Instruct: Identify the main and secondary category of Arxiv papers based on the titles and abstracts
Query: Predicting the Transition from Short-term to Long-term Memory based on
  Deep Neural Network   Memory is an essential element in people's daily life based on experience. So
far, many studies have analyzed electroencephalogram (EEG) signals at encoding
to predict later remembered items, but few studies have predicted long-term
memory only with EEG signals of successful short-term memory. Therefore, we aim
to predict long-term memory using deep neural networks. In specific, the
spectral power of the EEG signals of remembered items in short-term memory was
calculated and inputted to the multilayer perceptron (MLP) and convolutional
neural network (CNN) classifiers to predict long-term memory. Seventeen
participants performed visuo-spatial memory task consisting of picture and
location memory in the order of encoding, immediate retrieval (short-term
memory), and delayed retrieval (long-term memory). We applied
leave-one-subject-out cross-validation to evaluate the predictive models. As a
result, the picture memory showed the highest kappa-value of 0.19 on CNN, and
location memory showed the highest kappa-value of 0.32 in MLP. These results
showed that long-term memory can be predicted with measured EEG signals during
short-term memory, which improves learning efficiency and helps people with
memory and cognitive impairments.

14
The categories of this paper are: math-ph
20
The categories of this paper are: acc-phys
9
The categories of this paper are: nlin
37
The categories of this paper are: supr-con
8
The categories of this paper are: hep-ex
10
The categories of this paper are: q-bio
27
The categories of this paper are: comp-gas
11
The categories of this paper are: hep-lat
25
The categories of this paper are: patt-sol
33
The categories of this paper are: plasm-ph
4
The categories of this paper are: cond-mat
32
The categories of this paper are: atom-ph
12
The categories of this paper are: nucl-th
23
The categories of this paper are: solv-int
21
The categories of this paper are: adap-org
7
The categories of this paper are: hep-th