Hu, Y., Wang, C., Yang, L., Pan, G., Liu, H., Yu, G., Ye, B. (2020). A Neural Basis for Categorizing Sensory Stimuli to Enhance Decision Accuracy. Curr. Biol. 30(24): 4896--4909.e6.
FlyBase ID
FBrf0247657
Publication Type
Research paper
Abstract
Sensory stimuli with graded intensities often lead to yes-or-no decisions on whether to respond to the stimuli. How this graded-to-binary conversion is implemented in the central nervous system (CNS) remains poorly understood. Here, we show that graded encodings of noxious stimuli are categorized in a decision-associated CNS region in Drosophila larvae, and then decoded by a group of peptidergic neurons for executing binary escape decisions. GABAergic inhibition gates weak nociceptive encodings from being decoded, whereas escalated amplification through the recruitment of second-order neurons boosts nociceptive encodings at intermediate intensities. These two modulations increase the detection accuracy by reducing responses to negligible stimuli whereas enhancing responses to intense stimuli. Our findings thus unravel a circuit mechanism that underlies accurate detection of harmful stimuli.
