Person:

Schaak, Diane

Fluorescent labeling techniques have been widely used in live cell studies; however, the labeling processes can be laborious and challenging for use in non-transfectable cells, and labels can interfere with protein functions. While label-free biosensors have been realized by nanofabrication, a method to track intracellular protein dynamics in real-time, in situ and in living cells has not been found. Here we present the first demonstration of label-free detection of intracellular p53 protein dynamics through a nanoscale surface plasmon-polariton fiber-tip-probe (FTP).

The brain has persistent internal states that can modulate every aspect of an animal’s mental experience1–4. In complex tasks such as foraging, internal state is dynamic5–8. C. elegans alternate between local search and global dispersal5. Rodents and primates exhibit trade-offs between exploitation and exploration6,7. However, fundamental questions remain about how persistent states are maintained in the brain, which upstream networks drive state transitions, and how state-encoding neurons exert neuromodulatory effects on sensory perception and decision making to govern appropriate behavior. Using tracking microscopy in larval zebrafish9, we can monitor whole brain neuronal activity at cellular resolution in a freely moving animal across spontaneous internal state transitions. We show that larval zebrafish alternate between two persistent behavioral states during foraging for live prey (paramecia). In the exploitation state, the animal inhibits locomotion and promotes hunting, generating small localized trajectories. In the exploration state, the animal promotes locomotion and suppresses hunting, generating long ranging trajectories that enhance spatial dispersion. We uncover a dorsal raphe subpopulation with persistent activity that robustly encodes the exploitation state. The exploitation state-encoding neurons, together with a multimodal trigger network that is associated with state transitions, form a stochastically activated nonlinear dynamical system. The activity of this oscillatory network correlates with a global re-tuning of sensorimotor transformations during foraging that leads to dramatic changes in both the motivation to hunt for prey and the accuracy of motor sequences during hunting. This work reveals an important hidden variable that shapes the temporal structure of motivation and decision making.

The brain has persistent internal states that can modulate every aspect of an animal’s mental experience(1–4). In complex tasks such as foraging, internal state is dynamic(5–8). C. elegans alternate between local search and global dispersal5. Rodents and primates exhibit trade-offs between exploitation and exploration(6,7). However, fundamental questions remain about how persistent states are maintained in the brain, which upstream networks drive state transitions, and how state-encoding neurons exert neuromodulatory effects on sensory perception and decision making to govern appropriate behavior. Using tracking microscopy in larval zebrafish9, we can monitor whole brain neuronal activity at cellular resolution in a freely moving animal across spontaneous internal state transitions. We show that larval zebrafish alternate between two persistent behavioral states during foraging for live prey (paramecia). In the exploitation state, the animal inhibits locomotion and promotes hunting, generating small localized trajectories. In the exploration state, the animal promotes locomotion and suppresses hunting, generating long ranging trajectories that enhance spatial dispersion. We uncover a dorsal raphe subpopulation with persistent activity that robustly encodes the exploitation state. The exploitation state-encoding neurons, together with a multimodal trigger network that is associated with state transitions, form a stochastically activated nonlinear dynamical system. The activity of this oscillatory network correlates with a global re-tuning of sensorimotor transformations during foraging that leads to dramatic changes in both the motivation to hunt for prey and the accuracy of motor sequences during hunting. This work reveals an important hidden variable that shapes the temporal structure of motivation and decision making.