Abstract

Learning while sleeping is a long-standing human fantasy, although studies have revealed that humans are not aware of what transpires when sleeping. Nevertheless, an absence of conscious knowledge fails to rule out the premise that individuals discern and recollect occurrences when asleep. The distinct functions involved in the retention of memories are currently being studied at multiple tiers, spanning from molecular reactions to whole-brain engagement. The Brain-Computer Interface (BCI) technique is a potent tool for user-system connection. BCI technologies are implemented to give impaired persons recourse to the information offered through standard functions. This review aims to determine whether using BCI technology to facilitate learning in sleep is practical and effective. The study will examine how BCI may stimulate particular brain activity during sleep, ease recollection and consolidation, and encourage learning new concepts. A multidisciplinary approach will be used in the investigation, integrating electroencephalography (EEG) recordings with behavioural and subjective indicators of learning performance. The findings of this study will shed light on how BCI technology may be used to improve learning and cognitive function when a person is sleeping, having implications for educational settings and cognitive therapy.

Keywords: brain-computer interfaces, BCI, learning, sleep, memory consolidation, neural stimulation, cognitive performance. Top of Form

Sleep is a rapid-transitional condition that comprises a lack of awareness, reduced action, and the capacity to react to external cues. It is crucial for learning procedures as it helps consolidate memories (Wang, 2020). Although memory consolidation is not the sole objective of sleep, it serves the most fundamental function as it contributes to establishing cognition in alertness (Puchkova, 2020). The fluidity of memory is solely established when the mind’s innate recollections are perpetually referred to and associated with the present-moment emotions. Since several academics and psychologists argue that memory is a crucial component of the mental state, it would be thrilling to discover that memory is created and developed substantially while asleep (Born & Wilhelm, 2011). In the neural structures of the human brain, awareness and the creation of persistent memory constitute distinct phenomena deemed incompatible and unable to coincide. Therefore, memory building could represent a sleep component that ultimately enables individuals to comprehend how sleeping is connected to a varying degree of cognitive decline.

However, specific research findings indicate that daily occurrences are neither recalled nor acknowledged on subsequent days (Ruch & Henke, 2020). These outcomes support the idea that sleep may not be the optimal period for lasting memory development due to changes within the brain functions, genetic expression trends, and synaptic remodelling. However, several of such issues fluctuate throughout sleep. Since knowledge obtained while awake is eventually reinforced by neural repetition while sleeping to assess the mental process in sleep, certain structural modifications to memory structures occur when sleeping. According to Rasch & Born (2013), every living can preserve and regain memories, which allows action modification in response to the circumstances of a dynamic setting and to determine and cultivate habits in a specific collection properly.

Learning is among the most efficient neurological processes, and besides promoting cognitive and interpersonal growth, it also empowers individuals to pursue professions that advance a particular standard of living. Innovative developments have emerged from addressing the disparity in interactions between individuals and computers utilizing various technologies. Brain-Computer Interface (BCI) is among the emerging techniques in the field of neurology that enable direct brain-to-external device connection via conventional neuromuscular avenues (Mudgal et al., 2020). The brain-computer interface (BCI) infrastructure takes the brain’s messages and evaluates transfers, and converts them to instructions which are subsequently sent to programs that carry out specific activities, enabling direct brain-to-external-device connection (Camargo-Vargas et al., 2021) (Fig 1.1). BCI interfaces translate neural activity effectively into management and interaction for people with erratic or inadequate motor abilities. The programs enable the brain to communicate fluidly with an electronic system, attracting significant interest in areas like artificial intelligence (Abdulkader et al., 2015). Innovation for brain-computer interfaces (BCI) holds the prospect of improving the academic setting that confronts numerous obstacles and inefficiencie