Replay, the default mode network and the cascaded memory systems model

Kaefer, Karola; Stella, Federico; McNaughton, Bruce L.; Battaglia, Francesco P.

doi:10.1038/s41583-022-00620-6

Cited by 51 publications

(38 citation statements)

References 188 publications

(230 reference statements)

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“…Initial learning elicited greater hippocampal-iLOC connectivity during post-initial-learning rest, which might reflect a possible increase in neural excitability of this circuit. Since neuronal excitability in the hippocampal-neocortical circuitry prior to encoding is recognized to modulate subsequent allocation and integration of newly acquired information into long-term memory ( Josselyn and Frankland, 2018 ; Kaefer et al, 2022 ; Schlichting and Frankland, 2017 ; van Dongen et al, 2011 ; Yoo et al, 2012 ), we thus speculate that greater hippocampal-iLOC connectivity might provide a preparatory state to allocate new information into existing memory traces during emotional learning and thus contribute to emotion-charged retroactive memory benefit. Besides, neural circuits activated by emotional learning exhibit persistent activity and also alter a series of systems-level interactions during post-emotional-learning rest ( de Voogd et al, 2016 ; Hermans et al, 2017 ; Murty et al, 2017 ), including hippocampal connectivity with aPFC, mPFC, PCC, and IPL observed in this study.…”

Section: Discussionmentioning

confidence: 98%

“…Beyond online encoding, offline processes at awake rest and sleep also contribute to emotional memory benefit, most likely involving reconfiguration of hippocampal functional connectivity with distributed neocortical networks ( de Voogd et al, 2016 ; Schlichting and Frankland, 2017 ; Tambini et al, 2010 ). Recent studies have demonstrated that neural engagement, for instance, excitable hippocampal-neocortical coordinated interactions prior to encoding could affect the allocation of new information into specific neural populations and form a preparatory network for igniting reactivation or replay cascades to support memory integration ( Josselyn and Frankland, 2018 ; Kaefer et al, 2022 ; Schlichting and Frankland, 2017 ; van Dongen et al, 2011 ). Thus, it is possible that an excitable brain state at pre-emotional-encoding rest might modulate subsequent emotional memory integration and predict memory performance.…”

Section: Introductionmentioning

confidence: 99%

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Emotional learning retroactively promotes memory integration through rapid neural reactivation and reorganization

Zhu

Zeng

Ren

et al. 2022

eLife

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Neutral events preceding emotional experiences can be better remembered, likely by assigning them as significant to guide possible use in future. Yet, the neurobiological mechanisms of how emotional learning enhances memory for past mundane events remain unclear. By two behavioral studies and one functional magnetic resonance imaging study with an adapted sensory preconditioning paradigm, we show rapid neural reactivation and connectivity changes underlying emotion-charged retroactive memory enhancement. Behaviorally, emotional learning enhanced initial memory for neutral associations across the three studies. Neurally, emotional learning potentiated trial-specific reactivation of overlapping neural traces in the hippocampus and stimulus-relevant neocortex. It further induced rapid hippocampal-neocortical functional reorganization supporting such retroactive memory benefit, as characterized by enhanced hippocampal-neocortical coupling modulated by the amygdala during emotional learning, and a shift of hippocampal connectivity from stimulus-relevant neocortex to transmodal prefrontal-parietal areas at post-learning rests. Together, emotional learning retroactively promotes memory integration for past neutral events through stimulating trial-specific reactivation of overlapping representations and reorganization of associated memories into an integrated network to foster its priority for future use.

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Section: Discussionmentioning

confidence: 98%

Section: Introductionmentioning

confidence: 99%

Emotional learning retroactively promotes memory integration through rapid neural reactivation and reorganization

Zhu

Zeng

Ren

et al. 2022

eLife

View full text Add to dashboard Cite

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“…This suggests that RSPv is not tonically hyperactive but has exaggerated responses when activated, consistent with impaired feedforward inhibitory input from CA1 (Yamawaki e t al., 2019; Opalka et al, 2020). Further work is required to test the hypothesis that disruption in the balance of excitation and inhibition (Palop and Mucke, 2016) may be restricted to brain states or events (Kaefer et al, 2022).…”

Section: Discussionmentioning

confidence: 99%

Circuit-specific selective vulnerability in the DMN persists in the face of widespread amyloid burden

Brunwasser

Farris

Elmore

et al. 2022

Preprint

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The relationship between brainwide functional decline and accumulation of pathological protein aggregates in Alzheimer’s disease (AD) is complex and not well understood. A set of highly interconnected cortical regions known as the default mode network (DMN) exhibits selective vulnerability to both functional decline and amyloid beta (Aβ) plaques in early AD. One possibility is that early Aβ accumulation in the DMN drives vulnerability. However, it is unknown whether there is something intrinsic to neuronal projections within the DMN that biases these circuits towards dysfunction. Here we directly test this hypothesis using long-term recordings of the spiking activity of ensembles of single units in freely behaving mice characterized by global cortical and hippocampal Aβ burden (APP/PS1). Specifically, we track the interactions of a population of neurons within a DMN region and two additional populations that comprise monosynaptic targets, one within and the other outside the DMN. In addition, we record single neurons in hippocampus and examine interactions between in-DMN and out-DMN cortical circuits triggered on hippocampal sharp-wave ripples, stereotyped hippocampal events that contribute to memory consolidation in the cortex. We examine the statistics of local activity as well as inter-regional communication in a region, genotype, and brain-state dependent manner. Our data reveal dysfunction restricted to in-DMN projecting circuits. In contrast, communication along neuronal projections that originate in the DMN but target out-DMN populations are equivalent in APP/PS1 and WT mice. Circuit dysfunction is most evident throughout sleep as well as within sharp-wave ripples. Our results indicate that cells in the DMN exhibit differential intrinsic vulnerability to amyloid injury dependent on their projection targets.

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“…Recent studies reveal hippocampal involvement in the default mode network activity. default mode network may mediate interactions between the hippocampus and the neocortex in memory formation and replay [100].…”

Section: Predominant Hyperconnectivity Of Low-frequency Oscillations ...mentioning

confidence: 99%

Predicting alcohol-related memory problems in older adults: A machine learning study with multi-domain features

Kamarajan

Pandey

Chorlian

et al. 2023

Preprint

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Memory problems are common among older adults with a history of alcohol use disorder (AUD). Employing a machine learning framework, the current study investigates the use of multi-domain features to classify individuals with and without alcohol-induced memory problems. A group of 94 individuals (ages 50-81 years) with alcohol-induced memory problems (Memory group) were compared with a matched Control group who did not have memory problems. The Random Forests model identified specific features from each domain that contributed to the classification of Memory vs. Control group (AUC=88.29%). Specifically, individuals from the Memory group manifested a predominant pattern of hyperconnectivity across the default mode network regions except some connections involving anterior cingulate cortex which were predominantly hypoconnected. Other significant contributing features were (i) polygenic risk scores for AUD, (ii) alcohol consumption and related health consequences during the past 5 years, such as health problems, past negative experiences, withdrawal symptoms, and the largest number of drinks in a day during the past 12 months, and (iii) elevated neuroticism and increased harm avoidance, and fewer positive "uplift" life events. At the neural systems level, hyperconnectivity across the default mode network regions, including the connections across the hippocampal hub regions, in individuals with memory problems may indicate dysregulation in neural information processing. Overall, the study outlines the importance of utilizing multidomain features, consisting of resting-state brain connectivity collected ~18 years ago, together with personality, life experiences, polygenic risk, and alcohol consumption and related consequences, to predict alcohol-related memory problems that arise in later life.

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Replay, the default mode network and the cascaded memory systems model

Cited by 51 publications

References 188 publications

Emotional learning retroactively promotes memory integration through rapid neural reactivation and reorganization

Emotional learning retroactively promotes memory integration through rapid neural reactivation and reorganization

Circuit-specific selective vulnerability in the DMN persists in the face of widespread amyloid burden

Predicting alcohol-related memory problems in older adults: A machine learning study with multi-domain features

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