Ripple Events Research Articles

Bimodal coupling of ripples and slower oscillations during sleep in patients with focal epilepsy.

Differentiating pathologic and physiologic high-frequency oscillations (HFOs) is challenging. In patients with focal epilepsy, HFOs occur during the transitional periods between the up and down state of slow waves. The preferred phase angles of this form of phase-event amplitude coupling are bimodally distributed, and the ripples (80-150Hz) that occur during the up-down transition more often occur in the seizure-onset zone (SOZ). We investigated if bimodal ripple coupling was also evident for faster sleep oscillations, and could identify the SOZ. Using an automated ripple detector, we identified ripple events in 40-60min intracranial electroencephalography (iEEG) recordings from 23 patients with medically refractory mesial temporal lobe or neocortical epilepsy. The detector quantified epochs of sleep oscillations and computed instantaneous phase. We utilized a ripple phasor transform, ripple-triggered averaging, and circular statistics to investigate phase event-amplitude coupling. We found that at some individual recording sites, ripple event amplitude was coupled with the sleep oscillatory phase and the preferred phase angles exhibited two distinct clusters (p<0.05). The distribution of the pooled mean preferred phase angle, defined by combining the means from each cluster at each individual recording site, also exhibited two distinct clusters (p<0.05). Based on the range of preferred phase angles defined by these two clusters, we partitioned each ripple event at each recording site into two groups: depth iEEG peak-trough and trough-peak. The mean ripple rates of the two groups in the SOZ and non-SOZ (NSOZ) were compared. We found that in the frontal (spindle, p=0.009; theta, p=0.006, slow, p=0.004) and parietal lobe (theta, p=0.007, delta, p=0.002, slow, p=0.001) the SOZ incidence rate for the ripples occurring during the trough-peak transition was significantly increased. Phase-event amplitude coupling between ripples and sleep oscillations may be useful to distinguish pathologic and physiologic events in patients with frontal and parietal SOZ.

Disruption of perineuronal nets increases the frequency of sharp wave ripple events.

Hippocampal sharp wave ripples (SWRs) represent irregularly occurring synchronous neuronal population events that are observed during phases of rest and slow wave sleep. SWR activity that follows learning involves sequential replay of training-associated neuronal assemblies and is critical for systems level memory consolidation. SWRs are initiated by CA2 or CA3 pyramidal cells (PCs) and require initial excitation of CA1 PCs as well as participation of parvalbumin (PV) expressing fast spiking (FS) inhibitory interneurons. These interneurons are relatively unique in that they represent the major neuronal cell type known to be surrounded by perineuronal nets (PNNs), lattice like structures composed of a hyaluronin backbone that surround the cell soma and proximal dendrites. Though the function of the PNN is not completely understood, previous studies suggest it may serve to localize glutamatergic input to synaptic contacts and thus influence the activity of ensheathed cells. Noting that FS PV interneurons impact the activity of PCs thought to initiate SWRs, and that their activity is critical to ripple expression, we examine the effects of PNN integrity on SWR activity in the hippocampus. Extracellular recordings from the stratum radiatum of horizontal murine hippocampal hemisections demonstrate SWRs that occur spontaneously in CA1. As compared with vehicle, pre-treatment (120 min) of paired hemislices with hyaluronidase, which cleaves the hyaluronin backbone of the PNN, decreases PNN integrity and increases SWR frequency. Pre-treatment with chondroitinase, which cleaves PNN side chains, also increases SWR frequency. Together, these data contribute to an emerging appreciation of extracellular matrix as a regulator of neuronal plasticity and suggest that one function of mature perineuronal nets could be to modulate the frequency of SWR events.

Direct Medial Entorhinal Cortex Input to Hippocampal CA1 Is Crucial for Extended Quiet Awake Replay

Hippocampal replays have been demonstrated to play a crucial role in memory. Chains of ripples (ripple bursts) in CA1 have been reported to co-occur with long-range place cell sequence replays during the quiet awake state, but roles of neural inputs to CA1 in ripple bursts and replays are unknown. Here we show that ripple bursts in CA1 and medial entorhinal cortex (MEC) are temporally associated. An inhibition of MECIII input to CA1 during quiet awake reduced ripple bursts in CA1 and restricted the spatial coverage of replays to a shorter distance corresponding to single ripple events. The reduction did not occur with MECIII input inhibition during slow-wave sleep. Inhibition of CA3 activity suppressed ripples and replays in CA1 regardless of behavioral state. Thus, MECIII input to CA1 is crucial for ripple bursts and long-range replays specifically in quiet awake, whereas CA3 input is essential for both, regardless of behavioral state.

Physiological Ripples Associated with Sleep Spindles Differ in Waveform Morphology from Epileptic Ripples.

High frequency oscillations (HFOs, 80-500[Formula: see text]Hz) serve as novel electroencephalography (EEG) markers of epileptic tissue. The differentiation of physiological and epileptic HFO is an important challenge and is complicated by the fact that both types are generated in mesiotemporal structures. This study aimed to identify oscillation features that serve to distinguish physiological ripples associated with sleep spindles and epileptic ripples. We studied 19 patients with chronic intracranial EEG(iEEG) with mesiotemporal implantation and simultaneous scalp EEG. Sleep spindles, ripples and spikes were visually marked during nonrapid eye movement sleep stage 2. Ripples co-occurring with spikes and in seizure onset zone (SOZ) channels but outside of spindles were considered epileptic. The SOZ is defined by the origin of clinical seizures in iEEG. Ripples co-occurring with spindles were considered as models for physiological ripples. A correlation analysis showed a significant ripple amplitude peak - spindle trough - coupling, thus proving their physiological linkage. Epileptic ripples showed significantly higher values in all amplitude features than spindle ripples. All amplitude features and peaks per sample length showed a predictive value for the classification between model physiological ripples and epileptic ripples but indicate that the specificity is not sufficient for a reliable discrimination of single ripple events. The presented results suggest that a secure identification of epileptic ripples may be available to help identify the epileptic focus in the future.

Rearing-environment-dependent hippocampal local field potential differences in wild-type and inositol trisphosphate receptor type 2 knockout mice.

Mice reared in an enriched environment are demonstrated to have larger hippocampal gamma oscillations than those reared in isolation, thereby confirming previous observations in rats. To test whether astrocytic Ca2+ surges are involved in this experience-dependent LFP pattern modulation, we used inositol trisphosphate receptor type 2 (IP3 R2)-knockout (KO) mice, in which IP3 /Ca2+ signalling in astrocytes is largely diminished. We found that this experience-dependent gamma power alteration persists in the KO mice. Interestingly, hippocampal ripple events, the synchronized events critical for memory consolidation, are reduced in magnitude and frequency by both isolated rearing and IP3 R2 deficiency. Rearing in an enriched environment (ENR) is known to enhance cognitive and memory abilities in rodents, whereas social isolation (ISO) induces depression-like behaviour. The hippocampus has been documented to undergo morphological and functional changes depending on these rearing environments. For example, rearing condition during juvenility alters CA1 stratum radiatum gamma oscillation power in rats. In the present study, hippocampal CA1 local field potentials (LFP) were recorded from bilateral CA1 in urethane-anaesthetized mice that were reared in either an ENR or ISO condition. Similar to previous findings in rats, gamma oscillation power during theta states was higher in the ENR group. Ripple events that occur during non-theta periods in the CA1 stratum pyramidale also had longer intervals in ISO mice. Because astrocytic Ca2+ elevations play a key role in synaptic plasticity, we next tested whether these changes in LFP are also expressed in inositol trisphosphate receptor type 2 (IP3 R2)-knockout (KO) mice, in which astrocytic Ca2+ elevations are largely diminished. We found that the gamma power was also higher in IP3 R2-KO-ENR mice compared to IP3 R2-KO-ISO mice, suggesting that the rearing-environment-dependent gamma power alteration does not necessarily require the astrocytic IP3 /Ca2+ pathway. By contrast, ripple events showed genotype-dependent changes, as well as rearing condition-dependent changes: ISO housing and IP3 R2 deficiency both lead to longer inter-ripple intervals. Moreover, we found that ripple magnitude in the right CA1 tended to be smaller in IP3 R2-KO. Because IP3 R2-KO mice have been reported to have depression phenotypes, our results suggest that ripple events and the mood of animals may be broadly correlated.

Mechanisms for maintaining mental maps

Neuroscience When an animal runs around, some hippocampal neurons are selectively active in specific locations called their place fields. A maplike representation created from many such place fields serves as a navigation mechanism. How such hippocampal maps stabilize is still unknown. Roux et al. investigated a discrete form of high-frequency neuronal oscillations called sharp wave ripples. In a spatial learning task, they focally silenced a subpopulation of hippocampal area CA1 neurons during sharp wave ripple events. The place fields of the silenced neurons were altered, and their spatial information content failed to increase. Control place cells, however, largely kept their spatial correlates and showed increased information after learning. Sharp wave ripple–associated neuronal firing is necessary for stabilizing and refining hippocampal place fields. Nat. Neurosci. 20 , 845 (2017).

The glutamate receptor antagonists CNQX and MPEP decrease fast ripple events in rats treated with kainic acid.

Fast ripples (FR) are high frequency oscillations (250-600Hz) that have been associated with epilepsy. FR are assumed to be generated in small areas of the hippocampus (1mm3) that contain pathologically interconnected glutamate pyramidal cell clusters. Additionally, a relation between glutamate neurotransmission and α-amino-3-hydroxy-5-methyl-4-isoxazolepropionic acid/kainite (AMPA/KA) and metabotropic mGluR5 receptors is well established. Therefore, we hypothesized that antagonism of these glutamate receptors would decrease FR activity. For this propose, we induced status epilepticus with a kainic acid injection in the posterior right hippocampus and performed intracranial EEG recordings to detect and evaluate the presence of FR 15days after the injection. The glutamate AMPA/KA receptor antagonist CNQX (10mg/kg) and the mGluR5 antagonist MPEP (20mg/kg) were administered intraperitoneally, and the effects of the drugs were evaluated for a period of three hours after their administration. The results show a decrease in the number of FR in the first hour after drug administration in both cases (CNQX, p=0.0125; MPEP, p=0.0132) and a return to basal values in the third hour of the experiment, but not significant differences in the number of oscillations per event of FR, and the frequency and duration of each event of FR. We therefore conclude that blockade of AMPA/KA and mGluR5 receptors transiently decreases the generation of FR; however, the mechanisms by which this effect is achieved are to be further analyzed in future experiments.

Asynchronous ripple oscillations between left and right hippocampi during slow-wave sleep.

Spatial memory, among many other brain processes, shows hemispheric lateralization. Most of the published evidence suggests that the right hippocampus plays a leading role in the manipulation of spatial information. Concurrently in the hippocampus, memory consolidation during sleep periods is one of the key steps in the formation of newly acquired spatial memory traces. One of the most characteristic oscillatory patterns in the hippocampus are sharp-wave ripple (SWR) complexes. Within this complex, fast-field oscillations or ripples have been demonstrated to be instrumental in the memory consolidation process. Since these ripples are relevant for the consolidation of memory traces associated with spatial navigation, and this process appears to be lateralized, we hypothesize that ripple events between both hippocampi would exhibit different temporal dynamics. We tested this idea by using a modified "split-hyperdrive" that allows us to record simultaneous LFPs from both right and left hippocampi of Sprague-Dawley rats during sleep. We detected individual events and found that during sleep periods these ripples exhibited a different occurrence patterns between hemispheres. Most ripple events were synchronous between intra- rather than inter-hemispherical recordings, suggesting that ripples in the hippocampus are independently generated and locally propagated within a specific hemisphere. In this study, we propose the ripples’ lack of synchrony between left and right hippocampi as the putative physiological mechanism underlying lateralization of spatial memory.

A semi-automated method for rapid detection of ripple events on interictal voltage discharges in the scalp electroencephalogram

BackgroundHigh frequency oscillations are emerging as a clinically important indicator of epileptic networks. However, manual detection of these high frequency oscillations is difficult, time consuming, and subjective, especially in the scalp EEG, thus hindering further clinical exploration and application. Semi-automated detection methods augment manual detection by reducing inspection to a subset of time intervals. We propose a new method to detect high frequency oscillations that co-occur with interictal epileptiform discharges. New methodThe new method proceeds in two steps. The first step identifies candidate time intervals during which high frequency activity is increased. The second step computes a set of seven features for each candidate interval. These features require that the candidate event contain a high frequency oscillation approximately sinusoidal in shape, with at least three cycles, that co-occurs with a large amplitude discharge. Candidate events that satisfy these features are stored for validation through visual analysis. ResultsWe evaluate the detector performance in simulation and on ten examples of scalp EEG data, and show that the proposed method successfully detects spike-ripple events, with high positive predictive value, low false positive rate, and high intra-rater reliability. Comparison with existing methodThe proposed method is less sensitive than the existing method of visual inspection, but much faster and much more reliable. ConclusionsAccurate and rapid detection of high frequency activity increases the clinical viability of this rhythmic biomarker of epilepsy. The proposed spike-ripple detector rapidly identifies candidate spike-ripple events, thus making clinical analysis of prolonged, multielectrode scalp EEG recordings tractable.

A cortical-hippocampal-cortical loop of information processing during memory consolidation.

Hippocampal replay during sharp-wave ripple events (SWRs) is thought to drive memory consolidation in hippocampal and cortical circuits. Changes in neocortical activity can precede SWR events, but whether and how these changes influence the content of replay remains unknown. Here we show that during sleep there is a rapid cortical-hippocampal-cortical loop of information flow around the times of SWRs. We recorded neural activity in auditory cortex (AC) and hippocampus of rats as they learned a sound-guided task and during sleep. We found that patterned activation in AC precedes and predicts the subsequent content of hippocampal activity during SWRs, while hippocampal patterns during SWRs predict subsequent AC activity. Delivering sounds during sleep biased AC activity patterns, and sound-biased AC patterns predicted subsequent hippocampal activity. These findings suggest that activation of specific cortical representations during sleep influences the identity of the memories that are consolidated into long-term stores.

The relationship of medial temporal lobe epilepsy with the declarative memory system

SummaryIntroduction.Medial temporal lobe of epilepsy (MTLE) is considered as local/regional epilepsy. However, as was discussed in Part I of this review (Halász, 2016a) there is more evidence regarding the involvement of both temporal lobes so as to consider MTLE as one of the typical bilateral system epilepsies.Aim.To provide contemporary review of MTLE in relation to the declarative memory system and the newly recognized hippocampo-frontal memory consolidation during slow wave sleep.Methods.A review of the available literature on experimental and clinical data and also the authors own studies in MTLE patients.Review, discussion and results.New experimental and clinical neurophysiological data have shown that MTLE is closely linked to the hippocampal memory system. It is likely that hippocampal spiking is the epileptic variations of the normal sharp wave ripple events mediating the encoding and consolidation of memory engrams by a hippocampo-frontal dialogue during slow wave sleep.Conclusions.The source of memory impairment in MTLE patients is not merely the cell loss and synaptic transformation of the hippocampal structure, but the every night interference with memory consolidation due to interictal spiking.

Optogenetically Blocking Sharp Wave Ripple Events in Sleep Does Not Interfere with the Formation of Stable Spatial Representation in the CA1 Area of the Hippocampus.

During hippocampal sharp wave/ripple (SWR) events, previously occurring, sensory input-driven neuronal firing patterns are replayed. Such replay is thought to be important for plasticity-related processes and consolidation of memory traces. It has previously been shown that the electrical stimulation-induced disruption of SWR events interferes with learning in rodents in different experimental paradigms. On the other hand, the cognitive map theory posits that the plastic changes of the firing of hippocampal place cells constitute the electrophysiological counterpart of the spatial learning, observable at the behavioral level. Therefore, we tested whether intact SWR events occurring during the sleep/rest session after the first exploration of a novel environment are needed for the stabilization of the CA1 code, which process requires plasticity. We found that the newly-formed representation in the CA1 has the same level of stability with optogenetic SWR blockade as with a control manipulation that delivered the same amount of light into the brain. Therefore our results suggest that at least in the case of passive exploratory behavior, SWR-related plasticity is dispensable for the stability of CA1 ensembles.

Ripples on spikes show increased phase-amplitude coupling in mesial temporal lobe epilepsy seizure-onset zones.

Ripples (80-150 Hz) recorded from clinical macroelectrodes have been shown to be an accurate biomarker of epileptogenic brain tissue. We investigated coupling between epileptiform spike phase and ripple amplitude to better understand the mechanisms that generate this type of pathologic ripple (pRipple) event. We quantified phase amplitude coupling (PAC) between epileptiform electroencephalography (EEG) spike phase and ripple amplitude recorded from intracranial depth macroelectrodes during episodes of sleep in 12 patients with mesial temporal lobe epilepsy. PAC was determined by (1) a phasor transform that corresponds to the strength and rate of ripples coupled with spikes, and a (2) ripple-triggered average to measure the strength, morphology, and spectral frequency of the modulating and modulated signals. Coupling strength was evaluated in relation to recording sites within and outside the seizure-onset zone (SOZ). Both the phasor transform and ripple-triggered averaging methods showed that ripple amplitude was often robustly coupled with epileptiform EEG spike phase. Coupling was found more regularly inside than outside the SOZ, and coupling strength correlated with the likelihood a macroelectrode's location was within the SOZ (p < 0.01). The ratio of the rate of ripples coupled with EEG spikes inside the SOZ to rates of coupled ripples in non-SOZ was greater than the ratio of rates of ripples on spikes detected irrespective of coupling (p < 0.05). Coupling strength correlated with an increase in mean normalized ripple amplitude (p < 0.01), and a decrease in mean ripple spectral frequency (p < 0.05). Generation of low-frequency (80-150 Hz) pRipples in the SOZ involves coupling between epileptiform spike phase and ripple amplitude. The changes in excitability reflected as epileptiform spikes may also cause clusters of pathologically interconnected bursting neurons to grow and synchronize into aberrantly large neuronal assemblies.

Differentiating epileptic from non-epileptic high frequency intracerebral EEG signals with measures of wavelet entropy.

To assess whether there is a difference in the background activity in the ripple band (80-200Hz) between epileptic and non-epileptic channels, and to assess whether this difference is sufficient for their reliable separation. We calculated mean and standard deviation of wavelet entropy in 303 non-epileptic and 334 epileptic channels from 50 patients with intracerebral depth electrodes and used these measures as predictors in a multivariable logistic regression model. We assessed sensitivity, positive predictive value (PPV) and negative predictive value (NPV) based on a probability threshold corresponding to 90% specificity. The probability of a channel being epileptic increased with higher mean (p=0.004) and particularly with higher standard deviation (p<0.0001). The performance of the model was however not sufficient for fully classifying the channels. With a threshold corresponding to 90% specificity, sensitivity was 37%, PPV was 80%, and NPV was 56%. A channel with a high standard deviation of entropy is likely to be epileptic; with a threshold corresponding to 90% specificity our model can reliably select a subset of epileptic channels. Most studies have concentrated on brief ripple events. We showed that background activity in the ripple band also has some ability to discriminate epileptic channels.

Neuronal assembly dynamics in the brain

Brain Microcircuits Sharp-wave ripples are a form of neuronal activity pattern observed in the hippocampus that may play a role in memory consolidation. To investigate this phenomenon, Malvache et al. simultaneously imaged calcium dynamics in multiple hippocampal neurons of live mice. A category of neurons called place cells became active when mice ran on a treadmill. When the mice paused, fast replay events occurred that recalled the sequence of cell activations while the mice were running, and these coincided with the sharp-wave ripples. Reactivation periods in which different assemblies of cells took part were also observed. Imaging of the mice indicated that patches of neurons might cooperate to produce fragments of the ripple events. Science , this issue p. [1280][1] [1]: /lookup/doi/10.1126/science.aaf3319

Rapid classification of hippocampal replay content for real-time applications

Sharp-wave ripple (SWR) events in the hippocampus replay millisecond-timescale patterns of place cell activity related to the past experience of an animal. Interrupting SWR events leads to learning and memory impairments, but how the specific patterns of place cell spiking seen during SWRs contribute to learning and memory remains unclear. A deeper understanding of this issue will require the ability to manipulate SWR events based on their content. Accurate real-time decoding of SWR replay events requires new algorithms that are able to estimate replay content and the associated uncertainty, along with software and hardware that can execute these algorithms for biological interventions on a millisecond timescale. Here we develop an efficient estimation algorithm to categorize the content of replay from multiunit spiking activity. Specifically, we apply real-time decoding methods to each SWR event and then compute the posterior probability of the replay feature. We illustrate this approach by classifying SWR events from data recorded in the hippocampus of a rat performing a spatial memory task into four categories: whether they represent outbound or inbound trajectories and whether the activity is replayed forward or backward in time. We show that our algorithm can classify the majority of SWR events in a recording epoch within 20 ms of the replay onset with high certainty, which makes the algorithm suitable for a real-time implementation with short latencies to incorporate into content-based feedback experiments.

Age Is Associated with Reduced Sharp-Wave Ripple Frequency and Altered Patterns of Neuronal Variability.

Spatial and episodic memory performance declines with age, and the neural basis for this decline is not well understood. Sharp-wave ripples are brief (∼70 ms) high-frequency oscillatory events generated in the hippocampus and are associated with the consolidation of spatial memories. Given the connection between ripple oscillations and memory consolidation, we investigated whether the structure of ripple oscillations and ripple-triggered patterns of single-unit activity are altered in aged rats. Local field and single-unit activity surrounding sharp-wave ripple events were examined in the CA1 region of the hippocampus of old (n = 5) and young (n = 6) F344 rats during periods of rest preceding and following performance on a place-dependent eyeblink-conditioning task. Neural responses in aged rats differed from responses in young rats in several ways. First, compared with young rats, the rate of ripple occurrence (ripple density) is reduced in aged rats during postbehavior rest. Second, mean ripple frequency during prebehavior and postbehavior rest is lower in aged animals (aged: 132 Hz; young: 146 Hz). Third, single neurons in aged animals responded more consistently from ripple to ripple. Fourth, variability in interspike intervals was greater in aged rats. Finally, neurons were tuned to a narrower range of phases of the ripple oscillation relative to young animals. Together, these results suggest that the CA1 network in aged animals has a reduced "vocabulary" of available representational states. The hippocampus is a structure that is critical for the formation of episodic memories. Sharp-wave ripple events generated in the hippocampus have been implicated in memory consolidation processes critical to memory stabilization. We examine here whether these ripple oscillations are altered over the course of the life span, which could contribute to hippocampus-dependent memory deficits that occur during aging. This experiment used young and aged memory-impaired rats to examine age-related changes in ripple architecture, ripple-triggered spike variance, and spike-phase coherence. We found that there are, indeed, significant changes in characteristics of ripples in older animals that could impact consolidation processes and memory stabilization in the aged brain.

Coordinated Excitation and Inhibition of Prefrontal Ensembles during Awake Hippocampal Sharp-Wave Ripple Events

Interactions between the hippocampus and prefrontal cortex (PFC) are critical for learning and memory. Hippocampal activity during awake sharp-wave ripple (SWR) events is important for spatial learning, and hippocampal SWR activity often represents past or potential future experiences. Whether or how this reactivation engages the PFC, and how reactivation might interact with ongoing patterns of PFC activity, remains unclear. We recorded hippocampal CA1 and PFC activity in animals learning spatial tasks and found that many PFC cells showed spiking modulation during SWRs. Unlike in CA1, SWR-related activity in PFC comprised both excitation and inhibition of distinct populations. Within individual SWRs, excitation activated PFC cells with representations related to the concurrently reactivated hippocampal representation, while inhibition suppressed PFC cells with unrelated representations. Thus, awake SWRs mark times of strong coordination between hippocampus and PFC that reflects structured reactivation of representations related to ongoing experience.

Mechanisms of hippocampal sequence replay

Sleep is known to be important for memory consolidation [1], and memories are thought to be stored in the hippocampus during wakefulness and transferred to cortex during sleep [2]. Recently, memory replay - repeatable sequences of pyramidal cell firing - has been demonstrated during sleep, and associated with characteristic brain oscillations, giving rise to the hypothesis that these may form the critical neural substrate of memory consolidation. It is known that the content of hippocampal replay can be biased during sleep, in what is called cued-reactivation [3], and that similar paradigms show enhanced memory performance in humans [4]. Moreover, tampering with replay can disrupt memory formation and consolidation [5]. Despite extensive evidence highlighting the importance of replay within the broader phenomenon of sleep-mediated memory consolidation, the mechanisms underlying sequence replay are still unknown. During sleep, replay events are associated with specific patterns of neuronal oscillations [6]. Replay is seen in cortex during slow oscillation - a rhythmic ( 150 Hz) firing, driven by strong excitatory inputs coming from CA3, which result in a strong deflection in the LFP of stratum radiatum (the sharp wave) [7]. In the present study, we build on our previous research [8] to develop a model of spike sequence replay during sleep. In the past, we have introduced a model of CA1 ripples in which oscillations are transients, mediated by the intrinsic frequency of CA1 basket cells driven by CA3 activation. In this work, we construct a model of CA3 area in which stochastic intrinsic activation of pyramidal cells originates a massive cell activation that results in a strong excitatory input to area CA1. We observe that sequential activation of a selected sub-group of CA1 pyramidal cells is driven by a less specific sequential activation in CA3. We then characterize the mechanisms underlying sequence selection and reactivation within a sharp-wave ripple event. Using hippocampal and thalamocortical models, we investigate the role of cortical inputs on ripple timing and their specific spike content. Our study illustrates the possible role of cortical Up states during slow oscillation in biasing hippocampal replay, which is a core component of the cortico-hippocampal interaction underlying memory consolidation.

Disordered Ripples Are a Common Feature of Genetically Distinct Mouse Models Relevant to Schizophrenia

We present results from a novel comparative approach to the study of the mechanisms of psychiatric disease. Previous work has examined neural activity patterns in the hippocampus of a freely behaving mouse model associated with schizophrenia, the calcineurin knockout mouse. Here, we examined a genetically distinct mouse model that exhibits a similar set of behavioral phenotypes associated with schizophrenia, a transgenic model expressing a putative dominant-negative DISC1 (DN-DISC1). Strikingly, the principal finding of the earlier work is replicated in the DN-DISC1 mice, that is, a selective increase in the numbers of sharp-wave ripple (SWR) events in the hippocampal local field potential (LFP), while at the same time other LFP patterns such as theta and gamma are unaffected. SWRs are thought to arise from hippocampal circuits and reflect the coordinated activity of the principal excitatory cells of the hippocampus in specific patterns that represent reactivated memories of previous experiences and imagined future experiences that predict behavior. These findings suggest that multiple genetic alterations could converge on distinct patterns of aberrant neurophysiological function to give rise to common behavioral phenotypes in psychiatric disease.