Summary: A new study provides insight into the neural circuit computations that underlie risk-reward decision making.
Source: Yale.
The hungrier the mouse, the more risk it will take to grab cheese on the floor of a home with a house cat.
“But how does it make this risk-reward computation?” asks Michael Nitabach, professor of cellular and molecular physiology and professor of genetics at Yale.
The answer for worms — and potentially mammals such as people — is that the nervous system reverses the usual flow of information from sensory input areas to higher sensory-motor integration centers, Nitabach and colleagues report Nov. 17 in the journal Neuron.
Nitabach’s team, led by Yale graduate student D. Dipon Ghosh, compared the nervous systems of hungry and sated worms engaged in a task that requires them to cross a dangerous barrier that could kill them in order to obtain food. They found that signals that lead to the decision whether to cross this barrier act in a “top-down” fashion.
Instead of solely receiving and processing information from sensory areas, higher-order integration centers signal the sensory areas to implement the decision. This same reverse top-down flow of information occurs in the brains of human beings and other mammals, but it has not previously been linked to risk-reward decisions.
“The studies provide unprecedented insight into the detailed neural circuit computations underlying risk-reward decision-making in any animal,” Nitabach said.
Source: Bill Hathaway – Yale
Image Source: NeuroscienceNews.com image is adapted from the Yale press release.
Original Research: Abstract for “Neural Architecture of Hunger-Dependent Multisensory Decision Making in C. elegans” by D. Dipon Ghosh, Tom Sanders, Soonwook Hong, Li Yan McCurdy, Daniel L. Chase, Netta Cohen, Michael R. Koelle, and Michael N. Nitabach in Neuron. Published online November 17 2016 doi:10.1016/j.neuron.2016.10.030
[cbtabs][cbtab title=”MLA”]Yale. “Food or Flight? Molecular Mechanics of Risk-Reward Equation Described.” NeuroscienceNews. NeuroscienceNews, 18 November 2016.
<https://neurosciencenews.com/risk-reward-equation-psychology-5556/>.[/cbtab][cbtab title=”APA”]Yale. (2016, November 18). Food or Flight? Molecular Mechanics of Risk-Reward Equation Described. NeuroscienceNews. Retrieved November 18, 2016 from https://neurosciencenews.com/risk-reward-equation-psychology-5556/[/cbtab][cbtab title=”Chicago”]Yale. “Food or Flight? Molecular Mechanics of Risk-Reward Equation Described.” https://neurosciencenews.com/risk-reward-equation-psychology-5556/ (accessed November 18, 2016).[/cbtab][/cbtabs]
Abstract
Neural Architecture of Hunger-Dependent Multisensory Decision Making in C. elegans
Highlights
•Autocrine neuropeptide signaling motif regulates a C. elegans multisensory decision
•Multisensory decision is also modulated by top-down extrasynaptic aminergic signal
•Computational modeling reveals neuronal network dynamics underlying decision
•Food deprivation suppresses aminergic feedback pathway to increase threat tolerance
Summary
Little is known about how animals integrate multiple sensory inputs in natural environments to balance avoidance of danger with approach to things of value. Furthermore, the mechanistic link between internal physiological state and threat-reward decision making remains poorly understood. Here we confronted C. elegans worms with the decision whether to cross a hyperosmotic barrier presenting the threat of desiccation to reach a source of food odor. We identified a specific interneuron that controls this decision via top-down extrasynaptic aminergic potentiation of the primary osmosensory neurons to increase their sensitivity to the barrier. We also establish that food deprivation increases the worm’s willingness to cross the dangerous barrier by suppressing this pathway. These studies reveal a potentially general neural circuit architecture for internal state control of threat-reward decision making.
“Neural Architecture of Hunger-Dependent Multisensory Decision Making in C. elegans” by D. Dipon Ghosh, Tom Sanders, Soonwook Hong, Li Yan McCurdy, Daniel L. Chase, Netta Cohen, Michael R. Koelle, and Michael N. Nitabach in Neuron. Published online November 17 2016 doi:10.1016/j.neuron.2016.10.030
