To optimally encode and store sensory information, neural circuits in the brain must constantly adapt to ever-changing conditions, such as alterations in sensory stimulus intensity and the context in which stimuli are presented. Recent findings suggest that neuronal and network adaptations following alterations in sensory input are modulated by animals’ behavioral state. For example, a variety of plasticity mechanisms (e.g., homeostatic, heterosynaptic, and spike timing-dependent plasticity) are gated by aspects of brain physiology (such as neuromodulation) which vary as a function of vigilance state, attention, arousal, and motivation. The aspects of behavior that affect encoding of experience, the physiological mechanisms mediating these effects, and the features of brain states that promote long-term storage of information in neural circuits remain largely unknown. Furthermore, the question of how the brain maintains functional continuity and reliable information processing across changing behavioral states remains a mystery. Here physiological, behavioral, and computational perspectives are brought to bear on these issues - with the objective of clarifying how various brain states contribute to information processing and stable output dynamics in neural circuits.
To optimally encode and store sensory information, neural circuits in the brain must constantly adapt to ever-changing conditions, such as alterations in sensory stimulus intensity and the context in which stimuli are presented. Recent findings suggest that neuronal and network adaptations following alterations in sensory input are modulated by animals’ behavioral state. For example, a variety of plasticity mechanisms (e.g., homeostatic, heterosynaptic, and spike timing-dependent plasticity) are gated by aspects of brain physiology (such as neuromodulation) which vary as a function of vigilance state, attention, arousal, and motivation. The aspects of behavior that affect encoding of experience, the physiological mechanisms mediating these effects, and the features of brain states that promote long-term storage of information in neural circuits remain largely unknown. Furthermore, the question of how the brain maintains functional continuity and reliable information processing across changing behavioral states remains a mystery. Here physiological, behavioral, and computational perspectives are brought to bear on these issues - with the objective of clarifying how various brain states contribute to information processing and stable output dynamics in neural circuits.
