Directional coupling of slow and fast hippocampal gamma with neocortical alpha/beta oscillations in human episodic memory.
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ABSTRACT:
SUBMITTER: Griffiths BJ
PROVIDER: S-EPMC6815125 | biostudies-literature | 2019 Oct
REPOSITORIES: biostudies-literature
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Project description:To form an episodic memory, we must first process a vast amount of sensory information about the to-be-encoded event and then bind these sensory representations together to form a coherent memory trace. While these two cognitive capabilities are thought to have two distinct neural origins, with neocortical alpha/beta oscillations supporting information representation and hippocampal theta-gamma phase-amplitude coupling supporting mnemonic binding, evidence for a dissociation between these two neural markers is conspicuously absent. To address this, seventeen human participants completed an associative memory task that first involved processing information about three sequentially-presented stimuli, and then binding these stimuli together into a coherent memory trace, all the while undergoing MEG recordings. We found that decreases in neocortical alpha/beta power during sequence perception, but not mnemonic binding, correlated with enhanced memory performance. Hippocampal theta/gamma phase-amplitude coupling, however, showed the opposite pattern; increases during mnemonic binding (but not sequence perception) correlated with enhanced memory performance. These results demonstrate that memory-related decreases in neocortical alpha/beta power and memory-related increases in hippocampal theta/gamma phase-amplitude coupling arise at distinct stages of the memory formation process. We speculate that this temporal dissociation reflects a functional dissociation in which neocortical alpha/beta oscillations could support the processing of incoming information relevant to the memory, while hippocampal theta-gamma phase-amplitude coupling could support the binding of this information into a coherent memory trace.
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Project description:BackgroundThe mammalian brain expresses a wide range of state-dependent network oscillations which vary in frequency and spatial extension. Such rhythms can entrain multiple neurons into coherent patterns of activity, consistent with a role in behaviour, cognition and memory formation. Recent evidence suggests that locally generated fast network oscillations can be systematically aligned to long-range slow oscillations. It is likely that such cross-frequency coupling supports specific tasks including behavioural choice and working memory.Principal findingsWe analyzed temporal coupling between high-frequency oscillations and EEG theta activity (4-12 Hz) in recordings from mouse parietal neocortex. Theta was exclusively present during active wakefulness and REM-sleep. Fast oscillations occurred in two separate frequency bands: gamma (40-100 Hz) and fast gamma (120-160 Hz). Theta, gamma and fast gamma were more prominent during active wakefulness as compared to REM-sleep. Coupling between theta and the two types of fast oscillations, however, was more pronounced during REM-sleep. This state-dependent cross-frequency coupling was particularly strong for theta-fast gamma interaction which increased 9-fold during REM as compared to active wakefulness. Theta-gamma coupling increased only by 1.5-fold.SignificanceState-dependent cross-frequency-coupling provides a new functional characteristic of REM-sleep and establishes a unique property of neocortical fast gamma oscillations. Interactions between defined patterns of slow and fast network oscillations may serve selective functions in sleep-dependent information processing.
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Project description:Although the hippocampus plays a crucial role in encoding and retrieval of contextually mediated episodic memories, considerable controversy surrounds the role of the hippocampus in short-term or working memory. To examine both hippocampal and neocortical contributions to working memory function, we recorded electrocorticographic activity from widespread cortical and subcortical sites as 20 neurosurgical patients performed working memory tasks. These recordings revealed significant increases in 48-90 Hz gamma oscillatory power with memory load for two classes of stimuli: letters and faces. Sites exhibiting gamma increases with memory load appeared primarily in the hippocampus and medial temporal lobe. These findings implicate gamma oscillatory activity in the maintenance of both letters and faces in working memory and provide the first direct evidence for modulation of hippocampal gamma oscillations as humans perform a working memory task.
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Project description:Hippocampal theta (5-10 Hz) and gamma (35-85 Hz) oscillations depend on an inhibitory network of GABAergic interneurons. However, the lack of methods for direct and cell-type-specific interference with inhibition has prevented better insights that help link synaptic and cellular properties with network function. Here, we generated genetically modified mice (PV-Deltagamma(2)) in which synaptic inhibition was ablated in parvalbumin-positive (PV+) interneurons. Hippocampal local field potential and unit recordings in the CA1 area of freely behaving mice revealed that theta rhythm was strongly reduced in these mice. The characteristic coupling of theta and gamma oscillations was strongly altered in PV-Deltagamma(2) mice more than could be accounted for by the reduction in theta rhythm only. Surprisingly, gamma oscillations were not altered. These data indicate that synaptic inhibition onto PV+ interneurons is indispensable for theta- and its coupling to gamma oscillations but not for rhythmic gamma-activity in the hippocampus. Similar alterations in rhythmic activity were obtained in a computational hippocampal network model mimicking the genetic modification, suggesting that intrahippocampal networks might contribute to these effects.
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Project description:Although it has been tacitly assumed that the hippocampus exerts an influence on neocortical networks, the mechanisms of this process are not well understood. We examined whether and how hippocampal theta oscillations affect neocortical assembly patterns by recording populations of single cells and transient gamma oscillations in multiple cortical regions, including the somatosensory area and prefrontal cortex in behaving rats and mice. Laminar analysis of neocortical gamma bursts revealed multiple gamma oscillators of varying frequency and location, which were spatially confined and synchronized local groups of neurons. A significant fraction of putative pyramidal cells and interneurons as well as localized gamma oscillations in all recorded neocortical areas were phase biased by the hippocampal theta rhythm. We hypothesize that temporal coordination of neocortical gamma oscillators by hippocampal theta is a mechanism by which information contained in spatially widespread neocortical assemblies can be synchronously transferred to the associative networks of the hippocampus.
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Project description:The replay of previously stored memories during hippocampal sharp wave ripples (SWRs) is thought to support both memory retrieval and consolidation in distributed hippocampal-neocortical circuits. Replay events consist of precisely timed sequences of spikes from CA3 and CA1 neurons that are coordinated both within and across hemispheres. The mechanism of this coordination is not understood. Here, we show that during SWRs in both awake and quiescent states there are transient increases in slow gamma (20-50 Hz) power and synchrony across dorsal CA3 and CA1 networks of both hemispheres. These gamma oscillations entrain CA3 and CA1 spiking. Moreover, during awake SWRs, higher levels of slow gamma synchrony are predictive of higher quality replay of past experiences. Our results indicate that CA3-CA1 gamma synchronization is a central component of awake memory replay and suggest that transient gamma synchronization serves as a clocking mechanism to enable coordinated memory reactivation across the hippocampal network.
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Project description:Experimental and theoretical studies demonstrate that neuronal gamma oscillations crucially depend on interneurons, but current models do not consider the diversity of known interneuron subtypes. Moreover, in CA1 of the hippocampus, experimental evidence indicates the presence of multiple gamma oscillators, two of which may be coordinated by differing interneuron populations. In this article, we show that models of networks with competing interneuron populations with different postsynaptic effects are sufficient to generate, within CA1, distinct oscillatory regimes. We find that strong mutual inhibition between the interneuron populations permits distinct fast and slow gamma states, whereas weak mutual inhibition generates mixed gamma states. We develop idealized firing rate models to illuminate dynamic properties of these competitive gamma networks, and reinforce these concepts with basic spiking models. The models make several explicit predictions about gamma oscillators in CA1. Specifically, interneurons of different subtype phase-lock to different gamma states, and one population of interneurons is silenced and the other active during fast and slow gamma events. Finally, mutual inhibition between interneuron populations is necessary to generate distinct gamma states. Previous experimental studies indicate that fast and slow gamma oscillations reflect different information processing modes, although it is unclear whether these rhythms are intrinsic or imposed. The models outlined demonstrate that basic architectures can locally generate these oscillations, as well as capture other features of fast and slow gamma, including theta-phase preference and spontaneous transitions between gamma states. These models may extend to describe general dynamics in networks with diverse interneuron populations.NEW & NOTEWORTHY The oscillatory coordination of neural signals is crucial to healthy brain function. We have developed an idealized neuronal model that generates distinct fast and slow gamma oscillations, a known feature of the rodent hippocampus. Our work provides a mechanism of this phenomenon, as well as a theoretical framework for future experiments concerning hippocampal gamma. It moreover offers a tractable model of competitive gamma oscillations that is generalizable across the nervous system.
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Project description:Networks of GABAergic interneurons are of critical importance for the generation of gamma frequency oscillations in the brain. To examine the underlying synaptic mechanisms, we made paired recordings from "basket cells" (BCs) in different subfields of hippocampal slices, using transgenic mice that express enhanced green fluorescent protein (EGFP) under the control of the parvalbumin promoter. Unitary inhibitory postsynaptic currents (IPSCs) showed large amplitude and fast time course with mean amplitude-weighted decay time constants of 2.5, 1.2, and 1.8 ms in the dentate gyrus, and the cornu ammonis area 3 (CA3) and 1 (CA1), respectively (33-34 degrees C). The decay of unitary IPSCs at BC-BC synapses was significantly faster than that at BC-principal cell synapses, indicating target cell-specific differences in IPSC kinetics. In addition, electrical coupling was found in a subset of BC-BC pairs. To examine whether an interneuron network with fast inhibitory synapses can act as a gamma frequency oscillator, we developed an interneuron network model based on experimentally determined properties. In comparison to previous interneuron network models, our model was able to generate oscillatory activity with higher coherence over a broad range of frequencies (20-110 Hz). In this model, high coherence and flexibility in frequency control emerge from the combination of synaptic properties, network structure, and electrical coupling.
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Project description:Apolipoprotein (apo) E4 is the major genetic risk factor for Alzheimer's disease (AD), but the mechanism by which it causes cognitive decline is unclear. In knockin (KI) mice, human apoE4 causes age-dependent learning and memory impairments and degeneration of GABAergic interneurons in the hippocampal dentate gyrus. Here we report two functional apoE4-KI phenotypes involving sharp-wave ripples (SWRs), hippocampal network events critical for memory processes. Aged apoE4-KI mice had fewer SWRs than apoE3-KI mice and significantly reduced slow gamma activity during SWRs. Elimination of apoE4 in GABAergic interneurons, which prevents learning and memory impairments, rescued SWR-associated slow gamma activity but not SWR abundance in aged mice. SWR abundance was reduced similarly in young and aged apoE4-KI mice; however, the full SWR-associated slow gamma deficit emerged only in aged apoE4-KI mice. These results suggest that progressive decline of interneuron-enabled slow gamma activity during SWRs critically contributes to apoE4-mediated learning and memory impairments. VIDEO ABSTRACT.
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Project description:Neocortical local field potentials have shown that gamma oscillations occur spontaneously during slow-wave sleep (SWS). At the macroscopic EEG level in the human brain, no evidences were reported so far. In this study, by using simultaneous scalp and intracranial EEG recordings in 20 epileptic subjects, we examined gamma oscillations in cerebral cortex during SWS. We report that gamma oscillations in low (30-50 Hz) and high (60-120 Hz) frequency bands recurrently emerged in all investigated regions and their amplitudes coincided with specific phases of the cortical slow wave. In most of the cases, multiple oscillatory bursts in different frequency bands from 30 to 120 Hz were correlated with positive peaks of scalp slow waves ("IN-phase" pattern), confirming previous animal findings. In addition, we report another gamma pattern that appears preferentially during the negative phase of the slow wave ("ANTI-phase" pattern). This new pattern presented dominant peaks in the high gamma range and was preferentially expressed in the temporal cortex. Finally, we found that the spatial coherence between cortical sites exhibiting gamma activities was local and fell off quickly when computed between distant sites. Overall, these results provide the first human evidences that gamma oscillations can be observed in macroscopic EEG recordings during sleep. They support the concept that these high-frequency activities might be associated with phasic increases of neural activity during slow oscillations. Such patterned activity in the sleeping brain could play a role in off-line processing of cortical networks.
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