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They had subjects perform the same cued memory task, then applied a broad TMS pulse just after the signature of the uncued memory item had faded.
This 'memory masking' effect occurs when the mask differs from the memory item along the dimension to be remembered: When instructed to remember the spatial frequency of a grating, no interference is observed when the spatial frequency of the mask matches the frequency to be remembered, but with a masker twice or half the frequency of the memory item (±1 octave), memory is substantially impaired.
One particularly impressive characteristic of the model is its ability to simulate the "tip-of-tongue" phenomenon, in which one is certain about some features of the desired memory item, yet has difficulty in retrieving it (sometimes being unable to do so).
The model is robust against errors for at least two reasons: i) the contribution of any one hard location, in isolation, is negligible, and ii) the system can readily deal with incomplete information and still converge to a previously registered memory item.
Memory was evaluated through its components: working memory (item 1&2), episodic memory (item 3 though 9) and semantic memory (item 10&11).
Thus, the visual features of the memory item, and not the semantic association between the memory item and the second exemplar, may have been what biased attention.
Similar(15)
puzzling limit of about 7 short-term memory items that can be stored by humans.
Theoretical results are presented for storage/retrieval of memory items represented by feature vectors made up of 1000 randomly selected bivalent components.
Our modeling approach is based on the idea that uncompleted or partially completed intentions are available as context in the current goal, and they prime related memory items while inhibiting unrelated memory items.
Sparse distributed memory (SDM) is a content-addressable memory technique that relies on close memory items tending to be clustered together.
The cognitive neuroscience of human memory tries to comprehend how we encode, store, and retrieve memory items within and across those systems.
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Since I tried Ludwig back in 2017, I have been constantly using it in both editing and translation. Ever since, I suggest it to my translators at ProSciEditing.

Justyna Jupowicz-Kozak
CEO of Professional Science Editing for Scientists @ prosciediting.com