Hacking the functions of sleep: noninvasive approaches to stimulate sleep neurophysiology

Sleep is essentially contributing to human health and well-being through multiple biological functions, including restoration and biosynthesis, brain clearance, energy metabolism, immunological and endocrine processing, synaptic plasticity, memory consolidation, and regulation of cognitive and emotional processes. Sleep disturbances are highly prevalent and are both a symptom and a contributing risk factor for psychiatric, neurological, and somatic disorders. Given the limitations of pharmacological interventions, noninvasive neuromodulation techniques ranging from noninvasive transcranial [transcranial magnetic stimulation (TMS), transcranial direct current stimulation (tDCS), transcranial alternating current stimulation (tACS), transcranial random noise stimulation (tRNS), temporal interference stimulation (tTIS), and transcranial ultrasound stimulation (TUS)] to peripheral sensory (auditory, olfactory, visual, tactile, vestibular) and electrical nerve (galvanic vestibular, transcutaneous vagus nerve, and median nerve) stimulation have gained increasing attention as potential tools to modulate sleep physiology. These techniques offer promising avenues for both therapeutic applications and fundamental research into sleep-dependent neuroplasticity, interregional communication, and oscillatory activity. However, sleep is not a uniform state but a highly complex and dynamic phenomenon, with intricate macrostructural [e.g., non-rapid eye movement (NREM)-rapid eye movement (REM) sleep balance, sleep efficiency] and microstructural (e.g., hierarchically nested slow waves and spindles) characteristics that contribute to a variety of functions. This complexity necessitates precise targeting strategies, often employing real-time brain state-dependent stimulation, to modulate specific sleep-related processes effectively. In this review, we summarize the functions of sleep and the available noninvasive tools for its modulation, addressing key methodological challenges and providing recommendations for best practices in sleep neuromodulation.