Shenhav Lab

➡️P3.I.45: Validating predictions of a flexible decision-making model for varying decision goals and choice set properties by Ana Hernandez at 11:15 on 10/5.

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At #SNE2025? Check out our lab's presentations!

➡️O.03.02: "Competitors or Opportunities? Mutual exclusivity alters neural and attentional processing of choice alternatives" by @jasonleng.bsky.social at 9:00 on 10/4.

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Our findings demonstrate the critical role that cognitive dynamics play in explaining the mechanisms through which cognitive inflexibility arises in older adulthood.

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.

Using computational modeling and building on our previous work (psycnet.apa.org/record/2026-...), we measured changes in two control signals (attentional focus and response caution) as people of different ages switched between goals that induced distinct control configurations.

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).

Changing goals require adjustments of cognitive control configurations (e.g., level of attentional focus), even within similar tasks (e.g., emailing a friend vs. your boss). We formalize such adjustments as a dynamical system moving from its current state to the new target state.

Slower transitions between control states lead to reductions in cognitive flexibility over the lifespan Declines in cognitive flexibility are a hallmark of cognitive aging, but their causes remain elusive. Here, we examine a previously untested source of aging-related cognitive inflexibility, building o...

New preprint led by Ivan Grahek!

Shifting demands of daily life require constant adjustments in how we allocate cognitive resources. Here we show that slower transitions between different cognitive strategies limit cognitive flexibility across the lifespan: biorxiv.org/content/10.1...

🧵 A thread:

In a TEDx talk just out, @ashenhav.bsky.social discusses what research from our lab teaches us about “How to choose when choosing is hardest” (the talk’s original title 😆):

➡️ www.youtube.com/watch?v=zeHg...

Control adjustment costs limit goal flexibility: Empirical evidence and a computational account A cornerstone of human intelligence is the ability to flexibly adjust our cognition and behavior as our goals change. For instance, achieving some goals requires efficiency, while others require cauti...

P.S. Free version of the article is here: www.biorxiv.org/content/10.1...
Check Berkeley’s recent coverage of the work here: ls.berkeley.edu/news/psychol...

Overall, we show that changing control states (attention and caution) to meet a new goal induces control adjustment costs, and that these costs arise from cognitive control dynamics. Good luck with your post-Twitter-scroll goals!

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).

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.

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.

Different performance goals require different cognitive control states. Performing a task quickly can be done with low levels of caution (Threshold) and attention (Drift rate), but being accurate (Accuracy goal) requires an increase in caution and attention.

After scrolling Twitter, it will take you a while to get back into “work mode”. Why is this the case? Our new work (out now in Psych Review), led by Ivan Grahek and Xiamin Leng, explores the costs of adjusting cognitive control to meet different goals:
psycnet.apa.org/record/2026-...

🧵 A thread:

Shameless advertising here, but if you have been asking yourself this question and are attending @cogscisociety.bsky.social come check out Ziwei’s talk tomorrow on her paper that received Cog Sci’s Computational Modeling Prize for Higher-Level Cognition!! 🎉🎉
bsky.app/profile/shen...

Come and see our work at #cogsci2025!
Ziwei Cheng will be presenting a talk “Incentive Effects Capture Variability in Task-General Control Allocation” on Fri 8/1 (4-5:30 pm, Cognition 7)
🔗Paper link: escholarship.org/content/qt7b...

A Novel Approach-Avoidance Task to Study Decision Making Under Outcome Uncertainty To behave adaptively, people need to integrate information about probabilistic outcomes and balance drives to approach positive outcomes and avoid negative outcomes. However, questions remain about ho...

Our newest preprint “A novel approach-avoidance task to study decision making under outcome uncertainty” investigates the dynamics of approach-avoid decisions!

Check out www.biorxiv.org/cgi/content/..., led by Ziwei Cheng and @nadjagingjehli.bsky.social

Considering What We Know and What We Don’t Know: Expectations and Confidence Guide Value Integration in Value-Based Decision-Making Abstract. When making decisions, we often have more information about some options than others. Previous work has shown that people are more likely to choose options that they look at more and those t...

Our newest paper, led by Romy Froemer
and @fredcallaway.bsky.social‬, is now out in Open Mind: “Considering What We Know and What We Don’t Know: Expectations and Confidence Guide Value Integration in Value-Based Decision-Making”

direct.mit.edu/opmi/article...

👉“Leveraging Continuous Psychophysics to Study Cognitive Control Allocation in Dynamic Environments” by Yihuan Dong (A117)

👉“The effect of acute stress on mental effort allocation across motivational contexts” by Tony El Nemer (A115)

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Attending #CNS2025? Check out the following posters!
(A98, A115, A117)

👉“Decoding Cognitive Control Dynamics: Neural Evidence of Inertia in Cognitive Control Adjustments Following Goal Changes” by Ivan Grahek (A98)

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Also at #AffectScience2025,

📣 Ivan Grahek will give the talk “Towards Emotion Regulation Dynamics: A View from Cognitive Control Optimization” for the New Perspectives on Effort in Emotion Regulation Symposium. See you there!

📅: Friday March 21st at 6pm

Currently at #AffectScience2025? 😁

👉Come visit Ziwei Cheng's poster “Dissociable Influences Of Positive And Negative Incentives On Challenge And Threat States During Mental Effort Allocation“ in Poster Session P1 (P1.T.141)

Federal budget cuts threaten the work of neuroscientist with Martin County roots | Opinion Sarah Heilbronner is a proud product of Martin County schools. However, federal budget cuts threaten important work she's doing in brain research.

Neuroscientist Sarah Heilbronner is a proud product of Martin County schools in Florida 🌴. However, federal budget cuts threaten important work she's doing in brain research. 🧪🏠
@srheilbronner.bsky.social
www.tcpalm.com/story/opinio...

Inside the Collapse at NIH Administration officials pressured NIH to avoid clear advice from the agency’s own lawyers to restart grant funding now.

By @katherinejwu.com

"The NIH... supported 99 percent of the drugs approved in the U.S. from 2010 to 2019. The agency has had a hand in “nearly all of our major medical breakthroughs over the past several decades,”

The NIH is in a struggle for its (and our) lives. This is existential to America:

Coming to a Zoom near you!
The affective gradient hypothesis: An affect-centered account of motivated behavior - Dr. Amitai Shenhav

NIH funding cuts could have ‘devastating impact’ on medical advancements, Chicago researchers say The National Institutes of Health under President Donald Trump announced this month that it was cutting payments covering overhead costs for research institutions that receive its grants.

Freezing out the NIH's funding means freezing out American innovation.

Research into curing cancer, Alzheimer's, and Parkinson's all delayed.

And ultimately it won't just cost us advancements in life-saving research, it will cost us lives.