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Encoding (memory)

About: Encoding (memory) is a research topic. Over the lifetime, 7547 publications have been published within this topic receiving 120214 citations. The topic is also known as: memory encoding & encoding of memories.


Papers
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Journal ArticleDOI
TL;DR: Whether the presence of event boundaries during encoding can structure information to improve memory is explored and it is demonstrated that memory was better when the information was distributed across two events rather than combined into a single event.

56 citations

Journal ArticleDOI
TL;DR: This study demonstrates that repeated memory retrieval might strengthen memory by inducing more differentiated or elaborated memory representations in the parietal cortex, and at the same time reducing demands on prefrontal-cortex-mediated cognitive control processes during retrieval.
Abstract: Encoding and retrieval processes enhance long-term memory performance. The efficiency of encoding processes has recently been linked to representational consistency: the reactivation of a represent ...

56 citations

Journal ArticleDOI
TL;DR: This analysis combines an analytical mean field approach, stochastic dynamics, and cellular simulations of a time-discrete McCulloch-Pitts network with binary synapses to calculate a sparsely connected network's capacity to store sequences of patterns that represent behavioral events.
Abstract: The CA3 region of the hippocampus is a recurrent neural network that is essential for the storage and replay of sequences of patterns that represent behavioral events. Here we present a theoretical framework to calculate a sparsely connected network's capacity to store such sequences. As in CA3, only a limited subset of neurons in the network is active at any one time, pattern retrieval is subject to error, and the resources for plasticity are limited. Our analysis combines an analytical mean field approach, stochastic dynamics, and cellular simulations of a time-discrete McCulloch-Pitts network with binary synapses. To maximize the number of sequences that can be stored in the network, we concurrently optimize the number of active neurons, that is, pattern size, and the firing threshold. We find that for one-step associations (i.e., minimal sequences), the optimal pattern size is inversely proportional to the mean connectivity c, whereas the optimal firing threshold is independent of the connectivity. If the number of synapses per neuron is fixed, the maximum number P of stored sequences in a sufficiently large, nonmodular network is independent of its number N of cells. On the other hand, if the number of synapses scales as the network size to the power of 3/2, the number of sequences P is proportional to N. In other words, sequential memory is scalable. Furthermore, we find that there is an optimal ratio r between silent and nonsilent synapses at which the storage capacity α = P//[c(1 + r)N] assumes a maximum. For long sequences, the capacity of sequential memory is about one order of magnitude below the capacity for minimal sequences, but otherwise behaves similar to the case of minimal sequences. In a biologically inspired scenario, the information content per synapse is far below theoretical optimality, suggesting that the brain trades off error tolerance against information content in encoding sequential memories.

56 citations

Patent
18 Aug 2004
TL;DR: In this article, the memory array is read with high fidelity, not to provide actual final digital data, but rather to provide raw data accurately reflecting the analog storage state, which information is sent to a memory controller for analysis and detection of the actual digital data.
Abstract: Maximized multi-state compaction and more tolerance in memory state behavior is achieved through a flexible, self-consistent and self-adapting mode of detection, covering a wide dynamic range. For high density multi-state encoding, this approach borders on full analog treatment, dictating analog techniques including A to D type conversion to reconstruct and process the data. In accordance with the teachings of this invention, the memory array is read with high fidelity, not to provide actual final digital data, but rather to provide raw data accurately reflecting the analog storage state, which information is sent to a memory controller for analysis and detection of the actual final digital data.

56 citations

Journal ArticleDOI
TL;DR: In two paired-associate probe experiments, the items in the last input position in five-pair lists were recalled perfectly in immediate recall, but practically never in a subsequent delayed recall test as discussed by the authors.

56 citations


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Performance
Metrics
No. of papers in the topic in previous years
YearPapers
20231,083
20222,253
2021450
2020378
2019358
2018363