Spontaneous persistent activity in entorhinal cortex modulates cortico-hippocampal interaction in vivo

Hahn, Thomas T. G.; McFarland, James M.; Berberich, Sven; Sakmann, Bert; Mehta, Mayank R.

doi:10.1038/nn.3236

Cited by 127 publications

(147 citation statements)

References 55 publications

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“…Thus, whereas information may be conveyed quickly through high-frequency signals, slower propagation of low-frequency activity may act to coordinate signaling by creating a routing structure for higher frequency activity which delineates distinct 'packets' of information. For example, sharp wave ripples (SPW-Rs) rapidly convey high frequency (greater than 100 Hz) signals from the hippocampus to cortex [68], but the onset of SPW-Rs is modulated by slower (1-4 Hz) signals propagating from cortex to hippocampus [69,70]. Similarly, we speculate directed propagation of spontaneous infra-slow activity as reflected in the BOLD signal (e.g.…”

Section: Biological Mechanismmentioning

confidence: 78%

How networks communicate: propagation patterns in spontaneous brain activity

Mitra

Raichle

2016

Phil. Trans. R. Soc. B

114

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One contribution of 15 to a Theo Murphy meeting issue 'Interpreting BOLD: a dialogue between cognitive and cellular neuroscience'. Initially regarded as 'noise', spontaneous (intrinsic) activity accounts for a large portion of the brain's metabolic cost. Moreover, it is now widely known that infra-slow (less than 0.1 Hz) spontaneous activity, measured using resting state functional magnetic resonance imaging of the blood oxygen level-dependent (BOLD) signal, is correlated within functionally defined resting state networks (RSNs). However, despite these advances, the temporal organization of spontaneous BOLD fluctuations has remained elusive. By studying temporal lags in the resting state BOLD signal, we have recently shown that spontaneous BOLD fluctuations consist of remarkably reproducible patterns of whole brain propagation. Embedded in these propagation patterns are unidirectional 'motifs' which, in turn, give rise to RSNs. Additionally, propagation patterns are markedly altered as a function of state, whether physiological or pathological. Understanding such propagation patterns will likely yield deeper insights into the role of spontaneous activity in brain function in health and disease.This article is part of the themed issue 'Interpreting blood oxygen level-dependent: a dialogue between cognitive and cellular neuroscience'. Importance of intrinsic activityAs observed by Hans Berger, in reporting on the first measurements of the human electroencephalogram, spontaneous (intrinsic) neural fluctuations are a dominant feature of the brain's electrical activity [1]. In the context of studying task-evoked neural responses, spontaneous activity was long considered merely to be 'noise'. Thus, most early studies of neural activity employed computational strategies to suppress spontaneous activity. More recently, it has been appreciated that investigating spontaneous activity is essential for understanding brain function [2][3][4]. At the systems level, this paradigm shift was prompted by two major findings. First, although the human brain represents only 2% of total body mass, its intrinsic activity consumes 20% of the body's energy, most of which is used to support ongoing neuronal signalling ([5-9], but see also [10]). Task-related increases in neuronal metabolism are generally small (less than 5%) when compared with this large intrinsic energy consumption (for a recent review, see [9]). Thus, to understand how the brain operates, we must take into account the component that consumes most of the brain's energy: spontaneous activity.The second set of findings has been derived from resting state functional magnetic resonance imaging (rs-fMRI) of the blood oxygen level-dependent (BOLD) signal [11]. Biswal et al. used human rs-fMRI to discover that spontaneous infraslow (less than 0.1 Hz) fluctuations of the BOLD signal are highly correlated within the somatomotor system [12]. This basic result has since been extended to multiple functional networks spanning the entire brain ([13-17]; figure 1a,b). Spatial correlat...

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Section: Biological Mechanismmentioning

confidence: 78%

How networks communicate: propagation patterns in spontaneous brain activity

Mitra

Raichle

2016

Phil. Trans. R. Soc. B

114

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“…The recurrent CA3 network could generate motif-like activity, which might cause the observed ~2-s delayed responses of the hippocampal ensemble activity pattern to sudden changes in visual cues 24 . Alternatively, the motifs could arise in the medial entorhinal cortex, where neurons show motif-like activity lasting several seconds and robustly driving the CA1, even in anesthetized or sleeping animals 43 . Accordingly, sustained spiking in consecutive theta cycles was reduced, indicative of diminished motifs, in a GluA1 transgenic mouse with diminished distal dendritic inputs, which typically originate in the entorhinal cortex 44 .…”

Section: Discussionmentioning

confidence: 99%

“…Hence, to understand the mechanisms of the hippocampal spatial rate and temporal codes, it is important to determine whether the two can be dissociated during spatial exploration. In addition, dorsal hippocampal neurons are typically active for sustained periods lasting more than 1 second 1,2 , even under a variety of conditions [22][23][24][25] , and this sustained nature of activity has received little attention.…”

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confidence: 99%

Impaired spatial selectivity and intact phase precession in two-dimensional virtual reality

et al. 2014

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During real-world (RW) exploration, rodent hippocampal activity shows robust spatial selectivity, which is hypothesized to be governed largely by distal visual cues, although other sensory-motor cues also contribute. Indeed, hippocampal spatial selectivity is weak in primate and human studies that use only visual cues. To determine the contribution of distal visual cues only, we measured hippocampal activity from body-fixed rodents exploring a two-dimensional virtual reality (VR). Compared to that in RW, spatial selectivity was markedly reduced during random foraging and goal-directed tasks in VR. Instead we found small but significant selectivity to distance traveled. Despite impaired spatial selectivity in VR, most spikes occurred within ~2-s-long hippocampal motifs in both RW and VR that had similar structure, including phase precession within motif fields. Selectivity to space and distance traveled were greatly enhanced in VR tasks with stereotypical trajectories. Thus, distal visual cues alone are insufficient to generate a robust hippocampal rate code for space but are sufficient for a temporal code. npg © 2015 Nature America, Inc. All rights reserved.1 2 2 VOLUME 18 | NUMBER 1 | JANUARY 2015 nature neurOSCIenCe a r t I C l e S same physical location in space can be approached from multiple different directions at different speeds. We thus investigated the contribution of distal visual cues only in determining selectivity in such an experimental setup. RESULTS Nature of spatial selectivity of hippocampal responsesWe measured hippocampal activity during a two-dimensional randomforaging task in RW and VR [35][36][37] with similar distal visual cues (Fig. 1a). In VR, the rats were body-fixed, i.e., their bodies were held in place, with a harness on a floating ball, allowing for head movements but precluding full-body turns, thus minimizing vestibular cues (Online Methods) 21,36 . Rats quickly learned to avoid the virtual edges entirely on the basis of visual cues 36 and spent a similar amount of time away from the edges and in the center of the platform (Fig. 1a) compared to in RW. We measured the activity of 1,066 and 1,238 principal neurons in RW and VR, respectively, in the dorsal CA1 of four rats under a variety of conditions (Online Methods). Neurons fired vigorously in restricted regions of space in RW, as expected (Fig. 1b,c, Supplementary Fig. 1a and Supplementary Video 1) 1 . In contrast, the neurons showed little spatial selectivity in VR during random foraging (Fig. 1b,d and Supplementary Fig. 1b).Across the ensemble, neurons had moderately reduced (25%) mean firing rates but greatly reduced (68%) peak firing rates in VR ( Fig. 2a and Supplementary Fig. 2a). Neurons in VR also had greatly reduced spatial information content (75%), stability (59%), sparsity (42%) and coherence (40%) (Fig. 2b-d and Supplementary Fig. 2b,c) compared to spatially localized, stable and sparse RW rate maps (Fig. 2c). Although the mean firing rate was inversely correlated with information content (Supplementary Fig. 2d)...

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“…Instead, the theory proposes that high-frequency activity carries information from the sender to receiver, that is, from the cortex to hippocampus or the hippocampus to cortex, depending on the stage of memory consolidation (wake or SWS, respectively) (4). Conversely, low-frequency activity propagates from the receiver back to the sender to coordinate the transfer of high-frequency information through modulation of the sender's excitability (4,(7)(8)(9). Hence, the two-stage reciprocal dialogue model predicts that lower and higher frequency activity between the hippocampus and cortex should propagate in opposite directions across wake and SWS, as illustrated in the schematic in Fig.…”

mentioning

confidence: 99%

Human cortical–hippocampal dialogue in wake and slow-wave sleep

Mitra

Snyder

Hacker

et al. 2016

Proc. Natl. Acad. Sci. U.S.A.

110

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Declarative memory consolidation is hypothesized to require a twostage, reciprocal cortical-hippocampal dialogue. According to this model, higher frequency signals convey information from the cortex to hippocampus during wakefulness, but in the reverse direction during slow-wave sleep (SWS). Conversely, lower-frequency activity propagates from the information "receiver" to the "sender" to coordinate the timing of information transfer. Reversal of sender/ receiver roles across wake and SWS implies that higher-and lower-frequency signaling should reverse direction between the cortex and hippocampus. However, direct evidence of such a reversal has been lacking in humans. Here, we use human resting-state fMRI and electrocorticography to demonstrate that δ-band activity and infraslow activity propagate in opposite directions between the hippocampus and cerebral cortex. Moreover, both δ activity and infraslow activity reverse propagation directions between the hippocampus and cerebral cortex across wake and SWS. These findings provide direct evidence for state-dependent reversals in human cortical-hippocampal communication.D eclarative memories are initially hippocampus-dependent and gradually become hippocampus-independent over time, that is, consolidated (1, 2). It is theorized that a two-stage reciprocal dialogue between the hippocampus and the cerebral cortex underlies memory consolidation (3-5). According to this model, active behavior generates experiential codes in the cortex that are transmitted to the hippocampus, which houses a labile information store. Later, during slow-wave sleep (SWS), recently acquired hippocampal information is reactivated and transmitted to the cerebral cortex, where it is integrated into a more permanent memory store (5, 6). Thus, the hippocampus and cerebral cortex are proposed to exchange roles in sending and receiving information across wake and SWS (5, 6). Importantly, this model does not imply that all signals travel from the "sender" to the "receiver." Instead, the theory proposes that high-frequency activity carries information from the sender to receiver, that is, from the cortex to hippocampus or the hippocampus to cortex, depending on the stage of memory consolidation (wake or SWS, respectively) (4). Conversely, low-frequency activity propagates from the receiver back to the sender to coordinate the transfer of high-frequency information through modulation of the sender's excitability (4, 7-9). Hence, the two-stage reciprocal dialogue model predicts that lower and higher frequency activity between the hippocampus and cortex should propagate in opposite directions across wake and SWS, as illustrated in the schematic in Fig. 1. However, such reversal has not been directly observed in humans.We have recently analyzed temporal lags (delays) in neural signals to study the net propagation of spontaneous activity. In particular, we investigated resting-state fMRI (rs-fMRI) blood oxygen level-dependent (BOLD) signals and demonstrated directed propagation of infraslow activity (<0.1...

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Spontaneous persistent activity in entorhinal cortex modulates cortico-hippocampal interaction in vivo

Cited by 127 publications

References 55 publications

How networks communicate: propagation patterns in spontaneous brain activity

How networks communicate: propagation patterns in spontaneous brain activity

Impaired spatial selectivity and intact phase precession in two-dimensional virtual reality

Human cortical–hippocampal dialogue in wake and slow-wave sleep

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