Persistent hippocampal neural firing and hippocampal-cortical coupling predict verbal working memory load

Boran, Ece; Fedele, Tommaso; Klaver, Peter; Hilfiker, Peter; Stieglitz, Lennart; Grünwald, Thomas; Sarnthein, Johannes

doi:10.1126/sciadv.aav3687

Cited by 91 publications

(167 citation statements)

References 41 publications

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“…Consistently with experimental findings (Boran et al, 2019), a PF cell begins tonic firing just before the corresponding obj cell becomes inactive, this firing ends when new object is presented as input.…”

Section: Resultssupporting

confidence: 87%

“…2) Persistent firing cells, PF in Fig.1. These cells are active during the maintenance period of cognitive tasks (Boran et al, 2019), and imply internal processing in the absence of an external input. We assumed that they are activated by an input object, and make synaptic contacts with all obj cells except the one corresponding to the same object, as illustrated by the grey circles between PF and obj cells in Fig.1.…”

Section: Resultsmentioning

confidence: 99%

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Sequence learning in a single trial: a spiking neurons model based on hippocampal circuitry

Coppolino

Migliore

2020

Preprint

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In contrast with our everyday experience using brain circuits, it can take a prohibitively long time to train a computational system to produce the correct sequence of outputs in the presence of a series of inputs. This suggests that something important is missing in the way in which models are trying to reproduce basic cognitive functions. In this work, we introduce a new neuronal network architecture that is able to learn, in a single trial, an arbitrary long sequence of any known objects. The key point of the model is the explicit use of mechanisms and circuitry observed in the hippocampus, which allow the model to reach a level of efficiency and accuracy that, to the best of our knowledge, is not possible with abstract network implementations. By directly following the natural system's layout and circuitry, this type of implementation has the additional advantage that the results can be more easily compared to experimental data, allowing a deeper and more direct understanding of the mechanisms underlying cognitive functions and dysfunctions, and opening the way to a new generation of learning architectures.

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Section: Resultssupporting

confidence: 87%

Section: Resultsmentioning

confidence: 99%

Sequence learning in a single trial: a spiking neurons model based on hippocampal circuitry

Coppolino

Migliore

2020

Preprint

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show abstract

“…17 In addition, nonstimulus-specific PA in the MTL has also been observed. 17,24 Together, this body of work reveals evidence for persistently active cells in the human MTL whose activity is related to WM.…”

Section: Introductionmentioning

confidence: 86%

Between persistently active and activity‐silent frameworks: novel vistas on the cellular basis of working memory

Kamiński

Rutishauser

2019

Annals of the New York Academy of Sciences

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Recent work has revealed important new discoveries on the cellular mechanisms of working memory (WM). These findings have motivated several seemingly conflicting theories on the mechanisms of short‐term memory maintenance. Here, we summarize the key insights gained from these new experiments and critically evaluate them in light of three hypotheses: classical persistent activity, activity‐silent, and dynamic coding. The experiments discussed include the first direct demonstration of persistently active neurons in the human medial temporal lobe that form static attractors with relevance to WM, single‐neuron recordings in the macaque prefrontal cortex that show evidence for both persistent and more dynamic types of WM representations, and noninvasive neuroimaging in humans that argues for activity‐silent representations. A key insight that emerges from these new results is that there are several neural mechanisms that support the maintenance of information in WM. Finally, based on established cognitive theories of WM, we propose a coherent model that encompasses these seemingly contradictory results. We propose that the three neuronal mechanisms of persistent activity, activity‐silent, and dynamic coding map well onto the cognitive levels of information processing (within focus of attention, activated long‐term memory, and central executive) that Cowan's WM model proposes.

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“…Replication of our main findings in the 1-back task rules out mechanistic explanations based solely on working memory, necessitating the involvement of longer-term memory mechanisms 24 . Second, past studies using tasks with short timescales but large memory loads that seem to overwhelm working memory appear to recruit medial temporal lobe structures 23,24,34 . Both the main TRANSFER task and its 1-back variant fall in this category.…”

Section: Discussionmentioning

confidence: 99%

Differences in memory for what, where, and when components of recently-formed episodes

Sakon

Kiani

2020

Preprint

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An integral feature of human memory is the ability to recall past events. What distinguishes such episodic memory from associative and semantic memories is the joint encoding and retrieval of "what," "where," and "when" (WWW) of events. Here, we investigated whether the WWW components of episodes are retrieved with equal fidelity. Using a novel task where human participants were probed on the WWW components of a recently-viewed synthetic movie, we found fundamental differences in mnemonic accuracy between these components. The memory of "when" had the lowest accuracy and was most severely influenced by primacy and recency. Further, the memory of "when" and "where" were most susceptible to interference due to changes in memory load. These findings suggest that episodes are not stored and retrieved as a coherent whole. Rather, memory components preserve a degree of independence, suggesting that remembering coherent episodes is an active reconstruction process.Episodic memories store past events that shape how we remember our lives. Each episodic engram unites disparate streams from our sensory cortices into a combined representation 1 . At minimum, episodic memories bind "what", "where", and "when" (WWW) components into these engrams 2,3 . Therefore, studies in animals 4-8 and humans 1,2,[9][10][11] have focused on these key components when probing the presence of-and brain structures responsible for-episodic memory.However, little is known about the strength of association and interactions between the WWW components of episodic memory 12-14 . Put more simply: are the what, where and when components of episodic memory encoded and recalled with equal fidelity? One possibility is that an episodic engram is a holistic representation in which the WWW components are inseparably intertwined. In this case, encoding and retrieval of each component should invariably be at the same level as the other components. Alternatively, the WWW components may be stored separately, and re-joined post-hoc during retrieval to synthesize a coherent memory of a past event. Between these two extreme hypotheses, there is a spectrum in which the what, where, and when components of an event are encapsulated with various degrees of separability in an engram.A handful of studies have investigated this separability between the components of episodes 1,12-19 . An early study that tasked humans to remember series of consonants that differed in either spatial (where) or temporal (when) order found limited differences in recall accuracy once phonemic coding (saying the letters to remember them) was accounted for 12 . A more recent study attempting to probe the separability of spatial vs. temporal memory utilized objects with little resemblance to

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Persistent hippocampal neural firing and hippocampal-cortical coupling predict verbal working memory load

Cited by 91 publications

References 41 publications

Sequence learning in a single trial: a spiking neurons model based on hippocampal circuitry

Sequence learning in a single trial: a spiking neurons model based on hippocampal circuitry

Between persistently active and activity‐silent frameworks: novel vistas on the cellular basis of working memory

Differences in memory for what, where, and when components of recently-formed episodes

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