A System for True and False Memory Prediction based on 2D and 3D Educational Contents and EEG Brain Signals

The advances in 3D consumer technology has raised the question whether 3D educational contents are more effective than their 2D counterparts for learning and memory retention/recall. Electroencephalography (EEG) brain signals have been extensively studied to decode human brain activations performing different tasks. We studied the impact of 2D and 3D educational contents on learning and memory recall using EEG brain signals. For this purpose, a classification approach has been adopted that predicts true and false memories in case of both short term memory (STM) and long term memory (LTM) and helps to decide whether there is a difference between the impact of 2D and 3D educational contents on learning and memory recall. In the proposed approach, EEG brain signals are converted into topomaps (scalp-maps) and then discriminative features are extracted/selected from these topomaps and finally support vector machine (SVM) is employed to predict brain states as true and false memories. For data collection, sixty eight healthy individuals volunteered, half of which watched the learning material in 2D format whereas the second half watched the same material in 3D format. After learning task, memory recall tasks were performed after 30 minutes (for STM) and two months (for LTM), and EEG signals were recorded. In case of STM, 97.5% prediction accuracy was achieved for 3D and 96.6% for 2D and in case of LTM, it was 100% both for 2D and 3D. The statistical analysis of the results suggested that for learning and memory recall both 2D and 3D education materials do not have much difference in case of STM and LTM.