The Neurobiology of Decision: Consensus and Controversy

Kable, Joseph W.; Glimcher, Paul W.

doi:10.1016/j.neuron.2009.09.003

Cited by 797 publications

(699 citation statements)

References 117 publications

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“…These findings are broadly consistent with evidence about other types of value-based decision making, which indicate that a distributed network of brain regions underpins decisions of this type, with key nodes in this network including orbitofrontal/vmPFC (Kable and Glimcher, 2009), dlPFC (Hare et al, 2009), ACC (Kennerley et al, 2011), and ventral striatum (Peters and Buchel, 2009). Although there is substantial overlap in the neural systems subserving decision making about different types of rewards , there also appear to be distinctions dependent on reward type Sescousse et al, 2010), indicating that domain-specific as well as more generalized choice networks may be involved in decisions about drugs.…”

Section: Introductionsupporting

confidence: 84%

An fMRI-Based Neural Signature of Decisions to Smoke Cannabis

Bedi

Lindquist

Haney

2015

Neuropsychopharmacol

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Drug dependence may be at its core a pathology of choice, defined by continued decisions to use drugs irrespective of negative consequences. Despite evidence of dysregulated decision making in addiction, little is known about the neural processes underlying the most clinically relevant decisions drug users make: decisions to use drugs. Here, we combined functional magnetic resonance imaging (fMRI), machine learning, and human laboratory drug administration to investigate neural activation underlying decisions to smoke cannabis. Nontreatment-seeking daily cannabis smokers completed an fMRI choice task, making repeated decisions to purchase or decline 1-12 placebo or active cannabis 'puffs' ($0.25-$5/puff). One randomly selected decision was implemented. If the selected choice had been bought, the cost was deducted from study earnings and the purchased cannabis smoked in the laboratory; alternatively, the participant remained in the laboratory without cannabis. Machine learning with leave-one-subject-out cross-validation identified distributed neural activation patterns discriminating decisions to buy cannabis from declined offers. A total of 21 participants were included in behavioral analyses; 17 purchased cannabis and were thus included in fMRI analyses. Purchasing varied lawfully with dose and cost. The classifier discriminated with 100% accuracy between fMRI activation patterns for purchased vs declined cannabis at the level of the individual. Dorsal striatum, insula, posterior parietal regions, anterior and posterior cingulate, and dorsolateral prefrontal cortex all contributed reliably to this neural signature of decisions to smoke cannabis. These findings provide the basis for a brain-based characterization of drug-related decision making in drug abuse, including effects of psychological and pharmacological interventions on these processes.

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Section: Introductionsupporting

confidence: 84%

An fMRI-Based Neural Signature of Decisions to Smoke Cannabis

Bedi

Lindquist

Haney

2015

Neuropsychopharmacol

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“…These findings suggest that the mOFC might comprise a common valuation region that encodes for both appetitive and aversive DVs (Litt et al 2011). These results and related ones using monetary gambles and trinkets (Chib et al 2009), or immediate and delayed rewards Glimcher 2007, 2010) provide evidence that the brain encodes a "common currency" that allows for a shared valuation for different categories of goods (see Kable and Glimcher 2009, for a review).…”

Section: Understanding Value and Its Computationmentioning

confidence: 63%

“…A number of studies have documented the key role of the orbitofrontal cortex in the valuation process (e.g., Kringelbach 2005;Kable and Glimcher 2009). An open question in the neuroscience of decision making has been whether the brain has implemented a system that tracks the subjective value of items for choice, how these systems are at play when consumers "miscompute" their subjective value resulting in disadvantageous decision-making outcomes such as obesity, and whether brain activity in these systems can be consciously regulated.…”

Section: Understanding Value and Its Computationmentioning

confidence: 99%

Decision neuroscience and consumer decision making

et al. 2012

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This article proposes that neuroscience can shape future theory and models in consumer decision making and suggests ways that neuroscience methods can be used in decision-making research. The article argues that neuroscience facilitates better theory development and empirical testing by considering the physiological context and the role of constructs such as hunger, stress, and social influence on consumer choice and preferences. Neuroscience can also provide new explanations Mark Lett (2012) 23:473-485

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“…One may also speculate that the model may inform the debate on the meaning of cognitive choice and control (Haggard, 2008;Kable and Glimcher, 2009). Our so-called choice of action at each stage of decision-making could be largely a function of the neural experience (as defined previously) of a name pathway and the nature of the stimulus at every such assessment point in a name network.…”

Section: Resultsmentioning

confidence: 99%

The Name Pathway, an Elementary Cognitive Model of Names as Sensory Representations

Dass¹

2014

American Journal of Neuroscience

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Names function as sensory representations, but the relationship between names and sensory stimuli/responses remains unclear. This study proposes the existence of a class of stimulus-response pathways, the name pathway, where a name is a reproducible and communicable symbol and the name pathway is one where the same name is both the stimulus and the response. Once a stimulus-response "name" pathway is formed as a result of reinforcement-based learning and in concert with the formation of the associated stimulus-response "sensory" pathway for a named object, act or process, Hebbian cross-pathway connectivity between the sensory and name pathways allows each pathway's stimulus to activate the other's response. The model proposes that every higher-order cognitive function exists only because it was named and that each such function may be defined mechanistically to be the outcome of the "recognition," "interpretation," and "retrieval" of sensory experiences from networks of names for that function.

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The Neurobiology of Decision: Consensus and Controversy

Cited by 797 publications

References 117 publications

An fMRI-Based Neural Signature of Decisions to Smoke Cannabis

An fMRI-Based Neural Signature of Decisions to Smoke Cannabis

Decision neuroscience and consumer decision making

The Name Pathway, an Elementary Cognitive Model of Names as Sensory Representations

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