Conceptual representations in goal-directed decision making

Shea, Nicholas; Krug, Kristine; Tobler, Philippe N.

doi:10.3758/cabn.8.4.418

Cited by 18 publications

(10 citation statements)

References 83 publications

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“…Previous work has emphasized the role of the vMPFC, and closely situated orbitofrontal cortex (OFC), in goal-directed decision making (Daw et al., 2005; Rangel et al., 2008; Rudebeck et al., 2008), based on outcome expectancies (Murray et al., 2007), simple if-then rules (e.g., match versus nonmatch [Hampton et al., 2006; Miller et al., 2002; Otto and Eichenbaum, 1992]), and the integration of social and reward information (Behrens et al., 2008). While conceptual knowledge has often been assumed to influence goal-directed behavior in humans (Shea et al., 2008), our study highlights its profound effect on participants' behavior and shows that this is reflected in neural activity in vMPFC, adding a further level of abstraction to the nature of neural representations it sustains.…”

Section: Resultsmentioning

confidence: 99%

“…While conceptual knowledge is thought to play an influential role in human decision making (Shea et al., 2008), the neural mechanisms underpinning its emergence and influence on choice behavior have been little studied until now. Here, we reveal that the vMPFC, in concert with the hippocampus, underpins conceptual decision making, implying that this neural circuit comprises an important, but until now neglected, part of the goal-directed system in humans.…”

Section: Resultsmentioning

confidence: 99%

“…For instance, although an Alsatian and a Chihuahua look perceptually very different, we can easily appreciate that they have similar attributes (e.g., they bark) because they can be recognized as instances of a particular concept, in this case a dog (Locke, 1690; Martin, 2007; Murphy, 2004; Rogers and McClelland, 2004). While the devastating consequences of the degradation of well-established conceptual representations are all too apparent in neurological conditions like semantic dementia (Patterson et al., 2007), little is known about the neural mechanisms underpinning the emergence of conceptual knowledge, its application in novel settings, and its influence on human decision making (Shea et al., 2008). …”

Section: Introductionmentioning

confidence: 99%

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Tracking the Emergence of Conceptual Knowledge during Human Decision Making

Kumaran

Summerfield

Hassabis

et al. 2009

Neuron

250

235

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SummaryConcepts lie at the very heart of intelligence, providing organizing principles with which to comprehend the world. Surprisingly little, however, is understood about how we acquire and deploy concepts. Here, we show that a functionally coupled circuit involving the hippocampus and ventromedial prefrontal cortex (vMPFC) underpins the emergence of conceptual knowledge and its effect on choice behavior. Critically, the hippocampus alone supported the efficient transfer of knowledge to a perceptually novel setting. These findings provide compelling evidence that the hippocampus supports conceptual learning through the networking of discrete memories and reveal the nature of its interaction with downstream valuation modules such as the vMPFC. Our study offers neurobiological insights into the remarkable capacity of humans to discover the conceptual structure of related experiences and use this knowledge to solve exacting decision problems.

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Section: Resultsmentioning

confidence: 99%

Section: Resultsmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

See 1 more Smart Citation

Tracking the Emergence of Conceptual Knowledge during Human Decision Making

Kumaran

Summerfield

Hassabis

et al. 2009

Neuron

250

235

View full text Add to dashboard Cite

show abstract

“…Research has shown that memories are organized and stored in a manner that assigns meaning to experience (Bartlett, 1932); memories guide behavior (Bartlett, 1932;Shea, Krug, & Tobler, 2008;Kumeran et al, 2009), and facilitate encoding and retrieval (Anderson, 1984;Preston & Eichenbaum, 2013;Preston & Eichenbaum, 2013;Van Kesteren et al, 2013). One way researchers and theorists have conceptualized the organization and storage of memories is based in schema theory (Bartlett, 1932;Markus & Zajonc, 1985).…”

Section: Schema Theorymentioning

confidence: 99%

Validity, interrater reliability, and measures of adaptive behavior: Concerns regarding the probative versus prejudicial value.

Salekin¹,

Neal²,

Hedge³

2018

Psychology, Public Policy, and Law

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The question as to whether the assessment of adaptive behavior (AB) for evaluations of intellectual disability (ID) in the community meet the level of rigor necessary for admissibility in legal cases is addressed. Adaptive behavior measures have made their way into the forensic domain where scientific evidence is put under great scrutiny. Assessment of ID in capital murder proceedings has garnished a lot of attention, but assessments of ID in adult populations also occur with some frequency in the context of other criminal proceedings (e.g., competence to stand trial; competence to waive Miranda rights), as well as eligibility for social security disability, social security insurance, Medicaid/Medicare, government housing, and postsecondary transition services. As will be demonstrated, markedly disparate findings between raters can occur on measures of AB even when the assessment is conducted in accordance with standard procedures (i.e., the person was assessed in a community setting, in real time, with multiple appropriate raters, when the person was younger than 18 years of age) and similar disparities can be found in the context of the unorthodox and untested retrospective assessment used in capital proceedings. With full recognition that some level of disparity is to be expected, the level of disparity that can arise when these measures are administered retrospectively calls into question the validity of the results and consequently, their probative value.

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“…Concepts like "carnival currency" or "world currency" can support decisionmaking and efficient learning about individual coins by allowing for inferences across different coins that share feature relationships [3].…”

Section: Introductionmentioning

confidence: 99%

Dynamic integration of conceptual information during learning

Inhoff

Libby

Noguchi

et al. 2018

Preprint

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The development and application of concepts is a critical component of cognition. Although concepts can be formed on the basis of simple perceptual or semantic features, conceptual representations can also capitalize on similarities across feature relationships. By representing these types of higher-order relationships, concepts can simplify the learning problem and facilitate decisions.Despite this, little is known about the neural mechanisms that support the construction and deployment of these kinds of higher-order concepts during learning. To address this question, we combined a carefully designed associative learning task with computational model-based functional magnetic resonance imaging (fMRI). Participants were scanned as they learned and made decisions about sixteen pairs of cues and associated outcomes. Associations were structured such that individual cues shared feature relationships, operationalized as shared patterns of cue pair-outcome associations. In order to capture the large number of possible conceptual representational structures that participants might employ and to evaluate how conceptual representations are used during learning, we leveraged a well-specified Bayesian computational model of category learning [1]. Behavioral and model-based results revealed that participants who displayed a tendency to link experiences in memory benefitted from faster learning rates, suggesting that the use of the conceptual structure in the task facilitated decisions about cue pair-outcome associations. Model-based fMRI analyses revealed that trial-by-trial integration of cue information into

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Conceptual representations in goal-directed decision making

Cited by 18 publications

References 83 publications

Tracking the Emergence of Conceptual Knowledge during Human Decision Making

Tracking the Emergence of Conceptual Knowledge during Human Decision Making

Validity, interrater reliability, and measures of adaptive behavior: Concerns regarding the probative versus prejudicial value.

Dynamic integration of conceptual information during learning

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