T-ERC_COG - Tremplin-ERC Consolidator Grant

Higher-order motor control of stochastic behavior in an uncertain environment – MOTORHEAD

Submission summary

Decision-making often occurs in the absence of instruction to guide action. Instead, theories and experiments have predicted that the brain must compute a decision-value based on past experience to select the best action. This implies that the action with the highest subjective value should always be chosen. However, behavior is often stochastic with variability from trial-to-trial. To resolve this long-standing paradox, MOTORHEAD will take full advantage of state-of-the-art in vivo neuronal recordings and computational methods in rodent to bridge for the first time the gap between deterministic decision-signal and stochastic motor commands, achieving thus an unprecedented level of understanding of these “unpredictable” behaviors. Indeed, despite decade of intensive work, key questions remain unexplored: i) How such a deterministic decision signal is maintained without necessarily causing movement? ii) And how it is then converted to a biased motor command with trial-by-trial variability? Here, we hypothesize that these two operations occur across recurrent cortical layers of the secondary motor cortex (M2) of rodent, contributing to the proper balance between exploiting known secured options and exploring uncertain ones. Specifically, we posit that: i) Distinct populations of layer (L) 5 pyramidal neurons (PN) generate biased action according to the decision statistics provided by L2/3 PN. Specific attractor architectures, with different stability to noise, could cause the system to behave more or less randomly. ii) This top-down excitation could be gated by bottom-up plasticity forces from reward-related structures, which modulate decision-value to account for past choice outcome, notably when the action no longer generates the expected outcome. To achieve this breakthrough, we propose an ambitious system neuroscience approach, at high spatial/temporal resolution, to illuminate the cellular principles underlying the control and transformation of decision variable.

Project coordination

Frederic Gambino (INSTITUT INTERDISCIPLINAIRE DE NEUROSCIENCES)

The author of this summary is the project coordinator, who is responsible for the content of this summary. The ANR declines any responsibility as for its contents.

Partner

IINS INSTITUT INTERDISCIPLINAIRE DE NEUROSCIENCES

Help of the ANR 112,933 euros
Beginning and duration of the scientific project: May 2022 - 24 Months

Useful links

Explorez notre base de projets financés

 

 

ANR makes available its datasets on funded projects, click here to find more.

Sign up for the latest news:
Subscribe to our newsletter