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Article: Proactive and reactive construction of memory-based preferences.

Nicholas, Jonathan / Daw, Nathaniel D / Shohamy, Daphna

bioRxiv : the preprint server for biology

2023

Abstract: We are often faced with decisions we have never encountered before, requiring us to infer possible outcomes before making a choice. Computational theories suggest that one way to make these types of decisions is by accessing and linking related ... ...

Abstract	We are often faced with decisions we have never encountered before, requiring us to infer possible outcomes before making a choice. Computational theories suggest that one way to make these types of decisions is by accessing and linking related experiences stored in memory. Past work has shown that such memory-based preference construction can occur at a number of different timepoints relative to the moment a decision is made. Some studies have found that memories are integrated at the time a decision is faced (reactively) while others found that memory integration happens earlier, when memories are encoded (proactively). Here we offer a resolution to this inconsistency. We demonstrate behavioral and neural evidence for both strategies and for how they tradeoff rationally depending on the associative structure of memory. Using fMRI to decode patterns of brain responses unique to categories of images in memory, we found that proactive memory access is more common and allows more efficient inference. However, participants also use reactive access when choice options are linked to more numerous memory associations. Together, these results indicate that the brain judiciously conducts proactive inference by accessing memories ahead of time in conditions when this strategy is most favorable.
Language	English
Publishing date	2023-12-11
Publishing country	United States
Document type	Preprint
DOI	10.1101/2023.12.10.570977
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Article ; Online: The role of memory in counterfactual valuation.

Biderman, Natalie / Gershman, Samuel J / Shohamy, Daphna

Journal of experimental psychology. General

2023 Volume 152, Issue 6, Page(s) 1754–1767

Abstract: Value-based decisions are often guided by past experience. If a choice led to a good outcome, we are more likely to repeat it. This basic idea is well-captured by reinforcement-learning models. However, open questions remain about how we assign value to ... ...

Abstract	Value-based decisions are often guided by past experience. If a choice led to a good outcome, we are more likely to repeat it. This basic idea is well-captured by reinforcement-learning models. However, open questions remain about how we assign value to options we did not choose and which we therefore never had the chance to learn about directly. One solution to this problem is proposed by policy gradient reinforcement-learning models; these do not require direct learning of value, instead optimizing choices according to a behavioral policy. For example, a logistic policy predicts that if a chosen option was rewarded, the unchosen option would be deemed less desirable. Here, we test the relevance of these models to human behavior and explore the role of memory in this phenomenon. We hypothesize that a policy may emerge from an associative memory trace formed during deliberation between choice options. In a preregistered study (
MeSH term(s)	Humans ; Decision Making ; Choice Behavior ; Learning ; Reinforcement, Psychology ; Reward
Language	English
Publishing date	2023-05-18
Publishing country	United States
Document type	Journal Article
ZDB-ID	189732-9
ISSN	1939-2222 ; 0096-3445
ISSN (online)	1939-2222
ISSN	0096-3445
DOI	10.1037/xge0001364
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Article ; Online: Memory and decision making interact to shape the value of unchosen options.

Biderman, Natalie / Shohamy, Daphna

Nature communications

2021 Volume 12, Issue 1, Page(s) 4648

Abstract: The goal of deliberation is to separate between options so that we can commit to one and leave the other behind. However, deliberation can, paradoxically, also form an association in memory between the chosen and unchosen options. Here, we consider this ... ...

Abstract	The goal of deliberation is to separate between options so that we can commit to one and leave the other behind. However, deliberation can, paradoxically, also form an association in memory between the chosen and unchosen options. Here, we consider this possibility and examine its consequences for how outcomes affect not only the value of the options we chose, but also, by association, the value of options we did not choose. In five experiments (total n = 612), including a preregistered experiment (n = 235), we found that the value assigned to unchosen options is inversely related to their chosen counterparts. Moreover, this inverse relationship was associated with participants' memory of the pairs they chose between. Our findings suggest that deciding between options does not end the competition between them. Deliberation binds choice options together in memory such that the learned value of one can affect the inferred value of the other.
MeSH term(s)	Adult ; Algorithms ; Bayes Theorem ; Choice Behavior/physiology ; Decision Making/physiology ; Female ; Humans ; Linear Models ; Male ; Memory/physiology ; Models, Theoretical ; Motivation ; Pilot Projects ; Reward ; Young Adult
Language	English
Publishing date	2021-07-30
Publishing country	England
Document type	Journal Article ; Research Support, N.I.H., Extramural ; Research Support, Non-U.S. Gov't ; Research Support, U.S. Gov't, Non-P.H.S.
ZDB-ID	2553671-0
ISSN	2041-1723 ; 2041-1723
ISSN (online)	2041-1723
ISSN	2041-1723
DOI	10.1038/s41467-021-24907-x
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Article ; Online: Uncertainty alters the balance between incremental learning and episodic memory.

Nicholas, Jonathan / Daw, Nathaniel D / Shohamy, Daphna

eLife

2022 Volume 11

Abstract: A key question in decision making is how humans arbitrate between competing learning and memory systems to maximize reward. We address this question by probing the balance between the effects, on choice, of incremental trial-and-error learning versus ... ...

Abstract	A key question in decision making is how humans arbitrate between competing learning and memory systems to maximize reward. We address this question by probing the balance between the effects, on choice, of incremental trial-and-error learning versus episodic memories of individual events. Although a rich literature has studied incremental learning in isolation, the role of episodic memory in decision making has only recently drawn focus, and little research disentangles their separate contributions. We hypothesized that the brain arbitrates rationally between these two systems, relying on each in circumstances to which it is most suited, as indicated by uncertainty. We tested this hypothesis by directly contrasting contributions of episodic and incremental influence to decisions, while manipulating the relative uncertainty of incremental learning using a well-established manipulation of reward volatility. Across two large, independent samples of young adults, participants traded these influences off rationally, depending more on episodic information when incremental summaries were more uncertain. These results support the proposal that the brain optimizes the balance between different forms of learning and memory according to their relative uncertainties and elucidate the circumstances under which episodic memory informs decisions.
Language	English
Publishing date	2022-12-02
Publishing country	England
Document type	Journal Article
ZDB-ID	2687154-3
ISSN	2050-084X ; 2050-084X
ISSN (online)	2050-084X
ISSN	2050-084X
DOI	10.7554/eLife.81679
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Article ; Online: Visuospatial information foraging describes search behavior in learning latent environmental features.

Barack, David L / Bakkour, Akram / Shohamy, Daphna / Salzman, C Daniel

Scientific reports

2023 Volume 13, Issue 1, Page(s) 1126

Abstract: In the real world, making sequences of decisions to achieve goals often depends upon the ability to learn aspects of the environment that are not directly perceptible. Learning these so-called latent features requires seeking information about them. ... ...

Abstract	In the real world, making sequences of decisions to achieve goals often depends upon the ability to learn aspects of the environment that are not directly perceptible. Learning these so-called latent features requires seeking information about them. Prior efforts to study latent feature learning often used single decisions, used few features, and failed to distinguish between reward-seeking and information-seeking. To overcome this, we designed a task in which humans and monkeys made a series of choices to search for shapes hidden on a grid. On our task, the effects of reward and information outcomes from uncovering parts of shapes could be disentangled. Members of both species adeptly learned the shapes and preferred to select tiles expected to be informative earlier in trials than previously rewarding ones, searching a part of the grid until their outcomes dropped below the average information outcome-a pattern consistent with foraging behavior. In addition, how quickly humans learned the shapes was predicted by how well their choice sequences matched the foraging pattern, revealing an unexpected connection between foraging and learning. This adaptive search for information may underlie the ability in humans and monkeys to learn latent features to support goal-directed behavior in the long run.
MeSH term(s)	Humans ; Learning ; Feeding Behavior ; Reward ; Choice Behavior
Language	English
Publishing date	2023-01-20
Publishing country	England
Document type	Journal Article ; Research Support, N.I.H., Extramural ; Research Support, Non-U.S. Gov't
ZDB-ID	2615211-3
ISSN	2045-2322 ; 2045-2322
ISSN (online)	2045-2322
ISSN	2045-2322
DOI	10.1038/s41598-023-27662-9
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Article ; Online: Preserved motor memory in Parkinson's disease.

Lahlou, Soraya / Gabitov, Ella / Owen, Lucy / Shohamy, Daphna / Sharp, Madeleine

Neuropsychologia

2022 Volume 167, Page(s) 108161

Abstract: Patients with Parkinson's disease, who lose the dopaminergic projections to the striatum, are impaired in certain aspects of motor learning. Recent evidence suggests that, in addition to its role in motor performance, the striatum plays a key role in the ...

Abstract	Patients with Parkinson's disease, who lose the dopaminergic projections to the striatum, are impaired in certain aspects of motor learning. Recent evidence suggests that, in addition to its role in motor performance, the striatum plays a key role in the memory of motor learning. Whether Parkinson's patients have impaired motor memory and whether motor memory is modulated by dopamine at the time of initial learning is unknown. To address these questions, we measured memory of a learned motor sequence in Parkinson's patients who were either On or Off their dopaminergic medications at the time of initial learning. We compared them to a group of older and younger controls. Contrary to our predictions, motor memory was not impaired in patients compared to older controls, and was not influenced by dopamine state at the time of initial learning. To probe post-learning consolidation processes, we also tested whether learning a new sequence shortly after learning the initial sequence would interfere with later memory. We found that, in contrast to younger adults, neither older adults nor patients were susceptible to this interference. These findings suggest that motor memory is preserved in Parkinson's patients and raise the possibility that motor memory in patients is supported by compensatory non-dopamine sensitive mechanisms. Furthermore, given the similar performance characteristics observed in the patients and older adults and the absence of an effect of dopamine, these results raise the possibility that aging and Parkinson's disease affect motor memory in similar ways.
MeSH term(s)	Aged ; Corpus Striatum ; Dopamine ; Dopamine Agents/pharmacology ; Dopamine Agents/therapeutic use ; Humans ; Learning ; Parkinson Disease/complications ; Parkinson Disease/drug therapy
Chemical Substances	Dopamine Agents ; Dopamine (VTD58H1Z2X)
Language	English
Publishing date	2022-01-15
Publishing country	England
Document type	Journal Article ; Research Support, Non-U.S. Gov't
ZDB-ID	207151-4
ISSN	1873-3514 ; 0028-3932
ISSN (online)	1873-3514
ISSN	0028-3932
DOI	10.1016/j.neuropsychologia.2022.108161
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Article ; Online: Learning and motivation in the human striatum.

Shohamy, Daphna

Current opinion in neurobiology

2011 Volume 21, Issue 3, Page(s) 408–414

Abstract: The past decade has seen a dramatic change in our understanding of the role of the striatum in behavior. Early perspectives emphasized a role for the striatum in habitual learning of stimulus-response associations and sequences of actions. Recent ... ...

Abstract	The past decade has seen a dramatic change in our understanding of the role of the striatum in behavior. Early perspectives emphasized a role for the striatum in habitual learning of stimulus-response associations and sequences of actions. Recent advances from human neuroimaging research suggest a broader role for the striatum in motivated learning. New findings demonstrate that the striatum represents multiple learning signals and highlight the contribution of the striatum across many cognitive domains and contexts. Recent findings also emphasize interactions between the striatum and other specialized brain systems for learning. Together, these findings suggest that the striatum contributes to a distributed network that learns to select actions based on their predicted value in order to optimize behavior.
MeSH term(s)	Corpus Striatum/physiology ; Humans ; Learning/physiology ; Motivation/physiology
Language	English
Publishing date	2011-06
Publishing country	England
Document type	Journal Article ; Research Support, Non-U.S. Gov't ; Research Support, U.S. Gov't, Non-P.H.S. ; Review
ZDB-ID	1078046-4
ISSN	1873-6882 ; 0959-4388
ISSN (online)	1873-6882
ISSN	0959-4388
DOI	10.1016/j.conb.2011.05.009
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Article ; Online: What Are Memories For? The Hippocampus Bridges Past Experience with Future Decisions.

Biderman, Natalie / Bakkour, Akram / Shohamy, Daphna

Trends in cognitive sciences

2020 Volume 24, Issue 7, Page(s) 542–556

Abstract: Many decisions require flexible reasoning that depends on inference, generalization, and deliberation. Here, we review emerging findings indicating that the hippocampus, known for its role in long-term memory, contributes to these flexible aspects of ... ...

Abstract	Many decisions require flexible reasoning that depends on inference, generalization, and deliberation. Here, we review emerging findings indicating that the hippocampus, known for its role in long-term memory, contributes to these flexible aspects of value-based decision-making. This work offers new insights into the role of memory in decision-making and suggests that memory may shape decisions even in situations that do not appear, at first glance, to depend on memory at all. Uncovering the pervasive role of memory in decision-making challenges the way we define what memory is and what it does, suggesting that memory's primary purpose may be to guide future behavior and that storing a record of the past is just one way to do so.
MeSH term(s)	Decision Making ; Generalization, Psychological ; Hippocampus ; Humans ; Memory
Language	English
Publishing date	2020-06-05
Publishing country	England
Document type	Journal Article ; Research Support, Non-U.S. Gov't ; Review
ZDB-ID	2010989-1
ISSN	1879-307X ; 1364-6613
ISSN (online)	1879-307X
ISSN	1364-6613
DOI	10.1016/j.tics.2020.04.004
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Article ; Online: An energizing role for motivation in information-seeking during the early phase of the COVID-19 pandemic.

Abir, Yaniv / Marvin, Caroline B / van Geen, Camilla / Leshkowitz, Maya / Hassin, Ran R / Shohamy, Daphna

Nature communications

2022 Volume 13, Issue 1, Page(s) 2310

Abstract: The COVID-19 pandemic has highlighted the importance of understanding and managing information seeking behavior. Information-seeking in humans is often viewed as irrational rather than utility maximizing. Here, we hypothesized that this apparent ... ...

Abstract	The COVID-19 pandemic has highlighted the importance of understanding and managing information seeking behavior. Information-seeking in humans is often viewed as irrational rather than utility maximizing. Here, we hypothesized that this apparent disconnect between utility and information-seeking is due to a latent third variable, motivation. We quantified information-seeking, learning, and COVID-19-related concern (which we used as a proxy for motivation regarding COVID-19 and the changes in circumstance it caused) in a US-based sample (n = 5376) during spring 2020. We found that self-reported levels of COVID-19 concern were associated with directed seeking of COVID-19-related content and better memory for such information. Interestingly, this specific motivational state was also associated with a general enhancement of information-seeking for content unrelated to COVID-19. These effects were associated with commensurate changes to utility expectations and were dissociable from the influence of non-specific anxiety. Thus, motivation both directs and energizes epistemic behavior, linking together utility and curiosity.
MeSH term(s)	Anxiety ; COVID-19 ; Humans ; Information Seeking Behavior ; Motivation ; Pandemics
Language	English
Publishing date	2022-04-28
Publishing country	England
Document type	Journal Article ; Research Support, Non-U.S. Gov't
ZDB-ID	2553671-0
ISSN	2041-1723 ; 2041-1723
ISSN (online)	2041-1723
ISSN	2041-1723
DOI	10.1038/s41467-022-30011-5
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Article ; Online: The Role of the Cerebellum in Learning to Predict Reward: Evidence from Cerebellar Ataxia.

Nicholas, Jonathan / Amlang, Christian / Lin, Chi-Ying R / Montaser-Kouhsari, Leila / Desai, Natasha / Pan, Ming-Kai / Kuo, Sheng-Han / Shohamy, Daphna

Cerebellum (London, England)

2023

Abstract: Recent findings in animals have challenged the traditional view of the cerebellum solely as the site of motor control, suggesting that the cerebellum may also be important for learning to predict reward from trial-and-error feedback. Yet, evidence for ... ...

Abstract	Recent findings in animals have challenged the traditional view of the cerebellum solely as the site of motor control, suggesting that the cerebellum may also be important for learning to predict reward from trial-and-error feedback. Yet, evidence for the role of the cerebellum in reward learning in humans is lacking. Moreover, open questions remain about which specific aspects of reward learning the cerebellum may contribute to. Here we address this gap through an investigation of multiple forms of reward learning in individuals with cerebellum dysfunction, represented by cerebellar ataxia cases. Nineteen participants with cerebellar ataxia and 57 age- and sex-matched healthy controls completed two separate tasks that required learning about reward contingencies from trial-and-error. To probe the selectivity of reward learning processes, the tasks differed in their underlying structure: while one task measured incremental reward learning ability alone, the other allowed participants to use an alternative learning strategy based on episodic memory alongside incremental reward learning. We found that individuals with cerebellar ataxia were profoundly impaired at reward learning from trial-and-error feedback on both tasks, but retained the ability to learn to predict reward based on episodic memory. These findings provide evidence from humans for a specific and necessary role for the cerebellum in incremental learning of reward associations based on reinforcement. More broadly, the findings suggest that alongside its role in motor learning, the cerebellum likely operates in concert with the basal ganglia to support reinforcement learning from reward.
Language	English
Publishing date	2023-12-08
Publishing country	United States
Document type	Journal Article
ZDB-ID	2112586-7
ISSN	1473-4230 ; 1473-4222
ISSN (online)	1473-4230
ISSN	1473-4222
DOI	10.1007/s12311-023-01633-2
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