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The analysis indicates that in retrieving images by spatial content, retrieval response time and accuracy are traded-off.
In the retrieving phase, the MFNN iterates through all the layers to produce the retrieval response { a i(L), i = 1, …, NL} at the output layer based on the inputs of test patterns { a i(0), i = 1, …, N0}, the known weights w ij of the network, and the nonlinear activation function f i (for example, sigmoid function).
The average data retrieval response time in SOS+CSW mode is 17.6% of that of the SOS-alone mode.
During retrieval, response times for the source retrieval judgments for Ext-Ret were 1978+/−55 msec for hits and 2349+/−71 msec for misses.
Additional regressors were included to model the perceptual baseline trials (day 2: perceptual baseline encoding, perceptual baseline retrieval; day 2: perceptual baseline retrieval), response periods (collapsed across response and feedback/confidence ratings), cues and incorrect trials (summarized as one regressor of no interest).
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This strategy resulted in a large amount of incorrect answers to spatial schema trials (day 1, % correct retrieval responses, mean ± s.e.m.: excluded subjects: 45.8 ± 1.7; included subjects: 89.6 ± 3.4), while the non-spatial schema was learned correctly (excluded subjects: 79.7 ± 3.1; included subjects: 93.4 ± 1.1).
Following contextual fear conditioning, we then tested fear memory retrieval in response to an auditory cue, within a different environment.
The 'integrative database' schema is optimized for data integration, but is not efficient for data retrieval in response to complex queries.
This result contrasts with previous findings that repeatedly suppressing retrieval in response to a reminder can significantly impair recall performance of the avoided memories compared to baseline (e.g. Anderson & Green, 2001; Anderson et al., 2004; Bergström et al., 2009b; Depue et al., 2007).
Yet, research on distractor processing has shown that all features in a selection situation are integrated with responses and thereby can later on directly influence behavior due to feature-based retrieval of responses (which can be compatible or incompatible in the current situation).
To address this question we first correlated successful retrieval (Know responses) rates in the TOT task and FA values across the brain.
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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