What’s Worth the Risk? A Neural Circuit for Trade-Offs

Kolling, Nils; Rushworth, Matthew F. S.

doi:10.1016/j.cell.2015.05.031

Cited by 3 publications

(3 citation statements)

References 10 publications

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“…Such an approach is common in the literature and assumes that rewards have a similar effect across individuals to exert the associated effort [ 11 , 13 , 43 , 44 ]. However, preferences vary depending on subject-specific cost–benefit valuations, and SVs potentially afford a more sensitive measure of capturing individual differences in motivation [ 9 , 22 , 23 , 45 ]. Furthermore, SV has been proposed as an important entity in understanding apathy in healthy individuals as well as those with clinical disorders of motivation [ 8 , 21 , 46 ].…”

Section: Discussionmentioning

confidence: 99%

“…The key to elucidating the neural basis of cost–benefit decision making will be understanding how this domain-general network learns or forms a valuation of rewards associated with different forms of effort [ 15 , 22 ]. A central role of the dorsal ACC/dmPFC in value-based decision making and motivation is considered by some to be in signalling the value of a behaviour in comparison to alternatives [ 52 , 53 ].…”

Section: Discussionmentioning

confidence: 99%

“…Here, we used the computation of SV as a key operation to understand cost–benefit decision making across the domains of cognitive and physical effort [ 9 , 22 – 24 ]. In contrast to classical accounts, recent research in animals suggests that the mechanisms that underpin cognitive and physical effort discounting might be separable.…”

Section: Introductionmentioning

confidence: 99%

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Neurocomputational mechanisms underlying subjective valuation of effort costs

et al. 2017

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In everyday life, we have to decide whether it is worth exerting effort to obtain rewards. Effort can be experienced in different domains, with some tasks requiring significant cognitive demand and others being more physically effortful. The motivation to exert effort for reward is highly subjective and varies considerably across the different domains of behaviour. However, very little is known about the computational or neural basis of how different effort costs are subjectively weighed against rewards. Is there a common, domain-general system of brain areas that evaluates all costs and benefits? Here, we used computational modelling and functional magnetic resonance imaging (fMRI) to examine the mechanisms underlying value processing in both the cognitive and physical domains. Participants were trained on two novel tasks that parametrically varied either cognitive or physical effort. During fMRI, participants indicated their preferences between a fixed low-effort/low-reward option and a variable higher-effort/higher-reward offer for each effort domain. Critically, reward devaluation by both cognitive and physical effort was subserved by a common network of areas, including the dorsomedial and dorsolateral prefrontal cortex, the intraparietal sulcus, and the anterior insula. Activity within these domain-general areas also covaried negatively with reward and positively with effort, suggesting an integration of these parameters within these areas. Additionally, the amygdala appeared to play a unique, domain-specific role in processing the value of rewards associated with cognitive effort. These results are the first to reveal the neurocomputational mechanisms underlying subjective cost–benefit valuation across different domains of effort and provide insight into the multidimensional nature of motivation.

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Section: Discussionmentioning

confidence: 99%

Section: Discussionmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

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Neurocomputational mechanisms underlying subjective valuation of effort costs

et al. 2017

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Conserved features of anterior cingulate networks support observational learning across species

Burgos-Robles

Gothard

Monfils

et al. 2019

Neuroscience & Biobehavioral Reviews

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Translating Fear Circuitry: Amygdala Projections to Subgenual and Perigenual Anterior Cingulate in the Macaque

Sharma¹,

Kelly²,

Pfeifer³

et al. 2019

Cerebral Cortex

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Rodent fear-learning models posit that amygdala–infralimbic connections facilitate extinction while amygdala–prelimbic prefrontal connections mediate fear expression. Analogous amygdala–prefrontal circuitry between rodents and primates is not established. Using paired small volumes of neural tracers injected into the perigenual anterior cingulate cortex (pgACC; areas 24b and 32; a potential homologue to rodent prelimbic cortex) and subgenual anterior cingulate cortex (sgACC, areas 25 and 14c; a potential homologue to rodent infralimbic cortex) in a single hemisphere, we mapped amygdala projections to the pgACC and sgACC within single subjects. All injections resulted in dense retrograde labeling specifically within the intermediate division of the basal nucleus (Bi) and the magnocellular division of the accessory basal nucleus (ABmc). Areal analysis revealed a bias for connectivity with the sgACC, with the ABmc showing a greater bias than the Bi. Double fluorescence analysis revealed that sgACC and pgACC projections were intermingled within the Bi and ABmc, where a proportion were double labeled. We conclude that amygdala inputs to the ACC largely originate from the Bi and ABmc, preferentially connect to the sgACC, and that a subset collaterally project to both sgACC and pgACC. These findings advance our understanding of fear extinction and fear expression circuitry across species.

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What’s Worth the Risk? A Neural Circuit for Trade-Offs

Cited by 3 publications

References 10 publications

Neurocomputational mechanisms underlying subjective valuation of effort costs

Neurocomputational mechanisms underlying subjective valuation of effort costs

Conserved features of anterior cingulate networks support observational learning across species

Translating Fear Circuitry: Amygdala Projections to Subgenual and Perigenual Anterior Cingulate in the Macaque

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