Shenhav Lab
@shenhavlab.bsky.social
Neuroscience of motivation, decision making, and cognitive control
shenhavlab.org
shenhavlab.org
With increasing age, people move slower through the space of control configurations that determine performance. We also show that the ability to adjust control configurations and the ability to maintain performance despite goal switches is maintained across the lifespan.
September 18, 2025 at 5:02 PM
With increasing age, people move slower through the space of control configurations that determine performance. We also show that the ability to adjust control configurations and the ability to maintain performance despite goal switches is maintained across the lifespan.
We propose that the speed of movement between control limits cognitive flexibility in older adults. To test this, we had people across the lifespan perform a cognitively demanding task with changing performance goals (perform the task quickly vs. accurately).
September 18, 2025 at 5:02 PM
We propose that the speed of movement between control limits cognitive flexibility in older adults. To test this, we had people across the lifespan perform a cognitively demanding task with changing performance goals (perform the task quickly vs. accurately).
We also show (Study 4) that the frequency of performance goal changes parametrically increases the costs, and that the expectation about change frequency determines the cost.
August 27, 2025 at 4:37 PM
We also show (Study 4) that the frequency of performance goal changes parametrically increases the costs, and that the expectation about change frequency determines the cost.
We also confirmed 2 other predictions our model makes: we show that people exhibit larger costs when target control states are more distant (Study 2) and when they have less time to adjust control (Study 3).
August 27, 2025 at 4:37 PM
We also confirmed 2 other predictions our model makes: we show that people exhibit larger costs when target control states are more distant (Study 2) and when they have less time to adjust control (Study 3).
Confirming the prediction of the model, in Study 1 we found that control states (defined by levels of threshold and drift rate) are pulled closer together in blocks which demand control adjustments that produce costs.
August 27, 2025 at 4:37 PM
Confirming the prediction of the model, in Study 1 we found that control states (defined by levels of threshold and drift rate) are pulled closer together in blocks which demand control adjustments that produce costs.
Due to the time it takes to adjust control states, the model predicts the existence of a control adjustment cost. When frequently moving between different goals (Varying blocks) people will undershoot their target control state.
August 27, 2025 at 4:37 PM
Due to the time it takes to adjust control states, the model predicts the existence of a control adjustment cost. When frequently moving between different goals (Varying blocks) people will undershoot their target control state.
We develop a dynamical systems model to describe such adjustments in continuous control signals. Our model proposes that control states are adjusted gradually from their current state toward the target state specified by the new performance goal.
August 27, 2025 at 4:37 PM
We develop a dynamical systems model to describe such adjustments in continuous control signals. Our model proposes that control states are adjusted gradually from their current state toward the target state specified by the new performance goal.