Cognitive modeling of human memory and learning : a non-invasive brain-computer interfacing approach - Ghosh, Lidia; Konar, Amit; Rakshit, Pratyusha; IEEE Xplore (Online Service); Wiley (Hoboken, New Jersey : Wiley, 2020)
"This book models human memory from a cognitive standpoint by utilizing brain activations acquired from the cortex by electroencephalographic (EEG) and functional near-infrared-spectroscopic (f-NIRs) means. It begins with an overview of the early models of memory. The authors then propose a simplistic model of Working Memory (WM) built with fuzzy Hebbian learning. A second perspective of memory models is concerned with Short-Term Memory (STM)-modeling in the context of 2-dimensional object-shape reconstruction from visually examined memorized instances. A third model assesses the subjective motor learning skill in driving from erroneous motor actions. Other models introduce a novel strategy of designing a two-layered deep Long Short-Term Memory (LSTM) classifier network and also deal with cognitive load assessment in motor learning tasks associated with driving. The book ends with concluding remarks based on principles and experimental results acquired in previous chapters"--
6.4.6 Experiment 3: Optimal Parameter Setting of Feature Selection and Classifier Units 235 -- 6.5 Biological Implications 237 -- 6.6 Performance Analysis 239 -- 6.6.1 Performance Analysis of the proposed IT2FS and GT2FS Classifier 239 -- 6.6.2 Statistical Validation of the Classifiers using McNamer;s Test 242 -- 6.7 Conclusion 243 -- References 243 -- Chapter 7: Conclusions and Future Directions of Research on BCI based Memory and Learning -- 7.1 Self-Review of the Works Undertaken in the Book 250 -- 7.2 Limitations of EEG BCI-Based Memory Experiments 252 -- 7.3 Further Scope of Future Research on Memory and Learning 253 -- References.
Includes bibliographical references and index.
Also available in print.
Mode of access: World Wide Web
Keywords: Memory; Brain-computer interfaces; Cognitive neuroscience; Electronic books