117-130, 2013; McColgan T, Liu J, Kuokkanen PT, Carr CE, Wagner H, Kempter R. eLife 6: e26106, 2017). To determine how much the postsynaptic NL neurons contributed to the neurophonic, we recorded EFP responses in NL in vivo. Power spectral analyses showed that a small spectral component of the evoked response, between 200 and 700 Hz, could be attributed to the NL neurons' spikes, while nucleus magnocellularis (NM) spikes dominate the EFP at frequencies ≳1 kHz. Thus, spikes of NL neurons and NM axons contribute to the EFP in NL in distinct frequency bands. We conclude that if the spectral components of source types are different and if their activities can be selectively modulated, the identification of EFP sources is possible. NEW & NOTEWORTHY Extracellular field potentials (EFPs) generate clinically important signals, but their sources are incompletely understood. As a model, we have analyzed the auditory neurophonic in the barn owl's nucleus laminaris. There the EFP originates predominantly from spiking in the afferent axons, with spectral power ≳1 kHz, while postsynaptic laminaris neurons contribute little. In conclusion, the identification of EFP sources is possible if they have different spectral components and if their activities can be modulated selectively.

Auditory brainstem response wave III is correlated with extracellular field potentials from nucleus laminaris of the barn owl.

The auditory brainstem response (ABR) is generated in the auditory brainstem by local current sources, which also give rise to extracellular field potentials (EFPs). The origins of both the ABR and the EFP are not well understood. We have recently found that EFPs, especially their dipole behavior, may be dominated by the branching patterns and the activity of axonal terminal zones [1]. To test the hypothesis that axons also shape the ABR, we used the well-described barn owl early auditory system. We recorded the ABR and a series of EFPs between the brain surface and nucleus laminaris (NL) in response to binaural clicks. The ABR and the EFP within and around NL are correlated. Together, our data suggest that axonal dipoles within the barn owl nucleus laminaris contribute to the ABR wave III.

A single-cell spiking model for the origin of grid-cell patterns.

Spatial cognition in mammals is thought to rely on the activity of grid cells in the entorhinal cortex, yet the fundamental principles underlying the origin of grid-cell firing are still debated. Grid-like patterns could emerge via Hebbian learning and neuronal adaptation, but current computational models remained too abstract to allow direct confrontation with experimental data. Here, we propose a single-cell spiking model that generates grid firing fields via spike-rate adaptation and spike-timing dependent plasticity. Through rigorous mathematical analysis applicable in the linear limit, we quantitatively predict the requirements for grid-pattern formation, and we establish a direct link to classical pattern-forming systems of the Turing type. Our study lays the groundwork for biophysically-realistic models of grid-cell activity.