A Locus Coeruleus- Dorsal CA1 Dopaminergic Circuit Modulates Memory Linking

Chowdhury, Arindrajit; Luchetti, Alessandro; Fernandes, Giselle; Filho, Daniel Almeida; Kastellakis, George; Tzilivaki, Alexandra; Ramirez, Erica M.; Tran, Mary Y.; Poirazi, Panayiota; Silva, Alcino

doi:10.2139/ssrn.3985190

Cited by 3 publications

(3 citation statements)

References 79 publications

Supporting

Mentioning

Contrasting

Order By: Relevance

“…We found that our learning rule selectively strengthens the reactivated synapses, linking together the memory allocation hypothesis with burst reactivation-induced plasticity. Interestingly, it was recently reported that DA released by locus coeruleus cells projecting to dCA1 has a key permissive role in contextual memory linking ( Chowdhury et al, 2021 ). Moreover, the rule could also accommodate a temporally discontiguous instructive learning signal or a specific supervisory feedback signal.…”

Section: Discussionmentioning

confidence: 99%

Postsynaptic burst reactivation of hippocampal neurons enables associative plasticity of temporally discontiguous inputs

Fuchsberger

Clopath

Jarzebowski

et al. 2022

eLife

View full text Add to dashboard Cite

A fundamental unresolved problem in neuroscience is how the brain associates in memory events that are separated in time. Here we propose that reactivation-induced synaptic plasticity can solve this problem. Previously, we reported that the reinforcement signal dopamine converts hippocampal spike timing-dependent depression into potentiation during continued synaptic activity (Brzosko et al., 2015). Here, we report that postsynaptic bursts in the presence of dopamine produce input-specific LTP in mouse hippocampal synapses 10 minutes after they were primed with coincident pre- and postsynaptic activity (post-before-pre pairing; Δt = -20 ms). This priming activity induces synaptic depression and sets an NMDA receptor-dependent silent eligibility trace which, through the cAMP-PKA cascade, is rapidly converted into protein synthesis-dependent synaptic potentiation, mediated by a signaling pathway distinct from that of conventional LTP. This synaptic learning rule was incorporated into a computational model, and we found that it adds specificity to reinforcement learning by controlling memory allocation and enabling both ‘instructive’ and 'supervised' reinforcement learning. We predicted that this mechanism would make reactivated neurons activate more strongly and carry more spatial information than non-reactivated cells, which was confirmed in freely moving mice performing a reward-based navigation task.

show abstract

Section: Discussionmentioning

confidence: 99%

Postsynaptic burst reactivation of hippocampal neurons enables associative plasticity of temporally discontiguous inputs

Fuchsberger

Clopath

Jarzebowski

et al. 2022

eLife

View full text Add to dashboard Cite

show abstract

“…We found that our learning rule selectively strengthens the reactivated synapses, linking together the memory allocation hypothesis with burst reactivation-dependent plasticity. Interestingly, it was recently reported that DA released by LC cells projecting to dCA1 have a key permissive role in contextual memory linking (Chowdhury et al, 2021). Moreover, the rule could also accommodate a temporally discontiguous instructive learning signal or a specific supervisory feedback signal.…”

Section: Discussionmentioning

confidence: 99%

Postsynaptic burst reactivation of hippocampal neurons enables associative plasticity of temporally discontiguous inputs

Fuchsberger

Clopath

Jarzebowski

et al. 2022

Preprint

View full text Add to dashboard Cite

A fundamental unresolved problem in neuroscience is how the brain associates in memory events that are separated in time. Here we propose that reactivation-induced synaptic plasticity can solve this problem. Previously, we reported that the reinforcement signal dopamine converts hippocampal spike timing-dependent depression into potentiation during continued synaptic activity (Brzosko et al., 2015). Here, we report that postsynaptic bursts in the presence of dopamine produces input-specific LTP in hippocampal synapses 10 minutes after they were primed with coincident pre- and postsynaptic activity. The priming activity sets an NMDAR-dependent silent eligibility trace which, through the cAMP-PKA cascade, is rapidly converted into protein synthesis-dependent synaptic potentiation, mediated by a signaling pathway distinct from that of conventional LTP. Incorporated into a computational model, this synaptic learning rule adds specificity to reinforcement learning by controlling memory allocation and enabling both 'instructive' and 'supervised' reinforcement learning. We predicted that this mechanism would make reactivated neurons activate more strongly and carry more spatial information than non-reactivated cells, which was confirmed in freely moving mice performing a reward-based navigation task.

show abstract

“…The hippocampus plays essential roles in memory retrieval (Liu et al, 2012; Robinson et al, 2020) and consolidating new learning (Davis and Squire, 1984; Girardeau et al, 2009). One way these functions cooperate is through the process of integrating memories that are learned under the same hippocampal activity pattern, such as when two experiences occur close in time (Cai et al, 2016; Chowdhury et al, 2022) or when a second experience reminds one of the first (Zeithamova et al, 2012; Lee et al, 2017). In the current study, we found increased reactivation of hippocampal activity patterns associated with prior problems exclusively in the Structured training group and specifically late in learning, coinciding with the time that memory integration became apparent behaviorally.…”

Section: Discussionmentioning

confidence: 99%

Evolution of predictive memory in the hippocampus

Miller

Jacob

Ramsaran

et al. 2022

Preprint

View full text Add to dashboard Cite

The brain organizes experiences into memories that can be used to guide future behavior. Hippocampal CA1 population activity may reflect the retrieval of predictive models that contain information about future events, but little is known about how these kinds of memories develop with experience. We trained mice on a series of tone discrimination problems with or without a common statistical structure to observe how memories are formed and updated during learning. Mice that learned structured problems integrated their experiences into a predictive model that contained the solutions to upcoming novel problems. Retrieving the model during learning improved discrimination accuracy and facilitated learning by decreasing the amount of new information that needed to be acquired. Using calcium imaging to track the activity of thousands of CA1 neurons during learning on this task, we observed the emergence of a persistent hippocampal ensemble at the same time that mice formed a predictive model of their environment. This ensemble was reactivated during training and incorporated new neuronal activity patterns from each training problem. Interestingly, the degree to which mice reactivated the ensemble was related to how well their model predicted the content of the current problem, ensuring that the model was only updated with congruent information. In contrast, mice trained on unstructured problems did not form a predictive model or engage a persistent ensemble. These results show how hippocampal activity supports building predictive models by organizing newly learned information according to its congruence with existing memories.

show abstract

A Locus Coeruleus- Dorsal CA1 Dopaminergic Circuit Modulates Memory Linking

Cited by 3 publications

References 79 publications

Postsynaptic burst reactivation of hippocampal neurons enables associative plasticity of temporally discontiguous inputs

Postsynaptic burst reactivation of hippocampal neurons enables associative plasticity of temporally discontiguous inputs

Postsynaptic burst reactivation of hippocampal neurons enables associative plasticity of temporally discontiguous inputs

Evolution of predictive memory in the hippocampus

Contact Info

Product

Resources

About